OPSPORING VAN BORSTKANKER TUSSEN 70 EN 74 JAAR

KCE REPORT 176A

OPSPO ORING VAN BO ORSTK KANKER R TUSSEN 70 EN 74 JAAR

2012

www.kce.fgo ov.be

Het Federa aal Kennisce entrum voor de Gezond dheidszorg Het Federaal Kenniscentrum voorr de Gezondhe eidszorg is een parastatale, opgericht door de progrrammawet (1) va an 24 decemberr 2002 (artikelen 259 tot 281) die e onder de bevo oegdheid valt va an de Minis ster van Volksg gezondheid en Sociale Zaken.. Het Centrum is belast met het realiseren van beleid dsondersteunende studies binne en de sector van de gezondheids szorg en de ziektteverzekering.

Raad van Bestuur B Voorz zitter Leidend ambtenaar RIZ ZIV (vice-voorzitte er) Voorz zitter FOD Volksge ezondheid (vice-v voorzitter) Voorz zitter FOD Sociale e Zekerheid (vice-voorzitter) Admin nistrateur-generaa al FAGG Verteg genwoordigers Minister van Volksg gezondheid Verteg genwoordigers Minister van Sociale e Zaken Verteg genwoordigers Ministerraad Interm mutualistisch Agen ntschap

Beroe epsverenigingen van v de artsen Beroe epsverenigingen van v de verpleegku undigen Ziekenhuisfederaties Socia ale partners Kame er van Volksverteg genwoordigers

Efffectieve Leden

Plaatsvervangende Leden

Pie erre Gillet Jo De Cock Dirrk Cuypers Fra ank Van Massenh hove

Benoît Collin Chris D Decoster Jan Be ertels

Xa avier De Cuyper Be ernard Lange Ma arco Schetgen Oliver de Stexhe Ri De Ridder Jea an-Noël Godin Da aniel Devos Mic chiel Callens Pa atrick Verertbrugge en Xa avier Brenez Ma arc Moens Jea an-Pierre Baeyens Mic chel Foulon My yriam Hubinon Joh han Pauwels Jea an-Claude Praet Ritta Thys Pa aul Palsterman Lie eve Wierinck

Greet M Musch Franço ois Perl Annickk Poncé Karel V Vermeyen Lambe ert Stamatakis Frédérric Lernoux oghe Bart Oo Frank D De Smet Yoland de Husden Geert M Messiaen Roland d Lemye Rita Cu uypers Ludo M Meyers Olivier Thonon Katrien n Kesteloot Pierre Smiets Leo Ne eels Celien Van Moerkerke

Controle

Regeringscommissaris s

Yves Roger

Directie

Algem meen Directeur Adjun nct Algemeen Dire ecteur Progrrammadirectie

Ra af Mertens Jea an-Pierre Closon

Contact

Ch hristian Léonard Kristel De Gauquier

Federaal Kenniscentru um voor de Gezon ndheidszorg (KCE E) e Doorb building (10 verdieping) Kruid dtuinlaan 55 B-100 00 Brussel Belgium T +32 2 [0]2 287 33 88 F +32 2 [0]2 287 33 85 info@ @kce.fgov.be http:///www.kce.fgov.be e

KCE REPORT 176A GOOD CLINICA AL PRACTICE

OPSPO ORING VAN BO ORSTK KANKER R TUSSEN 70 EN 74 JAAR

FRANÇOISE MAMBOURG, M JO R ROBAYS, SOPHIIE GERKENS

2012

www.kce.fgo ov.be

COLOFON N Titel:

poring van borstka anker tussen 70 en e 74 jaar Opsp

Auteurs:

Françoise Mambourg (KCE), Jo Robays s (KCE), Sophie Gerkens G (KCE)

Reviewers:

Frank Hulstaert (KCE)), Pascale Jonckh heer (KCE), Nancy y Thiry (KCE)

Externe experte en:

Marc c Arbijn (WIV - IS SP), Martine Berliière (UCL Saint-L Luc), Hilde Bosmans (UZ Leuven)), Jean-Benoit Bu urrion (ASB BL Brummammo), Joëlle Desreux x (CHU Liège), André-Robert A Griv vegnée (Institut JJules Bordet), Pa atrick Neve en (UZ Leuven), Myriam M Provost (S SSMG), Hubert Th hierens (UGent), Reinhilde R Van Ee eckhoudt (WVG), Anne A Vand denbroucke (UCL Saint-Luc), Geertt Villeirs (UZ Gentt).

Externe Validattoren:

Philip ppe Autier (IPRI-L Lyon), Geert Page e (Jan Yperman Ziekenhuis), Z Chanttal Van Ongeval ((KU Leuven)

Belangenconflic ct:

Geen n gemeld

Layout:

Ine Verhulst V

Disclaimer:

• De D externe expert rten werden gera aadpleegd over een e (preliminaire e) versie van het wetenschappelijke ra apport. Hun opm merkingen werde en tijdens vergad deringen bespro oken. Zij zijn gee en coauteur van n het wetenschappelijk w e rapport en ging gen niet noodzakelijk akkoord met m de inhoud erv van. • Vervolgens werd een (finale) vers sie aan de valida atoren voorgelegd. De validatie v van het rapport volgt v uit een consensu us of een meerd derheidsstem tus ssen de validato oren. Zij zijn gee en coauteur van het wetenschappelijk w e rapport en ging gen niet noodzakelijk alle drie ak kkoord met de in nhoud ervan. • To ot slot werd dit rapport r unaniem goedgekeurd do oor de Raad van Bestuur. • Alleen A het KCE is s verantwoordellijk voor de eventuele resterend de vergissingen of onvolledighe eden allsook voor de aa anbevelingen aan n de overheid.

Publicatiedatum m:

26 ap pril 2012

Domein:

Good d Clinical Practice e (GCP)

MeSH:

Breast Neoplasms ; Mammography M ; Mass Screening

NLM classificattie:

WP 870 8 - Breast - Neo oplasms

Taal:

Nede erlands, Engels

Formaat:

Adob be® PDF™ (A4)

Wettelijk depot::

D/2012/10.273/18

Copyright:

De KCE-rapporten K w worden gepublice eerd onder de Licentie L Creative e Commons « b by/nc/nd » http:///kce.fgov.be/nl/co ontent/de-copyrigh hts-van-de-kce-ra apporten

Hoe refereren naar n dit documentt?

Mam mbourg F, Robays J, Gerkens S. Opsporing van bors stkanker tussen 70 7 en 74 jaar. Good Clinical Practtice (GCP). Brus ssel: Federaal Ke enniscentrum voo or de Gezondheiidszorg (KCE). 2 2012. KCE Repo ort 176A. D/2012/10.273/18. Dit document is be eschikbaar op de website van n het Federaal Kenniscentrum voor de Gezo ondheidszorg.

KCE Report 176 6A

VOOR RWOORD

Opsporing borstk kanker

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Keuz zes maken in de zorg z – het lijkt sne el op discriminatie e, zeker wanneer de d keuze gebeurtt op basis van lee eftijd. Hoe kan men bijvoo orbeeld verantwo oorden om aan een oudere patiënt de terugbeta aling voor een dure d hartin ngreep te ontzeggen, louter omwille van een leeftijjdscriterium, ook al is hij of zij voo or het overige no og in goed de algemene toes stand? Dergelijke denkpistes roepe en steevast een verhitte v maatschappelijke discussie e op, gevo oed vanuit soms diametraal tegenov ver mekaar staande waardensystemen. Met deze studie overr het al dan niet aanbieden a van een georganiseerd de borstkankerscrreening aan vrou uwen tusse en de 70 en 74 ja aar begeven we ons o dus andermaa al op glad ijs. Maa ar ook om andere e redenen moeten n we hier extra e waakzaam zijn. Zoals bij elke georganiseerde e opsporing richt men zich tot men nsen die a priori geen g gezo ondheidsklachten hebben en dus ook o niet noodzake elijk om dit onderrzoek gevraagd h hebben. Het adag gium primu um non nocere is hier dus des te belangrijker. Ook op het vlak van het te gebruiken argumentarium staan s we voor ee en bijzondere uitd daging. De clinicu us is imme ers doorgaans ve eel vertrouwder met m de logica van de diagnosestellling bij een perso oon met klachten dan met deze d van screenin ng. In het eerste geval g is het risico op vals positieve resultaten niet allleen kleiner, maar het word dt duidelijk ook als minder belang grijk gezien dan het h risico op een n vals negatief re esultaat, namelijk k het missen van een diag gnose. Dit verkla aart mede waaro om de nadelen van screening ssystematisch worden onde erschat. Bovendien laat het onderw werp de publieke opinie o zeker niet onberoerd, o er word dt druk rond gelob bbyd en he et ligt (dus) ook po olitiek gevoelig. Ook al mobiliseert me en alle op dit mom ment voorhanden zijnde z wetenschappelijke bevinding gen om een advie es te funde eren, toch kan me en niet hopen datt hiermee de conttroverse zal opho ouden. Alleen durvven we hopen da at we met dit d rapport beantw woorden aan wat men in een derge elijk debat van ee en wetenschappelijk adviesorgaan mag verw wachten.

Jean n-Pierre CLOSON Adjun nct Algemeen Directeur

Raf MERTENS Algemeen Directe eur

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KORT TE SAME ENVATT TING


KCE Report 176A 1

INLEIDING G Dit werk maakt de D eel uit van een groter g project mett als doel het upd daten v van het rapport: "Borstkankerscre eening", gepublicceerd in 2005 (KCE( ra apport nr. 11). Het H gaat hier me eer bepaald om de uitbreiding va an de g georganiseerde sc creening naar vrouwen van 70 tot 7 74 jaar die voor de e rest g geen enkel symptoom vertonen dat op borstkanke er zou kunnen wijzen, w n noch enige specifieke risicofactor hebben. B Borstkankerscreen ning is een com mplex proces datt zowel voordelen als n nadelen inhoudt. De D voornaamste voordelen v van borrstkankerscreenin ng zijn e een daling van de d mortaliteit en de morbiditeit d door borstkanker. Een d daling van de morrbiditeit houdt ofw wel in dat een mind der zware behand deling k worden gegev kan ven, ofwel dat er minder recidieven n optreden of de ziekte z m minder vaak het gemetastaseerde stadium s bereikt. D voornaamste nadelen van de screening hebb De ben te maken me et de le evenskwaliteit. Een E vals-positief resultaat, een onterechte diag gnose (o overdiagnose) ge evolgd door een behandeling b en h het vervroegen va an de d diagnose kunnen de d levenskwaliteitt inderdaad negattief beïnvloeden. V Vals-positieve res sultaten doen ge ezonde vrouwen terechtkomen in n een c circuit van ang gstwekkende, en n soms zelfs invasieve (biop psies) d diagnostische ond derzoeken. O Overdiagnose ka an worden ge edefinieerd als de opsporing van k kankergevallen die e zonder screenin ng nooit klinisch zzouden zijn opgem merkt, e de frequentie en e neemt toe na aarmate de leve ensverwachting in de g gescreende populatie lager wordtt. Overbehandelin ng is een gevolg g van o overdiagnose. Om mdat het op dit mo oment onmogelijkk is te voorspellen n hoe e een kanker verder zal evolueren n, wordt het ovvergrote deel va an de g gediagnosticeerde e kankers behandeld. D Door screening ko omen kankers twe ee tot drie jaar ee erder aan het lich ht dan d door klinische dia agnose. Hierdoor wordt de vrouw dus reeds vroeg ger in h haar leven geconffronteerd met hett feit dat zij aan kanker lijdt en met m de in nvasieve behande elingen ertegen.

KCE Report 176 6A


ONDERZ ZOEKSVRA AGEN Dit rapport onderzoekt volgend de vraag: moet men de georgan niseerde borstkankerscre eening uitbreiden tot de groep vrou uwen van 70 tot 74 4 jaar? Als het antwoord op deze vraag negatief is, stelt zich nog een bijk komende vraag: welk antwoord a moet men geven aa an een vrouw uit die leeftijdscategorrie die om een scrreening vraagt?

METHOD DOLOGIE Het onderzoek van de klinische voordelen van sc creening is gebas seerd op een literatuurov verzicht uitgevoerrd in OVID Medline, EMBASE, CDSR en DARE. In dit ov verzicht werden arrtikels opgenomen n die in het Engels, Duits, Nederlands en Frans werden g gepubliceerd van naf januari 2004 tot april 2011. De evaluatie van v de risico’s/b baten-verhouding van deze scree ening is gebaseerd op een overzicht va an modelleringso onderzoeken uit Medline, M Embase, NHS EED en Econlit. In dit overzicht we erden artikels opg genomen die werden gep publiceerd in het Engels, Duits, Ne ederlands en Fran ns vanaf januari 2000 tott september 2011. Om de risico’s//baten-verhouding g in de Belgische context te kwanttificeren, werd een spec cifiek model uitge ewerkt. Voor het opbouwen o van dit model werd in Medline e, Embase, HTA EED en Psycinfo o (1950-10/2011) gezocht naar onderzoe eken rond de levvenskwaliteit tijde ens en na scree ening en behandeling va an borstkanker. H Het model maakt maximaal m gebruik k van de beschikbare Be elgische gegevenss. Tenslotte werden op basis van het verkregen be ewijsmateriaal een aantal praktijkaanbeve elingen uitgewerkkt en aan externe experten voorge elegd. Er werd geen enke el belangenconflicct gemeld.

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RESULTAT R TEN VAN HET H LITER RATUURO ONDERZO EK M Mortaliteit De beschikbare gerandomiseerde D e en gecontrolee erde studies brachten v volgende feiten aa an het licht: •

Screening gaa at gepaard met ee en daling van de mortaliteit van 23 3% op een follow-up--periode van 13 ja aar bij vrouwen bo oven de 50 jaar die om de twee jaar een e screening ond dergingen.

•

De daling van n de sterfte komt tussen de 4 en 7 jaar na de screening tot uiting. Dez ze gegevens zijn n te bekijken in h het perspectief va an de gemiddelde le evensverwachting g in deze leeftijdscategorie, nl. 16 6 jaar op 70 jaar en 13 jaar op 74 jaar (Belgische gege evens voor 2009). B de interpretattie van deze bu Bij uitenlandse studie es moet men er wel re ekening mee hou uden dat in de lee eftijdsgroep van 70 0 tot 74 jaar het aantal a v vrouwen dat aan de studies deelne eemt niet erg hoo og is; het effect op o de m mortaliteit kon voo or hen niet statistis sch worden aange etoond.

M Morbiditeit Naast het aantal gewonnen N g levens sjaren is het voorrnaamste voordee el dat m men van screeniing verwacht de e mogelijkheid om minder agres ssieve b behandelingen te kunnen instellen, aangezien scree ening tot doel hee eft om tu umoren aan hett licht te brenge en wanneer ze nog kleiner zijn n. De B Belgische gegeven ns waarover wij momenteel m beschikken laten ons nie et toe o deze bewering om g te valideren. De e meest recente gegevens (KCE-ra apport 150) maken gewa ag van 58% bors stsparende chirurg gie versus 38% totale m mastectomieën in de minder gevorrderde stadia (Sta adia I en II). Bijna a 90% v de vrouwen die van d een borstsparrende ingreep ond dergingen, kregen n ook ra adiotherapie, 38% % van hen kregen n neo-adjuvante cchemotherapie en n 41% e hormonale be een ehandeling. A Anderzijds gaven de gerandomisee erde gecontroleerrde onderzoeken geen u uitsluitsel over he et percentage re ecidieven, noch o over de evolutie naar m metastatische stad dia van de ziekte. Op deze basis kan de hypothese e van e een daling van de d morbiditeit noch worden ontkrracht, noch bevestigd.

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Daarentegen werd w het verlies va an levenskwaliteit bij een gemetasttaseerde kanker wel in he et model opgenom men (zie hieronde er).

MODELLERING De voornaams ste modelleringso onderzoeken we erden uitgevoerd in het CISNET-project (Cancer Interve ention and Surveillane Modeling Network). N Het doel van deze modellen wa as het evalueren van v het relatieve aandeel van screening door mammograffie resp. van adju uvante behandelin ng in de daling van de mortaliteit door borstkanker vasttgesteld in de Ve erenigde Staten van 197 74 tot 2000. Ze m maakten gebruik van gegevens affkomstig van het Breast Cancer Screening g Consortium. De resultaten van v deze modellen n wijzen op een winst w gaande van 9 tot 22 levensjaren pe er 1000 gescree ende vrouwen. In het wetensch happelijk rapport worden ook andere mod dellen beschreven n die geen gebruik k maken van de CISNET T-methodologie. Deze modellen zijn niet zonder m meer aanpasbaar aan de Belgische e situatie aangezien het invoegen van Be elgische gegeven ns onmogelijk is. Daarom werd een nieuw w, specifiek modell ontwikkeld.

EEN COH HORTMOD DEL VOOR BELGIE Methodologie e Het model dat voor dit rapport werd ontworpen, is een cohortmo odel dat evolueert via ja aarcycli. In dit mod del worden twee theoretische t coho orten van vrouwen ouder dan 70 jaar met elkaar vergeleke en. Eén cohort krijgt geen uitnodiging voo or een screening g (huidige situatie), in de andere e cohort worden vrouwe en verder uitgeno odigd om deel te e nemen aan sc creening. Voor het deelnemingspercentag ge en de verdeling van de door sc creening opgespoorde kankers k versus de intervalkankers s worden dezelfde cijfers als in de leeftijd dsgroep van 50-69 9 jaar genomen. De bedoeling van v screening is tumoren in een vrroeg stadium (I en n II) aan het licht te bren ngen teneinde ee en evolutie te voo orkomen naar sta adium IV (metastatisch stadium) s dat onge eneeslijk is. Deze ‘stage shift’ houd dt in dat bij de opgespoo orde kankers het aantal vroege sta adia (I, II) toeneem mt terwijl tegelijkertijd hett aantal gevorderd de stadia (II en IV V) vermindert.

KCE Report 176A 1

Verder hebben we V w de hypothes se vooropgesteld d dat overleving g en le evenskwaliteit afhangen van de leeftijd van de patiënte en van n het tu umorstadium. De eze hypothese ho oudt geen rekenin ng met het feit dat de p prognose van de door screening opgespoorde kan nkers beter is da an die v van klinisch opg gespoorde kanke ers (intervalkankkers en kankers s die o optreden bij vrouw wen die niet aan sc creening deelnem men).

P Parameters Dit model maaktt maximaal gebrruik van Belgiscche gegevens, nl. D n de g gemiddelde leven nsverwachting va an de vrouwen volgens hun le eeftijd (2 2009), de gegevens van hett kankerregister (voor de Vlaamse G Gemeenschap), d gegevens afkomstig van hett huidige screen de ningsp programma (50-69 9 jaar), de tijd no odig voor het ontkkrachten van een valsp positief resultaat (IMA/AIM) ( en de gegevens g over ovverleving na vijf ja aar in fu unctie van het sttadium (kankerregister). De gegevvens van de Vlaamse G Gemeenschap w werden gebruikt omdat ze vollediger zijn en omdat o o opportunistische s screening na 70 jaar j er minder va aak gebeurt dan in de re est van het land d. Hoeveel vroeg ger de diagnose wordt gesteld en het p percentage overdiagnose werd den bepaald o op basis van de literatuuranalyse.

M Meting van de levenskwaliteit l t De gegevens overr de levenskwalite D eit tijdens screenin ng en behandeling zijn a afkomstig uit de literatuur. Voor het beschrijven van de g gezondheidstoesta and werd het EQ-5D (Europea an Quality of Life-5 D Dimensions) ins strument gebru uikt; deze beschrijvingen we erden g gevaloriseerd doo or de algemene engelse bevolkiing ("UK tariffs")). We k konden niet over gegevens besch hikken met betrekkking tot de Belg gische b bevolking. D veranderingen in levenskwaliteiit van vrouwen ou De uder dan 70 jaar die in d modellen werde de en gebruikt, zijn de d volgende: •

Het verlies aa an levenskwaliteit na een vals-posittief screeningsresultaat wordt geraam md op 16%, gedure ende 45 dagen.

KCE Report 176 6A


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Voor de kankerpatiënten k e en tijdens het ee erste jaar volgend d op de diagnose (ongeacht het tyype behandeling) wordt het verllies aan levenskwaliteit geraamd op 16% voor de stad dia I,II,III en op 18% voor de stadia IV. Tijdens de volgende jaren wordt het verlies aan levenskwaliteit geraamd op 6% voor de stad dia I,II,III. Dit verrlies blijft stationair (18%) voor de stad dia IV. Omdat aan de eze benadering vverschillende bepe erkingen verbond den zijn, moeten deze cijfers met de nodig ge omzichtigheid worden geïnterpreteerd.

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Het optimistisch scenario gaat uit van een hypothese mett 3% H o overdiagnose en n 2% vals-posiitieven, waardoo or een verlies van le evenskwaliteit oprtreedt van 0,13 gedurende g 36 da agen. Dit scenario o past o de gescreende op e groep de verdeling per stadia toe e die momenteel wordt w v vastgesteld in hett kader van de in n Nederland georganiseerde screening (70-74 jaar). Ditt optimistisch scenario raamt e een winst van 17,0 le evensjaren en ee en winst van 16,3 3 QALY’s per 100 00 vrouwen die aa an de s screening deelnam men. Dit betekentt dat het nodig is om gedurende vijjf jaar 6 vrouwen voor een 67 e screening uit te t nodigen om éé én QALY te winnen.

Resultaten Het basisscena ario toont dat scre eening tussen 70 en 74 jaar 1,3 ov verlijden zou kunnen vo oorkomen per 10 000 deelnemende e vrouwen, hetge een een daling van de sterfte met 21% % vertegenwoord digt. Het globaa al aantal gewonnen levensjaren wordt gerraamd op 13,1 en n de winst aan QA ALY’s op 3,9. Omdat er veell onzekerheid is met betrekking tot t deze raminge en (voor details, zie de bespreking in h het wetenschapp pelijk rapport), werd een sensitiviteitsana alyse op het mod del uitgevoerd. Deze D analyse om mvat een pessimistisch scenario en een op ptimistisch scenarrio. Het pessimistisch scenario gaat uit van een hypothese met 20% overdiagnose en 10% vals-p positieven, waarrdoor een verlies van levenskwaliteit optreedt van 0,19 dat gedurende e 54 dagen aanho oudt (de tijd nodig om de d resultaten te ontkrachten). Voor de gescreend de groep werd de verdeling van de opge espoorde kankers s per stadia gebruikt die momenteel wo ordt vastgesteld in het kader van de georgan niseerde screening (50-6 69 jaar) in Vlaanderen. Dit pessimis stisch scenario ra aamt een winst van 8,7 levensjaren, maa ar een verlies va an 3,1 QALY’s per p 1000 vrouwen die aa an de screening deelnamen. Dit betekent b dat in bepaalde b omstandighede en - en we blijven hierbij zeker realiistisch - de screen ning kan leiden tot een daling d van de levenskwaliteit.

C CONCLUS IE Het doel van het organiseren van H n screenings is het verbeteren van het w welzijn van de bevolking door voortijdige overliijdens te voorko omen. U Uiteraard zou het uitbreiden van de e screening naar de leeftijd van 74 4 jaar h het mogelijk ma aken om voor een e bepaald aa antal vrouwen enkele e le evensjaren te win nnen. De invloed d van georganise eerde screening op o de le evenskwaliteit is s echter veel onzekerder (erg g laag niveau van b bewijskracht, want gebaseerd op o een model)). Volgens bepaalde re ealistische hypothesen zou dez ze interventie ze elfs een verlies van le evenskwaliteit ku unnen veroorzake en. In deze omstandigheden zo ou de b balans tussen de vooren nadelen n van screening g globaal eerder ku unnen d doorslaan naar de e kant van een verrlies van welzijn van de bevolking. E wordt dus niet aanbevolen Er a om de georganiseerde e borstkankerscreening u te breiden tot de groep vrouwen van 70 tot 74 jaarr. uit

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AANB BEVELIN NGENa

a

KCE Report 176A 1

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Het sy ystematisch uitn nodigen van vro ouwen tussen 70 0 en 74 jaar om m deel te nemen n aan georganiseerde borstk kankerscreening g wordt niet aanb bevolen.

•

Als ee en vrouw boven n de 70 jaar vrraagt om een mammografie m in n het kader van n een screen ning zal de arts erover e waken da at de vrouw goed d op de hoogte w wordt gebracht va an de voordelen en mogelijk ke nadelen die de eze screening me et zich mee kan brengen.

•

Elke screeningsmamm s mografie moet beantwoorden aa an de Europese v vereisten op hett vlak van kw waliteit, met nam me: de controle en e kwaliteit van de installaties, d de dubbele lezing, de registratie en de optim malisering van he et recall-percenta age. Daarom zal de arts de vrouw w die om een e screening vraagt, doorrverwijzen naarr een structu uur die aan deze kwaliteitsvereisten bea antwoordt.

•

Om he et risico op een verlies aan leve enskwaliteit te wijten w aan vals po ositieve resultatten te minim maliseren is het belangrijk dat de d proportie vrouwen die terugg geroepen wordt voor verderr onderzoek zo la aag mogelijk is en e onder de Euro opese vereisten blijft (<5%).

Het KCE blijft b als enige veran ntwoordelijk voor de e aanbevelingen die e aan de overheid worden w geformuleerd d.

KCE Report 176 6

S Screening Breast Cancer C

1

TABL LE OF CO ONTENT TS LIST OF FIGURES S ................................................................................................................................................. 4 LIST OF TABLES ................................................................................................................................................... 4 LIST OF ABBREVIIATIONS ................................................................................................................................... 5 1. 2. 3.

SYNTHES SE .............................................................................................................................................. 7 CONTEXT T................................................................................................................................................. 7 ONDERZO OEKSVRAGEN ......................................................................................................................... 7 BESCHRIJVING VAN DE PROBLEMATIEK P K ......................................................................................... 8

3.1.

INTUÏTIEV VE BENADERING G .................................................................................................................... 8

3.2.

EPIDEMIO OLOGISCHE BEN NADERING.................................................................................................... 8 3.2.1. Doel D op korte term mijn ................................................................................................................. 9 3.2.2. Uiteindelijk U doel .......................................................................................................................... 9 3.2.3. Vals-positieven V en overtollige diagnosen .................................................................................. 9 METHODO OLOGIE .................................................................................................................................. 11

4. 4.1.

RAMING VAN V DE VOORDE ELEN VAN SCRE EENING ........................................................................... 11 4.1.1. Daling D van de morrtaliteit .......................................................................................................... 11 4.1.2. Verbetering V van de e levenskwaliteit van v patiënten ................................................................... 11

4.2.

RAMING VAN V DE NADELE EN VAN SCREENING ................................................................................. 12 4.2.1. Vermindering V van de levenskwaliteitt van patiënten ................................................................ 12

4.3.

BENADER RING DOOR MOD DELLISERING ............................................................................................ 12 4.3.1. Meting M van de leve enskwaliteit ................................................................................................. 12 4.3.2. Beschrijving B van het product ................................................................................................... 13 4.3.3. Basishypothesen B ...................................................................................................................... 15 4.3.4. Gegevensinvoer G vo oor het model ............................................................................................. 15 4.3.5. Sensitiviteitsanalys S se ................................................................................................................ 15 RESULTA ATEN........................................................................................................................................ 16 BESPREK KING ........................................................................................................................................ 16

5. 6.

2


KCE Reportt 176

6.1.

LEVENSJA AREN TOEVOEG GEN? ........................................................................................................... 16

6.2.

7.

TOEVOEG GEN VAN LEVEN NSKWALITEIT AA AN LEVENSJAREN? ...................................................... 17 6.2.1. Minder M agressieve e behandelingen? ........................................................................................ 17 6.2.2. Vals-positieven V ......................................................................................................................... 17 6.2.3. Overtollige O diagnos ses en behandelin ngen ................................................................................ 17 CONCLUS SIES ........................................................................................................................................ 17

7.1.

MOET ME EN DE SCREENIN NG UITBREIDEN TOT DE LEEFTIJ JD VAN 74 JAAR R? ............................. 17

7.2.

WAT MOE ET MEN ZEGGEN N TEGEN EEN PE ERSOON DIE OM M SCREENING VR RAAGT?.................. 18

7.3. 8.

KERNBOO ODSCHAPPEN ....................................................................................................................... 18 REFEREN NTIES....................................................................................................................................... 19

1.

SCIENTIF FIC REPORT ............................................................................................................................ 20 INTRODUCTION .................................................................................................................................... 20

1.1.

CONTEXT T OF THIS REPORT .............................................................................................................. 20

1.2.

SCOPE OF O THIS REPORT T ................................................................................................................... 20

1.3.

BREAST CANCER C SCREE ENING IN BELGIU UM.................................................................................... 20

1.4.

CLINICAL QUESTIONS ......................................................................................................................... 21

1.5. 2.

SCIENTIF FIC APPROACH ...................................................................................................................... 21 LITERATU URE REVIEWS ....................................................................................................................... 22

2.1.

REVIEW OF O CLINICAL STU UDIES......................................................................................................... 22 2.1.1. Methodology M ............................................................................................................................. 22 2.1.2. Description D of scre eening benefit .............................................................................................. 23 2.1.3. Description D of scre eening harms............................................................................................... 26 2.1.4. Screening S conditio ons ............................................................................................................... 28 2.1.5. Key K data ................................................................................................................................... 29 2.1.6. Conclusion C ................................................................................................................................ 30

2.2.

REVIEW OF O MODELING STUDIES S ...................................................................................................... 30 2.2.1. Literature L search strategy s ....................................................................................................... 30 2.2.2. Selection S criteria ....................................................................................................................... 30

KCE Report 176 6


2.2.3. 2.2.4. 2.2.5. 2.3.

3

Quantity of researc Q ch available ................................................................................................. 31 S Selected studies ....................................................................................................................... 31 C Conclusion ................................................................................................................................ 34

3.

REVIEW OF O QUALITY OF LIFE STUDIES ........................................................................................... 34 2.3.1. Methods M .................................................................................................................................... 35 2.3.2. Results R ..................................................................................................................................... 36 2.3.3. Discussion D ................................................................................................................................ 44 DECISION N ANALYSIS ........................................................................................................................... 44

3.1.

DATA SOU URCES ................................................................................................................................... 45

3.2.

MODEL DESCRIPTION D ......................................................................................................................... 45

3.3.

DESCRIPT TION OF THE PA ARAMETERS .............................................................................................. 49 3.3.1. Age A specific overa all survival .................................................................................................... 49 3.3.2. Breast B cancer incid dence .......................................................................................................... 49 3.3.3. Participation P rate ...................................................................................................................... 49 3.3.4. Proportion P of scree en detected breas st cancers ........................................................................ 49 3.3.5. Recall R rate ................................................................................................................................ 49 3.3.6. Stage S distribution and a stage shift ............................................................................................ 50 3.3.7. Stage S specific rela ative survival ................................................................................................ 51 3.3.8. QALY Q ........................................................................................................................................ 52

3.4.

RESULTS S ............................................................................................................................................... 55

3.5. 4.

DISCUSSION ......................................................................................................................................... 59 ANSWER TO CLINICAL QUESTIONS Q ................................................................................................. 61

4.1.

BREAST CANCER C RELATE ED MORTALITY ......................................................................................... 61

4.2.

DELAY BE ETWEEN THE SC CREENING AND THE T MORTALITY Y REDUCTION ................................... 61

4.3.

OVERALL L MORTALITY ......................................................................................................................... 61

4.4.

MORBIDIT TY ............................................................................................................................................ 61

4.5.

FALSE PO OSITIVE OR FALS SE NEGATIVE RESULTS .......................................................................... 61

4.6.

ADDITION NAL DIAGNOSTIC C TESTS ..................................................................................................... 61

4.7.

OVER-DIA AGNOSIS AND OVER-TREATMEN O NT .................................................................................... 61

4


4.8. 5.

LIST OF FIGURES F

LIST OF TABLES T

KCE Reportt 176

WHAT AT TTITUDE SHOULD D BE RECOMMENDED FOR WOM MEN IN CASE OF F SELF REFERRA AL?62 REFEREN NCES ....................................................................................................................................... 63

s for which uttilities are needed d (reflection process) ...................................................... 37 Figure 2.1: Health states Figure 2.2: Percenttage change in utilities ............................................................................................................ 43 Figure 3.1: Comparrison of the two co ohorts with and without a screening g program............................................ 47 Figure 3.2: Comparrtments in the two o cohorts and the transitions t betwee en them .............................................. 48

Ta able 2.1: Data issu ued from clinical literature review .......................................................................................... 29 Ta able 2.2: Selection n criteria .................................................................................................................................. 31 Ta able 2.3: Modeling g studies excluded d after full-text ass sessment ........................................................................ 31 Ta able 2.4: results of the different models m in terms of o mortality reduc ction and years o of life gained perr 1000 wo omen screened fo or the different mo odels ............................................................................................................ 33 Ta able 2.5: Article se election criteria ........................................................................................................................ 35 Ta able 2.6: Health sttates descriptions s for the study of Lidgren L et al. .................................................................... 39 Ta able 2.7: Description of a “false pos sitive” state (Gerard et al)83......................................................................... 40 Ta able 2.8: Description of the selected d utilities ..................................................................................................... 41 Ta able 3.1: Stage diistribution among screen detected breast cancers, interval cancers a and cancers amon ng non pa articipants, age 50 0-69, Flemish scre eening program 2001-2006. ....................................................................... 50 Ta able 3.2: Parametters used in the model m ............................................................................................................ 53 Ta able 3.3 Modeling results: baseline, worst and best case c scenario. ................................................................. 56 Ta able 3.4 Modeling results: sensitivitty analysis. .................................................................................................. 57

KCE Report 176 6

LIST OF ABBREVIA A ATIONS


AB BBREVIATION

DEFINITION

CP PG CC CRT CII DC CIS DE ET BC CSC AH HRQ BC CR DN NETB CIISNET IM MA/AIM IN NAMI/RIZIV IC CER KC CE MST M-A NIIS NB BSS NB BCSP NH HS NH HS EED NC CI QA ALY Qo oL RC CT RR R

Clinical Practic ce Guideline Cochrane Cen ntral Register of Controlled C Trials Confidence Intterval Ductal Carcino oma in situ Data Extractio on Table Breast Cancerr Surveillance Con nsortium (USA) Agency for He ealth Care Researrch and Quality Belgian Cance er Registry Dutch Nationa al Evaluation Team m for Breast cance er screening Cancer Interve ention and Surveillance Modelling Network N Intermutualistic Agency National Institu ute for Health and d Disability Insuran nce Incremental co ost-effectiveness ratio r Belgian Health hcare Knowledge Centre Mean Sojourn Time Meta-analysis National Institu ute for Statistics Canadian Natiional Breast Canc cer Screening Study Norwegian Bre east Cancer Scree ening Programme es National Healtth Service (UK) NHS Economic Evaluation Data abase National Canc cer Institute (USA)) Quality Adjuste ed Life Year Quality of Life Randomized Controlled C Trial Relative Risk

5

6


SE EER SR R ST T TT TO UK K US SA US SPSTF

Surveillance, Epidemiology E and d End Results (US SA) Systematic Re eview Sojourn Time Time-trade-offf United Kingdo om Unites States of America US Preventive e Services Task Force

KCE Reportt 176

KCE Report 176 6

SYNT THESE

Screening Breast Cancer C

7

1 CONTEX 1. XT Het KCE publiceerde al drie rapporten over borsskankerscreening. Het H b basisrapport, gepubliceerd in 2005 (KCE-rapp port nr. 11) betrof b b borstkankerscreen ning in het algemeen, in de bevolking zo onder risicofactoren. Borrstkankerscreenin ng bij vrouwen in de leeftijdsklasse e van 4 40-49 jaar was het onderwerp p van een ge edeeltelijke bijwe erking g gepubliceerd in 20 010. In dit rapporrt (KCE-rapport nr. 129) beval het KCE g geen systematische screening aan n bij vrouwen jon nger dan 50 jaarr. Het d derde rapport (KC CE-rapport nr. 172), gepubliceerd d in 2012, stelde e het p probleem van de e opsporing van vrouwen die ee en verhoogd risic co op b borstkanker hebb ben. In dit rap pport wordt ond derzocht of men n de g georganiseerde borstkankerscreening moet uitbreid den naar vrouwen n van 7 tot 74 jaar. 70 D Deze vraag wordtt vaak gesteld aan n politici omwille van de stijging va an de le evensverwachting g van de vrouw welijke bevolking.. Hoewel de meeste g groepen die actie ef zijn bij screen ning deze uitbre eiding vragen, zijjn de o openbare instantie es hierover minde er unaniem. Slechts vier lidstaten va an de E Europese Unie ric chten zich op de leeftijdsgroep van n 70-74 jaar (Fran nkrijk, N Nederland, Spanje e en Zweden)1. De D andere landen n benadrukken da at het n noodzakelijk is om m de vrouwen te informeren en de beslissing samen n met h te nemen. hen

2 ONDERZ 2. ZOEKSVR RAGEN Moet de georganiseerde borstkankerscreening worrden uitgebreid tot de M le eeftijd van 74 jaar? Als het antwoo ord op deze vraag g negatief is, wat moet m dan zeggen tegen men t een persoon n die om deze scrreening vraagt? D eerste vraag heeft meer specifie De ek betrekking op d de openbare insta anties e de tweede op de en d zorgverleners.

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KCE Reportt 176

3. BESCH HRIJVING VAN DE PROBLEMATIEK K

een kanker (vals-n e negatief) dan voorr de risico's die sa amenhangen mett valsp positieve resultate en.

3.1. Intuïtiev ve benadering

Borstkanker is de B e meest voorkom mende kanker bijj de vrouw. In België B w werden 10.849 ge evallen van borstk kanker gediagnossticeerd in 2008. Meer d drie vierde va dan an de borstkankerrs wordt gediagno osticeerd na de le eeftijd v van 50 jaar. Het gemiddelde oge enblik van de dia agnose is 62 jaar. De in ncidentie van borrstkanker is 370,7 7/100.000 in de g groep vrouwen va an 70 to ot 75 jaar6. N Nochtans verschilt het relatieve aa andeel van morta aliteit veroorzaakt door b borstkanker in hett totale percentage mortaliteit in fun nctie van de leeftijd. In 1999 was borstka anker verantwoorrdelijk voor 18% van de overlijden ns bij v vrouwen van 50 to ot 54 jaar, 13% in de groep van 60 tot 64 jaar en 6% in de g groep van 70 to ot 74 jaar (KCE E-rapport nr.11). In 2006 bedroe eg dit p percentage 14% voor v vrouwen van n 50 tot 54 jaar, 12% voor de groep p van 6 tot 64 jaar, 7% 60 % voor de groep van v 70 tot 74 jaarr en 5% voor de groep g v 75 tot 79 jaar6. van

Op intuïtief vla ak heeft borstkankerscreening ze eker zin. De me edia zijn meestal erg en nthousiast over sccreening. Deze houding werd aan ngetoond door Schwartz begin 21ste eeuw2. Een enquête uitgevoerd in de Ve erenigde an de volwassenen van oordeel was dat Staten toonde aan dat 87% va e ondervraagde personen p screening een goed idee is. Drrie vierde van de h opsporen van kanker in een vro oeg stadium in de e meeste verklaarde dat het gevallen levens s redt. Het enthousiasme van de re espondenten was zo groot dat voor de me eesten van hen sscreening geen te t nemen besliss sen was, maar een more ele verplichting3. Deze algemen ne houding die e we als volgt kunnen same envatten "vroegtijdige op psporing van kankkers kan levens re edden", kan onrea alistische verwachtingen wekken bij vrou uwen. Silverman realiseerde teleffonische t evalueren hoe vrouwen borstkanker en het voord deel van interviews om te screening via mammografie m zien n. De meeste res spondenten besch houwden borstkanker als s een uniform prrogressieve ziektte en geloofden dat alle 4 kankers beginn nen met een gene eesbare en stille vorm v . Samengev vat, deze vrouwen waren n van oordeel dat indien borstkank ker niet wordt opg gespoord door een mam mmografie en vroe egtijdig behandeld d, de kanker gro oeit, zich vermeerdert en n doodt. Omwille vvan deze opvattingen, gaan vrouwe en ervan uit dat gevorde erde kankers (en zonder enige tw wijfel de meeste dodelijke d kankers) samen nhangen met het falen van vroegtijdige opsporing. Schwartz bekle emtoonde dat 94% % van de vrouwen n niet weten dat sc creening kankers kan op psporen die zich n nooit zullen ontwik kkelen. Bovendien n is 92% van de respon ndenten ervan ovvertuigd dat mam mmografie ongeva aarlijk is voor een persoo on die geen borsttkanker heeft5. Het medisch ko orps zelf begrijpt de screening nie et altijd op een adequate a manier. Daard door blijven talrrijke clinici zich h concentreren op het percentage ge ediagnosticeerde kankers (tussentijds doel), terrwijl het uiteindelijke do oel van de opsporing het verlage en van de morta aliteit is. Anderzijds lijke en clinici gevoeliger voor het risico o van het miskennen van

3 3.2. Epidemiollogische benad dering

E Essentiële kenmerrken van screenin ng: 1.

Screening is s bedoeld voor personen in g goede gezondheid In tegenstelling g tot een patiëntt die zijn arts raa adpleegt omwille e van een klacht of o een symptoo om, wordt ervan n uitgegaan datt een persoon die deelneemt aan een e screening n niet lijdt aan de ziekte z die wordt op pgespoord.

2 2.

Screening he eeft als doel om op o korte termijn d de afwezigheid va an de ziekte te beve estigen.

3 3.

Screening he eeft als uiteinde elijk doel de mo ortaliteit/morbiditeiit die samenhangt met m de ziekte te verminderen. v

4 4.

Het principe “primum “ non noce ere” (in ieder geva al geen kwaad doen) is vooral van toe epassing op scree ening.

Wij wensen eraan te herinneren dat op duizend gescreende vro W ouwen tu ussen 70 en 74 ja aar, meer dan 990 0 geen borstkanke er hebben.

KCE Report 176 6


9

3.2.1. Doel op o korte termijn

3 3.2.3. Vals-posiitieven en overto ollige diagnosen n

Screening heefft als doel om de afwezigheid van n de ziekte te bev vestigen. De persoon die e aan screening d deelneemt, geniet van "het vermoe eden van onschuld" wat betreft borstkankker. Daarentegen wordt de patiëntt die zijn acht heeft of omda at hij iets ongewo oon heeft arts raadpleegt omdat hij een kla e. Het doel van de e arts en de midd delen die opgemerkt, "verdacht" van ziekte n deze twee situaties diametraal te egenover hiertoe worden gebruikt, staan in g van het scherpstellen van ee en diagnose heeftt de arts elkaar. In het geval de plicht om allle middelen in te zetten om een ettiologie te vinden voor de klacht of het sy ymptoom. In het g geval van screening daarentegen, heeft de arts de plicht om o alleen de ono ontbeerlijke onderz zoeken uit te voe eren. De bedoeling hierv van is om de risico o's en ongemakke en van screening voor de vrouwen die ge een borstkanker he ebben zo gering mogelijk m te houden. Omdat de ople eiding van artsen voornamelijk gebeurt g in hospittalen bij zieken gaat dez ze verandering va an gezichtspunt vo olledig in tegen de e intuïtie van een clinicus s.

Vooraleer een geo V organiseerde scre eening in te voeren n, is het nodig er zeker v van te zijn dat de e verhouding voo ordelen/nadelen vvan screening ove erhelt n naar de kant van de voordelen. Om O dit te doen moet de grootte va an de d daling van de mortaliteit m het verrlies aan levenskkwaliteit compens seren v veroorzaakt door ongemakken o en riisico's van de scre eening. D zogenaamd "v De vals-positieve" res sultaten (vermoed den van kankerla aesies z zonder de aanwezigheid van ka anker) zijn de o ongewenste nega atieve g gevolgen van bors stkankerscreening g die het vaakst vvoorkomen. Deze valsp positieve resultate en zorgen voor heel veel angst en het uitvoeren n van b bijkomende onderz zoeken. M Meer nog dan de d vals-positieve e resultaten is vvooral het risico o van o overtollige diagnos se het grootste riisico van screenin ng bij vrouwen va an 70 to ot 74 jaar. Ove ertollige diagnos se kan worden gedefinieerd als s het d diagnosticeren van n kanker waarvan n de evolutie zoda anig is dat ze zich nooit k klinisch zou man nifesteren wanne eer er geen sccreening zou he ebben 8 p plaatsgevonden . Dit risico is des te groter naarmate de kanker slechts trraag evolueert en n de levensverwac chting van de perssoon laag is. Vooral dit risico is weinig bekend b bij de be evolking. Zeer w weinig vrouwen weten w nderdaad dat so ommige kankers zo langzaam evvolueren dat, zelfs al in w worden ze niet behandeld, ze geen g invloed zo ouden hebben op o de 9 g gezondheid . D rapport heeft tot Dit t doel om de vo oor- en nadelen tte bepalen (zie Fig. F 1) v deze screenin van ng om ze in persp pectief te kunnen plaatsen en ervo oor te z zorgen dat de voo ordelen grotendee els opwegen tegen het risico van verlies v v levenskwaliteiit. van

3.2.2. Uiteind delijk doel Diagnosticeren van kanker in ee en vroeg stadium m vooraleer de zie ekte zich en en uitzaaien (metastasen) is s het basisprincipe van kan ontwikkele borstkankerscre eening. Daarom vverwacht men da at screening de mortaliteit m die specifiek ge ekoppeld is aan de ziekte zal verm minderen, en bijgev volg ook de totale mortaliteit. Het feit dat d de gebruikte technologie toelaat om m weinig n dus mogelijk no og geneesbare la aesies te diagnos sticeren, gevorderde, en vormt een tusse enstap in dit procces. Het betreft hier dus een noodz zakelijke voorwaarde die e echter onvoldoen nde is7. Men kan ook de d hypothese vooropstellen dat scrreening de morbid diteit die gepaard gaat met m de ziekte ve ermindert, doorda at het mogelijk wordt w om minder invasiev ve behandelingen n te gebruiken (g gedeeltelijke masttectomie in plaats van totale mastectom mie) en doordat men een deel van de asen kan voorkom men. progressie naarr metastatische fa

10


KCE Reportt 176

Figuur 1 - mog gelijke vooren d de nadelen van screening. s

Vals negatieef

Onnterecht gerustgesteld

Diagnose laattijdiger

Normaal Resultaat -

Geruustgesteld

Vals positieef

Bijko omende onderzoeeken

Opsporiing door mamm mografie

Abnormaal Resultaat +

Invasieef carcinnoma

In situ s carcinoma

Vroegtijdige V b behandeling

Vrroegtijdige beehandeling

Verminderdee mortaliteit

Overbehandeling

KCE Report 176 6


4. METHODOLOGIE We hebben elementen voor e een antwoord op p voorgenoemde vragen k literatuurr, in modelleringss studies en in natio onale en gezocht in de klinische internationale gegevens. g Dit opzzoekingswerk werd uitgevoerd volgens de bij het KCE gelldende procedure es. Ze worden gedetailleerd beschreven in hoofdstuk 2 van n het wetenschappelijk rapport.

4.1. Raming g van de voordelen van scree ening 4.1.1. Daling g van de mortalite eit De meest bewijskrachtige e gegevens met betrekkin ng tot eening komen u uit acht gerandom miseerde geconttroleerde borstkankerscre studies. Op bas sis van deze studies kunnen twee belangrijke vaststtellingen worden gedaan n: 1. Screening zorgt voor een daling van de morrtaliteit met 23% over o een speriode van 13 jjaar voor vrouwe en ouder dan 50 jaar die opvolgings elke twee jaar een screening g ondergingen. 2. Deze dalin ng van de mortaliiteit komt 4 tot 7 jaar na de scree ening tot uiting. Dit moet in perspecttief geplaatst worrden ten opzichte e van de wachting van de doelpopula atie. De gem middelde levensverw levensverw wachting in deze leeftijdscategorie e is 16 jaar op 70 0 jaar en 13 jaar op 74 jaar (Belgische e gegevens voor 2009). 2 De bewijskrach htige gegevens va an deze gerando omiseerde geconttroleerde studies kunnen n geen antwoord geven op onze basisvraag. Slec chts één enkele gerando omiseerde studie, de Zweedse "Tw wo County"-studie,, bevatte ook vrouwen in de leeftijdscate egorie van 70 to ot 74 jaar en he et aantal udie deelnam was s te laag (10.000 voor de zeventigjarigen dat aan deze stu twee groepen) om een statistissch significant efffect op de mortaliteit te onen. Bovendien n werd deze studie gehinderrd door kunnen aanto methodologisch he bias.

11

4 4.1.2. Verbeteriing van de leven nskwaliteit van p patiënten Hoewel screening H g als doel heeft klleine tumoren aan te tonen, is een n van d verwachte vo de oordelen dat hett zal toelaten om m minder agres ssieve b behandelingen t te gebruiken. Noch de gege evens afkomstig g uit g gerandomiseerde evens gecontroleerde studies, noch feitelijke gege v verzameld in België laten toe om de eze verwachtingen n te bevestigen. G Gerandomiseerde gecontroleerde e onderzoeken hebben noch het p percentage recidie even, noch de evo olutie naar metasstatische stadia va an de z ziekte gekwantificeerd. Op deze basis kan de hypo othese van een daling d v van de morbiditteit dus noch worden ontkraccht, noch bevestigd. D Daarentegen werd d een verlies van levenskwaliteit d door metastasen wel w in h hieronder besc het chreven model op pgenomen. D Belgische gege De evens waarover wij w momenteel besschikken laten ons niet to oe om deze bew wering te validere en. De meest reccente gegevens (KCE( ra apport 150) make en gewag van 58 8% conservatieve e chirurgie versus s 38% to otale mastectomie eën in de minder gevorderde stadia (Stadia I en II). Bijna 9 90% van de vrrouwen die een n conservatieve chirurgische ing greep o ondergingen, kreg gen ook een behandeling met radiotherapie, 38% van n hen k kregen een neo-a adjuvante behand deling met chemo otherapie en 41% % een h hormonale behand deling.

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KCE Reportt 176

4.2. Raming g van de nadele en van screeniing

4 4.3. Benaderin ng door modellisering

4.2.1. Vermin ndering van de llevenskwaliteit van v patiënten

Met voornoemde literatuuronderzoe M eken konden we de verhouding tu ussen v vooren nadelen n niet afwegen en daarom hebb ben we hiervoorr een s specifiek model uitgewerkt. u Voor het uitwerken va an dit model was het n nodig studies te zo oeken met betrek kking tot de levensskwaliteit van vro ouwen tiijdens de screenin ng en de levenskw waliteit van patiën nten tijdens hun ziekte.

Screening vero oorzaakt een verm mindering van de e levenskwaliteit van v een deel van de gescreende perso onen. Dit kan worden verklaard door een reeks factoren: ositieve resultaten n van screening worden w door de patiënten p 1. De vals-po ervaren als s terecht-positieve e resultaten gezie en zolang de bijk komende onderzoeke en ze niet hebb ben kunnen ontkrrachten. Ze vero oorzaken ongerusthe eid met betrekkking tot borstka anker en de in nvasieve procedures s zoals puncties. 2. De overtolllige diagnoses e en behandelingen n die erop volgen (overdiagnose en overbehandeling (voor meer m details zie z het appelijk rapport), lleiden tot ernstige e ongerustheid en zware wetenscha behandelin ngen waaronder b borstamputaties die d geen invloed hebben op de overrleving van de perrsoon. 3. Een voortiijdige diagnose kkan leiden tot he et verlies van meerdere m levensjaren n in goede gezondheid. Screening heeft als doel om m kanker vroeger op p te sporen dan met een klinisch he diagnose. De patiënte wordt hierd door vroeger in haar leven ziek va an kanker. Wanne eer deze patiënte ov verlijdt aan een o oorzaak die niets te maken heeft met m haar kanker, du us voordat die kanker de kans kre eeg te evolueren,, zou ze enkele jaren te vroeg "aa an kanker gelede en hebben" terw wijl deze zins een invloed had op voortijdige diagnose en behandeling geensz sverwachting10. haar levens

4 4.3.1. Meting va an de levenskwa aliteit Er zijn verschillen E nde instrumenten n beschikbaar vo oor het meten va an de le evenskwaliteit. Be epaalde instrume enten zijn specifie ek aangepast aa an de z ziekte zoals bijjvoorbeeld de vragenlijst met betrekking tott de le evenskwaliteit van n patiënten die aan borstkanker lijjden van de Euro opean O Organization for Research and Treatment T of Ca ancer (EORTC). Deze h hulpmiddelen evallueren het beeld dat d de patiënte heeft van haar lich haam, h haar pyschologisc ch functioneren, de d angst voor hervallen... Het is echter e n niet mogelijk om m met deze mu ultidimensionele gezondheidsgege evens re ekening te houde en in een model. Ze moeten wo orden omgezet in n een g globale index vo oor levenskwalite eit, nl. de Quality-Adjusted Life-Year (QALY). De QA ALY's zijn het aantal levensjarren met een goede g evenskwaliteit. le D farmaco-econo De omische aanbeve elingen van het KCE gaan ervan uit u dat d vragenlijst EQ--5D een van de beste hulpmiddelen is die beschikba de aar is v voor het evaluerren van de QA ALY's. Met dit hulpmiddel word dt de le evenskwaliteit gekoppeld aan de gezondheidstoesta g and rekening hou udend m met vijf elemente en: mobiliteit, au utonomie van de e persoon, dage elijkse a activiteiten, pijn/hinder, angst/depre essie. Voor elk va an deze elementen zijn m meerdere antwoo orden mogelijk. Die D verwijzen na aar de ernst van n het p probleem (geen probleem, enkele problemen, matig ge problemen, ern nstige p problemen). Dez ze vragenlijst wordt w voorgelegd d aan de betro okken p populatie, dus voo or screening aan een e populatie van n vrouwen die nie et aan b borstkanker lijden, en voor de ziektte zelf aan een p populatie patiënten n met b borstkanker. Via het literatuurov verzicht konden drie studies wo orden o opgespoord die aan a onze inclusie ecriteria voldeden n. Op basis van deze s studies worden de e variaties in leve enskwaliteit bij ze eventigjarigen als volgt g geraamd:

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1.

Het verlies aan levenskw waliteit voortvloeie end uit een vals s-positief geraamd op 16% % tijdens de periiode die screeningrresultaat wordt g nodig is om m dit vals-positievve resultaat te ontkrachten. In Belg gië duurt die periode e gemiddeld 45 dagen (min. 36, max. 54 dagen) vollgens de gegevens van het Intermutu ualistisch Agensch hap (IMA). 2. Voor de kankerpatiënten, k e en tijdens het ee erste jaar volgend d op de diagnose (bij ( om het even w welke behandelin ng), wordt het verrlies aan levenskwaliteit geraamd op 16% voor de stad dia I,II,III en op 18% voor m IV. Tijdens de e volgende jaren n wordt het verllies aan de stadium levenskwaliteit geraamd op 6% voor de stad dia I,II,III. Dit verrlies blijft dium IV. stationair (18%) voor de stad eze benadering vverschillende bepe erkingen verbond den zijn, Omdat aan de moeten deze cijfers met de nodige omzichtigheid d worden geïnterp preteerd. e landen. De gebruikte g Het betreft hier resultaten uitt Angelsaksische E meet de e algemene gezon ndheidsdimensies s en niet vragenlijst, nl. EQS-5D, de dimensies die specifiek zijn n voor borstkanker. De maatrege elen met d patiënten houd den slechts in ge eringe mate reken ning met betrekking tot de de impact op korte termijn va an de diagnose en de chirurgie e. Deze d gebruikt tijdenss ambulante cons sultaties en de re esultaten vragenlijst werd ervan weerspiegelen dus niet de levenskwa aliteit van ernstig zieke z niet meer kun nnen verplaatsen. Het bijzondere karakter patiënten die zich van de gebruiktte studie zou de g geringe wijziging in levenskwaliteitt kunnen verklaren die werd w vastgesteld tussen patiënten n met borstkanke er en de algemene popu ulatie of tussen p patiënten met me etastasen en zij die d geen metastasen onttwikkelden.

4.3.2. Beschrrijving van het p product Het model bev vat twee theoretische cohorten. Deze D twee cohorrten zijn samengesteld uit u 100.000 vrouw wen waarvan de evolutie e wordt gev volgd tot aan hun overlijden. Hieronder vindt u het sch hema dat deze evolutie weergeeft.

13

14


(1) )Invasieve kaanker gevonden door screening Uitgenodigde Vrrouwen

Coh hort A

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I II III IV

(2) Interval kankker bij niet gescreendee vrouwen

I II III IV

(3) Invasieve kanker bij niet gescreeende vrouwen

I II III IV

(5) Overlijden (allle oorzaken)

(4) Ductal Carcinoma in Situ

Co ohort B

Niet uitgenodiggde vrouwen

(6) Invasieve kanker bij niet gescreeende vrouwen (7) Ductal Carccinoma in Situ

I II III IV (8) Overlijden (aalle oorzaken)

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Cohort A illu ustreert de hyp pothese van ee en uitbreiding van v de georganiseerde e screening tot 7 74 jaar. Het coh hort is samenges steld uit vrouwen die uitgenodigd u werd den om deel te nemen aan sc creening. Sommigen van hen namen deel (uitgenodigd/dee elnemer) en ande eren niet et-deelnemer). De e kankers die zich h voordeden in he et cohort (uitgenodigd/nie werden geïnv ventariseerd. He et betreft hier kankers die werden gediagnosticeerd tijdens de sscreening (1), of o kankers die werden enings (2), of kan nkers die gediagnosticeerd in het interval ttussen twee scree den/nietgediagnosticeerd werden in de groep van de uitgenodigd 3). De ductale carcinomen in situ tenslotte kunnen deelnemers (3 voorkomen in de d groep uitgenodigden/deelnemers net zoals bij de d groep van de uitgenodigden/niet-deeln nemers (4). De ov vergrote meerderh heid van d dit cohort u uitmaakten overlleden aan een andere de vrouwen die aandoening dan n borstkanker (5).. Cohort B (contrrole-cohort) komt overeen met de huidige h situatie. De D leden van dit cohortt werden niet uitgenodigd voor de screening. Sommige S vrouwen werde en getroffen door e een invasieve kan nker (6), andere door d een ductaal carcino oom in situ (7). De overgrote meerderheid van de vrouwen v die dit cohort uitmaakten overrleden aan een andere aandoen ning dan borstkanker (8). volueert in vier sttadia (I, II, III, IV). Stadium I is het minst Borstkanker ev gevorderde sta adium. Overlevin ng is per definittie minder goed en de behandeling is des te zwaarder en meer invasieff wanneer de kan nker zich vorderd stadium b bevindt op het mo oment van de diag gnose. in een meer gev

4.3.3. Basish hypothesen De basishypoth hese is de volgende: bij de kankers s die worden opg gespoord door screening, is het percentag ge weinig gevorde erde kankers (sta adia I en eerd wordt. Alle vo oordelen II) groter dan biij kanker die klinissch gediagnostice van screening komen voort uit d de verschillen tus ssen de verdeling g van de hift) volgend op de e screening. stadia (stage-sh De andere weerhouden w hyp pothese is dat de overleving en de levenskwaliteit van de vrouwen uitsluitend afhan nkelijk is van het stadium de vrouw op het ogenblik o van de diiagnose, van de tumor en de leeftijd van d of dit nu al dan niet volgt op een screening.

15

De cohorten we D erden jaar na jaar opgevolgd in functie van n de o overgangsparame eters zoals het aan ntal vrouwen dat e elk jaar getroffen wordt w (incidentie) en het overlevingsperce entage in functie vvan het kankerstad dium.

4 4.3.4. Gegeven nsinvoer voor het model Om deze oefenin O ng te kunnen do oen, hebben we zo goed mogelijjk de B Belgische gegeve ens in ons model ingevoerd. Dezze parameters wo orden g gedetailleerd besc chreven in hoofdsttuk 3.3 van het ra apport. D levensverwach De hting van de onde erzochte populatiie is afkomstig va an de o overlevingstabelle n van de vrouwelijke popu ulatie van dez zelfde le eeftijdsgroep. De incidentie van kanker k in functie van de leeftijd en e de s stadia van de ziekte z is afkoms stig van het Be elgisch Kankerregister (V Vlaamse Gemeenschap). De gegevens met betrekkking tot de screening z zijn afkomstig uit de huidige prog gramma's (vrouw wen van 50-69 ja aar in W Wallonië, Brussel en de Vlaamse Gemeenschap). G V Voor elk compartiment van het model werd de levvenskwaliteit gem meten. H model bevat een Het e basisscenario o (base case) datt overeenstemt met m de m meest aannemelijk ke situatie. “ wezen zijn alle modellen vals, maar “In m sommige zijn n nuttig”a

4 4.3.5. Sensitivitteitsanalyse In n ons model zijn n we uitgegaan van een zeker aantal simplificerrende h hypothesen omwiille van de gege evens waarover w we beschikten, en e de n noodzaak om te vermijden een te t complex mode el te gebruiken. Deze k keuze veroorzaak kt onzekerheid die e verband houdt met de structuur van h model, met de het e goede keuze van n de parameters e en met de bron va an de in nformatie. Om aa an deze verschillende soorten onze ekerheden het hoo ofd te k kunnen bieden, hebben we een e diepgaande e sensitiviteitsan nalyse u uitgevoerd waarbijj we gebruik maakten van verschilllende scenario's. Deze v verschillende scen nario's worden ge edetailleerd besch hreven in tabel 3.2 2 van h wetenschappe het elijk rapport.

a

citaat toegesc chreven aan de statisticus George Boxx.

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5. RESULTATEN Het basisscena ario toont dat uitb breiding van de screening s tot 74 jaar 1,3 overlijdens zou u kunnen voorko omen per 1000 deelnemende vrouwen, v hetgeen een da aling van de sterffte met 21% vertegenwoordigt. He et aantal gewonnen leve ensjaren wordt ge eraamd op 13,1 en de winst in QALY Q op 3,9. Deze sensitivitteitsanalyse omvvat een pessimistisch scenario en een optimistisch sce enario. Het pessimistis sch scenario gaat uit van een hypothese met een ov vertollige diagnose van 20%, 2 een percenta age vals-positieve en van 10% waard door een verlies van lev venskwaliteit worrdt veroorzaakt van v 0,19 dat gedurende 54 dagen aanhoudt (de tijd nodig om de resultate en te ontkrachten). Op de oep werd de verrdeling van de opgespoorde o kank kers per gescreende gro stadia die mom menteel wordt vasttgesteld in het kader van de in Vlaanderen georganiseerde e screening (50 0-69 jaar), toege epast. Dit pessiimistisch scenario raamtt een winst van 8 8,7 levensjaren, maar m een verlies van 3,1 QALY per 1000 vrouwen die aa an de screening deelnamen. Dit betekent b e omstandigheden n - en we blijven hierbij zeker realistisch dat in bepaalde de screening ka an leiden tot een d daling van de leve enskwaliteit. Het optimistisch h scenario gaat u uit van een hypotthese met een ov vertollige diagnose van 3%, 3 een percenta age vals-positieve en van 2% waard door een verlies van leve enskwaliteit wordt veroorzaakt van n 0,13 dat gedure ende 36 dagen aanhoud dt. Dit scenario p past op de gescre eende groep de verdeling v per stadia toe die momenteel w wordt vastgesteld d in het kader va an de in organiseerde sccreening (70-74 jaar). Dit optiimistisch Nederland geo scenario raamtt een winst van 17,0 levensjaren n en een winst van v 16,2 QALY per 1000 0 vrouwen die aa an de screening deelnamen. Dit betekent b dat het nodig is s om gedurende vvijf jaar 62 vrouwe en voor een scree ening uit te nodigen om een e QALY te winn nen.

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6 BESPRE 6. EKING De resultaten van het hierboven beschreven model w D wijzen erop dat, wat w de b basissituatie betre eft, de winst in le evensjaren 13 ja aar bedraagt per 1000 g gescreende vrouw wen. Dit resultaat blijft betrouwba aar doorheen gan ns de s sensitiviteitsanalys se. De QALY daa arentegen variëren aanzienlijk in fu unctie v van de gekozen hypothesen, h gaan nde van een rela atief geringe wins st tot, v volgens sommig ge geloofwaardige hypothesen,, een verlies aan le evenskwaliteit.

6 6.1. Levensjarren toevoegen? ? De verhoging van D n de levensverw wachting van de vrouw is één va an de a argumenten die worden w gebruikt om o borstkankersccreening uit te breiden to ot vrouwen die ouder o zijn dan 69 6 jaar. Dit argum ment gaat uit va an de v veronderstelling dat de populatie van de zevventigjarigen dez zelfde k kenmerken heeft als a de populatie van v de zestigjarige en. Dit is helemaa al niet h geval voor het aantal vrouwen dat het d overlijdt en hun doodsoorzaak. H aantal overlijd Het dens vastgesteld in de leeftijdsgro oep van 70-79 ja aar is tw weeënhalf keer zo z hoog als die in de leeftijdsgroe ep van 60-69 jaa ar. De B Belgische populattie verliest 4% van haar effectieve leden tussen 50 à 59 ja aar, 8% tussen 60 0 à 69 jaar en 20% % tussen 70 à 79 9 jaar (Belgian life table 2 2009). D oorzaken van het overlijden verrschillen eveneen De ns. In België wijzig gt het p percentage overlijjdens door borstk kanker van 13% tussen 60 en 64 4 jaar n naar 6% van alle overlijdens tusse en 70 en 75 jaar. Op die leeftijd zijn de m mortaliteit door ka anker, en de card diovasculaire morrtaliteit praktisch gelijk e elk verantwoorrdelijk voor meer dan een derde vvan alle overlijden en ns. In h overlijdensperrcentage daalt he het et aandeel van bo orstkanker dus met m de le eeftijd (KCE-rappo ort nr. 11).

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6.2. Toevoe egen van levenskwaliteit aan levensjaren?

7 CONCLU 7. USIES

6.2.1. Minderr agressieve beh handelingen?

7 7.1. Moet men n de screening uitbreiden tot d de leeftijd van 74 jaar?

Naast de wins st in levensjaren is het voornaam mste voordeel da at wordt verwacht van screening de mogelijkheid om o minder agressieve Echter, noch de gegevens afkomstig van behandelingen toe te passen. E de gecontroleerde studies, noch de d feitelijke gegev vens die gerandomiseerd werden verzam meld in België, kon nden deze verwac chting bevestigen.

6.2.2. Vals-positieven In ons model vertegenwoordig gden de "vals-po ositieve" diagnos sen een on van verlies aa an levenskwaliteit. Een hoog perrcentage belangrijke bro vals-positieve resultaten r (dat to ot 10% kan bedra agen) gecombine eerd met een relatief lan nge wachtperiode e (gemiddeld 45 dagen) voor bijk komende onderzoeken kan k leiden tot e een totaal negatief screeningresu ultaat in termen van QA ALY. Als men e erin slaagt om dit percentage bin nnen de Europese norm men te houden (3,5%) zoals dit het geval is in één re egio van het land (in Vlaa anderen), is de w winst aan QALY 3 op 1 000 vrouwen n.

6.2.3. Overto ollige diagnoses en behandeling gen Het risico van overtollige diagnoses is het grootste risico van sc creening arigen. Wanneer w we een percentag ge over-diagnose van 3% voor zeventigja toepassen, kan n men zich eraan verwachten dat in elk cohort van 100.000 vrouwen, 108 bijkomende b vrouw wen een diagnose van kanker zullen n krijgen en waarschijnlijk een behand deling zullen on ndergaan. Als we w een er-diagnose van 10% toepassen, sttijgt dit aantal tot 367. 3 percentage ove Anderzijds worrden alle vrouwen bij wie de diag gnose van kanke er wordt gesteld door miiddel van screenin ng, twee tot drie ja aar eerder ziek da an in het geval van een klinische diagnosse. Dit heeft een negatieve invloe ed op de e levensjaren die zzij nog hebben. kwaliteit van de

De conclusie van deze studie is da D at het antwoord o op deze vraag nee en is. D Deze uitspraak is enerzijds gebase eerd op de resulta aten van het mod del en a anderzijds op de specifieke s contextt van deze vraag. De resultaten va an het m model tonen een winst van 13 le evensjaren aan per 1000 gescre eende v vrouwen. Sommige hypothesen, die e helemaal niet on nrealistisch zijn, wijzen w e echter op dat het er h netto-resultaa at van een uitbreid ding van de screening e algemeen verrlies in levenskwa een aliteit kan veroorzzaken. Deze resultaten z dus als zodan zijn nig niet doorslagge evend in de bijzondere context van n een g georganiseerde s screening. Georg ganiseerde scree ening richt zich h per d definitie op een in ndividu die geen enkele klacht, no och vraag heeft. Deze s specificiteit houdt in dat men des te meer waakza aamheid moet in acht 11 n nemen op het vla ak van ethische principes p . Drie e ethische basisprin ncipes z met name op screening van to zijn oepassing: het prrincipe van weldo oen of g geen schade toe ebrengen, het principe p van recchtvaardigheid off van b billijkheid en het principe van respect voor autonomie e12. H principe van weldoen of gee Het en schade toebre engen wordt als volgt g gedefinieerd: "Ten n eerste geen kw waad doen, in ied der geval geen kwaad k d doen (primum no on nocere) Dit moet m gepaard gaa an met een plich ht tot w weldoen die sam mengaat met een n houding van welwillendheid"12. Het p principe van rechttvaardigheid of billijkhkeid is: "dezze bezorgdheid die d de c collectieve dimens sie van gezondhe eidsproblemen laa at tussenbeide ko omen m met van een voorkeur voor de meest zzwakken, de meest m 12 a achtergestelden ” ”. H doel van hett organiseren van Het n screening is he et verbeteren van het w welzijn van de be evolking door voortijdige overlijde ens te voorkomen n. De re esultaten die via het model werden n verkregen lieten n echter niet toe om o uit te e sluiten dat in sommige s gevallen screening de llevenskwaliteit va an de o onderzochte leefttijdsgroep negatie ef zou kunnen beïnvloeden. In deze o omstandigheden zou dit kunnen leiden tot een n schending van n het b basisprincipe: “prim mum non nocere”” (in ieder geval ge een kwaad doen).

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Anderzijds is screening s duidelijjk minder doeltre effend voor vrouw wen met een lagere lev vensverwachting. Dit verschil in doeltreffendheid bestaat zeker ook bij de d andere leeftijdssgroepen, maar minder m uitgesprok ken. Het respecteren va an het principe va an rechtvaardighe eid of billijkheid blijkt b dus een bijkomende e reden te zijn om negatief te anttwoorden op de gestelde g vraag.

7.2. Wat mo oet men zeggen tegen een pe ersoon die om screening vraagt? De context van n deze vraag ond derscheidt zich van vorige vraag op twee punten: het ind dividu zelf is hier vragende partij en e het probleem moet op individueel vlak k worden geëvalue eerd. Het principe e van het respecte eren van de autonomie is zeer goed van n toepassing in deze d situatie. Dit principe n is het wordt als volgt gedefinieerd: ""het respecteren van de persoon h respecteren vvan de autonomiie van de persoo on vloeit basisprincipe, het hieruit voort; het h gaat om he et erkennen van het vermogen van de individuele pers soon om keuzes tte maken voor zic chzelf (zelfbeschik kking en vrije keuze) en om zijn handelwijjze te beheersen (zelfbestuur)12”. Opdat O de v keuze zou kunnen maken, is het belangrijk k dat hij persoon een vrije duidelijk en co orrect geïnformee erd wordt over de vooren nade elen van screening in zijn persoonlijke situ uatie. Het recht op o informatie (artik kel 7) en eïnformeerde toesstemming zijn bes schreven in de Belgische het recht op ge wet betreffende e de rechten van d de patiënt. De geïïnformeerde toesttemming van de patiën nte kan slechts worden verkreg gen na lezing van v een informatieblad. Het gaat om een proces wa aarbij idealiter ook o een n ideeën met de zzorgverlener moett plaatsvinden uitwisseling van Tevens is het nuttig n dat de arts voor zijn patiënte e die om screening vraagt een strategie uitwerkt u die de na adelen tot een minimum beperkt13. Zo kan een houding in drie stappen word den aanbevolen: •

Specifieke informatie voor de leeftijdsgroep

•

en van een besslissing in functtie van de pers soonlijke Het neme beoordeling g van de patiënte14.

•

Oriëntatie van de persoon die screening we enst, naar een sc creening e modaliteiten de nadelen tot een minimum m beperke en. waarvan de

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De criteria die werden D w gedefinie eerd in het kade er van het Euro opese p programma voorziien met name hett toezicht op de te echnische kwaliteit van d gebruikte appa de aratuur, een dubb bele lezing van d de mammografieë ën en e optimalisatie van een v het trefpercen ntage1. Aangezien n in België de erk kende m mammografische afdelingen moe eten beantwoorden aan welbepaalde c criteria in het kad der van het Eurropese programm ma, is het logisch h om v vrouwen die uitdrrukkelijk om scre eening vragen na aar deze structuren te o oriënteren.

7 7.3. Kernbood dschappen Het doel van hett organiseren van H n screening is he et verbeteren van het w welzijn van de bevolking door voortijdige overliijdens te voorko omen. U Uiteraard zou het uitbreiden van de e screening naar de leeftijd van 74 4 jaar h mogelijk make het en om enkele lev vensjaren te winnen. Echter, de invloed v van deze maatre egel op de levenskwaliteit is du uidelijk meer onz zeker. V Volgens billijke hypothesen zou deze d interventie zelfs een verlies s van le evenskwaliteit ku unnen veroorzake en. In deze omstandigheden zo ou de b balans tussen de vooren nad delen van scree ening eerder ku unnen d doorslaan naar de kant van een algemeen verlies van welzijn va an de b bevolking.

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2.

3.

4.

5.

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Perry N, N Broeders M, de e Wolf C, Tornberg g S, Holland R, vo on Karsa L. Euro opean guideliness for quality assu urance in breastt cancer screeniing and diagnosiss. Fourth edition---summary docume ent. Ann Oncol. 2008;19(4):614-2 22. Schwarrtz LM, Woloshin n S. News media a coverage of sc creening mammo ography for women in their 40s and a tamoxifen for primary preventtion of breast cancer. JAMA. 2002;287(23):3136-42.. Schwarrtz LM, Woloshin S, Fowler FJ, Jr.., Welch HG. Enthusiasm for cancer screening in the United States s. JAMA. 2004;29 91(1):718. man E, Woloshin S, Schwartz LM M, Byram SJ, We elch HG, Silverm Fischho off B. Women's vviews on breast cancer c risk and sc creening mammo ography: a qualittative interview sttudy. Med Decis Making. 2001;21(3):231-40. Schwarrtz LM, Woloshin S, Sox HC, Fisc chhoff B, Welch HG. US women n's attitudes to fa alse positive ma ammography resu ults and detectio on of ductal carcinoma in situ: cros ss sectional surve ey. BMJ. 2000;32 20(7250):1635-40 0. Belgian n Cancer Registrry, editor. Cance er incidence in Belgium, B 2004-2005. Brussels; 20 008. Paulus D, Mambourg F F, Bonneux L. [B Breast cancer scrreening]. Good Clinical Practice (GCP). Brussells: Belgian Health Care edge Centre (KC CE); 2005 02/05//2005. KCE Rep ports 11 Knowle Availab ble from: http://kc ce.fgov.be/index_ _en.aspx?SGREF=5221&CREF=93 348

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11. 12. 13.

14.

Mandelbla att JS, Cronin KA A, Bailey S, Berrry DA, de Koning g HJ, Draisma G, et al. Effects of mammogra aphy screening under u dules: model esstimates of pottential different screening sched m appears in Ann n Intern Med. 2010 0 Jan benefits and harms.[Erratum 0):738-47. 19;152(2)::136]. Ann Intern Med. 2009;151(10 Woloshin S, Schwartz LM, Byram SJ, Sox H HC, Fischhoff B, Welch W men's understand ding of the mam mmography screening HG. Wom debate. Arrch Intern Med. 20 000;160(10):1434 4-40. Mandelbla att JS, Silliman R. Hanging in the balance: making decisions about the benefits s and harms of brreast cancer screening e oldest old witho out a safety net o of scientific eviden nce. J among the Clin Oncol. 2009;27(4):487--90. Doumont D, Verstraeten K. Enjeux éth hiques du dépistage unauté Française. 2012(7):3-7. organisé. Santé en Commu D les ca ancers, mais à quelle condition n In: Gallois. Dépister UNAFORM MEC, editor. Médecine. Paris; 2005 5. p. 72-7. USPSTF. Screening for Brreast Cancer: U.S S. Preventive Serrvices dation Statementt Annals of Intternal Task Forrce Recommend Medicine 2011(151):716-26 2 6. Woloshin S, Schwartz LM. The bene efits and harm ms of AMA. mammogrraphy screening: understanding tthe trade-offs. JA 2010;303((2):164-5.

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SCIENTIFIC REPORT T


KCE Reportt 176

1 INTROD 1. DUCTION 1 1.1. Context of o this report This report is a partial update of the clinical practicce guideline (CPG T G) on b breast cancer screening published d in 20051. Therefore, the KCE ex xperts m made a list of clinical c questions s related to brea ast cancer scree ening. R Representatives o stakeholders’ orrganizations were of e then invited to re eview th he choice and the e wording of the questions, to highliight the main prob blems re elated to each question and to score the relevance of cllinical q questions(see KC CE report 172)2. Selected questio ons were then divided o over three KCE re eports. A first KCE E report published d in 2010 is focuse ed on b breast cancer scre eening with mam mmography for wo omen in the age group g o 40-49 years (KC of CE report 129)3. The second is focused on identific cation o women at risk fo of or breast cancer and a technical metthods for breast ca ancer s screening (KCE re eport 172)2.

1 1.2. Scope of this report This report focuse T es on the extensio on of organized brreast cancer screening w with mammography to older wom men. Eligible pop pulation is define ed as w women between 70-74 7 years of age e with average risk of breast cancer.

1 1.3. Breast ca ancer screening g in Belgium The Belgian fed T deral and regional governmentss signed a pro otocol a agreement in 200 01 for an organized screening programme for wo omen a aged 50-69 years s, to be organiz zed by the regional governments s with a appropriate financ cial resources sup pplied by the fede eral government. Since S 2 2001, Flanders, th he Walloon region n and the Brusse els capital region have e each introduced an a organized scre eening programm me within their sp pecific c context of alread dy existing practtices. Indeed, op pportunistic screening re emains quite freq quent in the Wallo oon and Brussels region among wo omen in n the age-group 50-69, 5 but also among a younger (4 40-49 years of ag ge) or o older women (>7 70 years). In Flanders, screening mammographies s are d dominant in the ag ge-group 50-69. In the age-group 7 70-79 overall cove erage d drops, mainly beca ause organized sc creening stops at age 69. The cove erage b means of diagn by nostic mammogra aphy decreases also with 3%, indic cating th hat substitution of screening mamm mography by opp portunistic screeniing at

KCE Report 176 6


the age of 70 is not frequent in Flanders. At this age, total coverage c ortunistic (including both diagnostic or folllow up mammogrraphies and oppo mains at 18% in F Flanders, 33% in Brussels and 30% % in the screening) rem Walloon region (KCE report 172))2.

1.4. Clinical questions This specific report addresses th he following questiions: 1. What are clinical c benefits off an extension off breast cancer orrganized screening in i women betwee en 70 and 74 years s? 1.1. What is the effect of an n extension (70-74 4 years) of breas st cancer er related mortality y? organized screening on the breast cance ong is the delay b between the scree ening and the associated 1.2. How lo breastt cancer related m mortality reduction? ? 1.3. What is the effect of an n extension (70-74 4 years) of breas st cancer organized screening on the overal mortallity? n extension (70-74 4 years) of breas st cancer 1.4. What is the effect of an organized screening on morbidity? ension of breast cancer 2. What are the specific harms of an exte s in wom men between 70 and 74 years?H Harms in organized screening terms of false positive o or false negative re esults? 2.2. Harms s in terms of additional diagnostic te ests? 2.3. Harms s in terms of over--diagnosis? 2.4. Harms s in terms of overttreatment? 3. What attitu ude should be re ecommended for women in case e of self referral?

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1 1.5. Scientific approach For each clinical question, a sys F stematic search of the literature was p performed and dis scussed with the support of extern nal experts chose en for th heir scientific co ompetency in se everal fields: gyynaecology, radio ology, e epidemiology, or health economic cs. For question n 3, we searche ed for m models. To quan ntify what the im mplications of ourr findings are on n the B Belgian situation we applied da ata from the Intermutualistic Ag gency (IMA/AIM), cancerr registry and datta from the literature on the Belgia an life ables and constru ucted a simple tim me dependent Markov chain with annual ta c cycles. T methodology used and the resu The ults are described d in each chapter.

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2. LITER RATURE RE EVIEWS 2.1. Review w of clinical stud dies 2.1.1. Metho odology 2.1.1.1. Sou urces A broad searc ch of the electronic databases OVID O Medline, EM MBASE, CDSR and DAR RE was conducted d in April 2011. Se earch was conduc cted first for systematic reviews r (SR) and meta-analysis (M M-A).

2.1.1.2.

Sea arch terms

For searching on o Medline database, the following g MeSH terms we ere used in combination with usual langua age: Breast neoplasms (MESH) an nd mass e detection) ((MESH) and mam mmography (MES SH). For screening (or early EMBASE, the following Emtree terms were used: u 'cancer scrreening', phy'. These MESH H and Emtree term ms were 'breast cancer' and 'mammograp entify systematic reviews combined with a standard searcch strategy to ide nalysis (M-A). (SR) or meta-an

2.1.1.3.

In- and exclusion crriteria

Databases werre searched for S SR and M-A in English, E French, Dutch D or German. This report r is a update e of previous KCE E report1 (search made in 2004), thus we w used a date restriction (2004 4-2011) and a la anguage restriction (English, Dutch, Frencch and German). Inclusion criteria used for d on title, abstra act or full text were: w population (women selection based without breastt cancer and w without particula ar breast cance er risk), intervention (m mammography), o outcome (mortality, morbidity, additional diagnosis tests, over diagnosis and over treatme ent), design (SR or o metaCT), key question (screening), age e of population (> >70 and analysis or RC <75 years), and original publica ation. Relevant pu ublications were selected b 2 reviewers (FM M, JR). independently by

2 2.1.1.4.

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Additio onal evidence

We identified two SR4, 5 as the more W m extensive so ource for the rese earch q question 2. Therrefore the evide ence-identified through those SR R-was u updated by search hing Medline and the Cochrane Database of Systematic R Reviews from the search date of the t two SR’s on (search date Nov v-Dec 2 2008). Additional hand h searching of o reference lists w was also undertak ken to e ensure that no potentially relevant studies were missed. We also sca anned re eference lists off SR and of ou ur previous repo ort on breast ca ancer 3 s screening . T The identified studies were selecte ed based on title e and abstract. For F all e eligible studies, the full-text was s retrieved. In ccase no full-text was a available, the stud dy was not taken in nto account. T The description and results of the literature searche es and flow of sttudies s search are in Appe endix 1.1.

2 2.1.1.5.

Quality ty appraisal

The methodologic T cal quality of systtematic reviews a and associated riisk of b bias were rated using the check klists of the Dutch Cochrane Centre C (w www.cochrane.nl). The assessmen nt of the risk of b bias in the include ed SR w conducted by was y a team of two rev viewers (FM, JR).. T methodologic The cal quality of selec cted additional evvidence was also rated u using the adeq quate checklists of the Dutch Cochrane Centre C (w www.cochrane.nl). T results of the quality appraisal are The a in Appendix 1.5.

2 2.1.1.6.

Identiffied systematic reviews r

In n the systematic search for literature reviews, 53 citations on the topic w were identified in n database searrches. The majo ority of citations were e excluded on the basis b of title and abstract; 10 citattions were retriev ved in fu ull and reviewed in more detail. On O the basis of tthe full text, 5 rev views w were included4-8. T The reviews writte en by Götzsche and Nelson4, 5 a are mainly focuse ed on m mortality as outco ome, those from Biesheuvel and JJorgensen6, 7 on overd diagnosis and the review of Virnig8 on ductal carcinoma in situ (DCIS).

KCE Report 176 6


23

As a first step,, a quality appraisal of all the rev views was carried out to 4 5 determine theirr suitability for incclusion. Götzsche e and Nelson SR4, were 5 judged to be off high quality with a low risk of bias s. Nelson review was an update of one e other review performed by Humphrey H for th he U.S. Preventive Tas sk Force9. Humph hrey review was also a judged to be e of high quality and used here as comple ementary information source. The review writtten by Biesheuve el6 was judged to be b of good quality y (quality appraisal of selected trials not ssufficiently describ bed) and those written w by s judged to be off high quality. The e review written by b Virnig Jorgensen7 was was also judged d to be of high quality.

For DCIS, this upd F date was carried out in July 2011 identifying 7 citations. A citations were excluded All e on the basis b of title and abstract. F overtreatmentt, this update was For s carried out in Ju uly 2011 identifyin ng 19 c citations on Medlin ne and 7 citations s on the Cochrane e Library. The ma ajority o citations were excluded of e on the basis b of title and abstract; 2 pape ers on o overtreatment werre retrieved in full and reviewed in more detail. On the b basis of the full te ext, we retrieved again a the SR writtten by Götzsche4 and s selected one pub blication presentiing data issued from the UK Breast B S Screening Program mme11. The description and resultss of those update es are in n Appendix 1.4.

2.1.1.7.

2 2.1.1.9.

Iden ntified RCT 5

The evidence was w updated using g the key words reported in Nelson n SR by searching Med dline and the Cocchrane Database e of Systematic Reviews R from the search h date of this SR on (search date Nov 2008). The literature search for relev vant RCTs carried out in Medline, EMBASE and CCRT C (in April 2011) iden ntified 432 citation ns. The majority of o citations were excluded e on the basis off title and abstractt; the other paperrs (n=8) were retrrieved in full and review wed in more deta ail. On the basis of the full text, all eight studies were ex xcluded because of the study des sign (not an RCT T) shows the flow of rand domized controlled d trials from selec ction to in-or exclusion. By hand searc ching of referencce lists of Götzs sche and Nelson4, 5, the Swedish RCT’s s were identified. Among those, the e Two County tria als is the only RCT tha at includes wom men aged 70-74 years at the time of randomization. Quality appraisall of this RCT was s carried out to de etermine f inclusion. The Two County trials was judged to be b of fair their suitability for quality by Nelson and of low qu uality by Götzsche e and included fo or further analysis10.

2.1.1.8.

Iden ntified additional evidence

For diagnostic errors and over--diagnosis, this update was carrie ed out in o citations were excluded e July 2011 identtifying 10 citations. The majority of on the basis of o title and abstrract; 2 papers on n diagnostic erro ors were retrieved in full and reviewed in more detail. On the basis of the full text, ers are discussio ons and those two studies were excluded. Most pape he two main SR4, 5. comments on th

Ongoiing clinical trials

In n addition to the database search hes, the ClinicalT Trials.gov website e was s searched for clinic cal trials. The sea arch terms ‘breastt neoplasm’ as well w as ‘s screening’ and ‘m mammography’ were w used to search for studies.. The m majority of search h results (n=135 5) were ongoing trials. Two poten ntially re elevant trials (NC CT00963911, NC CT00247442) werre identified but were c considered as out of scope after receiving more iinformation on th he full p protocol.

2 2.1.1.10. Data extraction e Data from system D matic reviews and from trials were e extracted into a data e extraction table (D DET) summarizin ng key design fea atures and resultts. All d data extraction tab ble are in Appendiix 1.6.

2.1.2. Descripttion of screening 2 g benefit 2 2.1.2.1. Sourc ces In n the years 196 60-1980, USA, Sweden, S Canada and United King gdom c conducted random mized controlled trrials of mammogra aphy screening. In n US, th he HIP trial (N = 60 995) started d in 1963. In Sw weden, the Malmö ö trial (phase I and II, N = 60 076) started in 1976 and 1978 8, the Two county y Trial = 133 065) in 19 977-78, the Stock kholm (Kopparberg and Ostergötland, N= n 1980 and finally y the Göteborg tria al (N= 51 611) in 1981. trrial (N= 60 117) in In n Canada, the Na ational Breast Sc creening Trials (N NBSS-1 and 2, N = 89 8 835) were initiated d in 1980. In Unite ed Kingdom, the E Edinburgh, trial sttarted in n 1979 in 1980 (N N=44 268) and th he UK Age Trial iin 1991 (trial limitted to

24


women aged 40-49 years)12. Numerous publlications and so ome SR ow available. summarizing theirs results are no ased on the SR R (2002) commiss sioned to assist the US This part is ba Preventive Serv vices Task Force e (USPTSF) and its update of 200 095,9 and 4 on the Cochran ne SR . We ana alysed more in de etail one RCT named the Swedish Two-C County trial (Osttergötland) which h was included by both SR10,13,14. Both reviews in ncluded the same e trials in their me eta-analysis: the HIP H trial, Malmö I and II, the Two coun nty trial, the NBS SS trials (1 and 2), the A Trial. The Ed dinburgh Stockholm trial, the Göteborg trrial and the UK Age d as poor quality b by both authors an nd excluded there efore4, 9. study was rated Nelson updated d the meta-analyssis from Humphrey y9 to include new findings about younger women (40-49 yyears of age). Th herefore, we refe er to the blication for morta ality analysis perrformed on wome en aged Humphrey pub from 50 to 74 years. Götzsche e4 performed firstt a meta-analysis s among 4 years of age. T Then he did a sep parate analysis forr women women 39 to 74 younger than 50 0 years and for w women older than 50 5 years. Two-County trrial We analysed the Swedish T Two-County trial in order to fin nd more ears). The Swedis sh Twoinformation on our specific population (70-74 ye he first eight rand domized trials. We W used County trial is the largest of th e publications tha at describe this study. s We used the first therefore three publication of th he initiator10, the p publication of Nys ström13 who was selected s by Nelson and the last publication of Tabar published in July 201114. The wedish National Board B of Two-County trial was commissioned by the Sw W and inclu uded women in two Swedish counties: c Health and Welfare Kopparberg and d Östergötland. In n 1977-78, 134 867 women aged 40 4 to 74 years were cluster-randomized d by geographic area. They we ere also ocioeconomic stattus, urban or rura al residency, and d size of stratified by so cluster. Finally, 78 085 women n were invited to o the screening. Among n aged 70-74 years in the screenin ng group those, they werre 10 568 women and 7 462 in the t control group. At this age, wo omen were invited d to two screening roun nds with a screen ning interval of 33 3 months. The trial t was closed in 1984 after approximate ely 7 years of scre eening10.

KCE Reportt 176

In n 2002, Nyström performed one review r of the Sw wedish RCT’s including th he Malmö, Oste ergötland, Stockh holm, Göteborg trials. Results of o the K Kopparberg trial were w not available e at this time. Thiss publication asse essed th he age-dependen ncy of the effectt of screening. T The author calcu ulated m mortality relative risks r for consecutive 5-years age g group based on re esults frrom the Ostergöttland trial. The median m follow-up time was 17.9 years. y U Unfortunately, with hout the Kopparbe erg part of the Sw wedish trial, the nu umber o women 70 to 74 of 4 years of aged enrolled e was low ((approximately 50 000 in e each group)13. F Finally, we found one publication summarizing s long g term data (29 years) y o mammographic on c screening effectt on mortality14. T Trials quality and d bias A studies include All ed by Humphrey in i 2002 and later by Nelson were rated a fair5, 9. Götzs as sche assessed th he randomization n quality. This author a d divided his results s on results based d on adequately ra andomized contro ol trial a results based on suboptimally randomized and r contro ol trial4. N Nevertheless, the third meta-analy yses were judged of high quality with w a lo ow risk of bias (se ee Appendix 1.5.1). S Some publications s based on The Swedish Two-Co ounty reported va arying n numbers of women enrolled. To explain this variation n, Nyström replied d that s some studies ana alysed results by y year-of-birth wh hile some others used e exact age at rand domization13. Nev vertheless, Götzscche assessed this s trial a suboptimally ra as andomized and likely to be biase ed. He argued that for O Ostergötland, a pu ublic notary alloca ated the clusters b by tossing a coin while w witnesses were prresent. Breast ca ancer mortality in the control group p was a almost twice as high h in Kopparbe erg compared to Ostergötland (0.0021 v versus 0.0012, p = 0.02). The au utopsy rate was 36% for all the TwoC County trial and ca ause-of-death ass sessments were n not blinded4. Acco ording to o that the validity y of local end poin nt committee data a was criticized, a third c committee (named d consensus committee) reviewed the records conta aining a doubtful cause of o death14.

KCE Report 176 6

2.1.2.2.


Bre east cancer relatted mortality red duction

For women age ed 39 to 74 yearss and at approxim mately 13 years of o followup, the Humphrrey meta-analysiss (M-A)9 and the Cochrane C review4 showed a significant re eduction in breasst cancer mortalitty of 16% (Relative Risk (RR) 0.84, 95% % confidence inte erval (CI) 0.77 to 0.91) and 19% (Relative ( Risk (RR) 0.81,, 95% (CI) (0.74, 0 0.87) respectively y. For women ag ged 39 to 74 years, the Review of Swedish rand domized control trial sho owed a significan nt reduction in breast cancer mortality at 15.8 years (me edian follow up) o of 21% (Relative Risk R (RR) 0.79, 95% 9 (CI) 0.70 to 0.89). This T study showed d that the effect off breast cancer sc creening in terms of brreast cancer morrtality reduction varies according to age range13. For women age ed at least 50 y a at randomization, three t trials with adequate a randomization did not show a significant reduction in breast cancer y (Relative Risk (RR) 0.94, 95% % (CI) 0.77 to 1.15). Four mortality at 13 years trials with suboptimal randomizzation showed a significant redu uction in m (RR of 0 0.77 (95% CI 0.67 7 to 0.83)). The RR R for all breast cancer mortality 4 seven trials com mbined was 0.77 ((95% CI 0.69 to 0.86) 0 . trial, applying a more The review of o Swedish rand domized control conservative de etermination of ca ause of death for women w aged at le east 70 y at randomizatio on, did not show w a significant reduction in breastt cancer mortality at 17.4 years ((RR) 1.1 12, 95% (CI) 0.73 3 to 1.72)). Unforttunately, mall (approximate ely 5000 women in each this age group was relatively sm owered13. Consequently, we must conclude c group) and this study is underpo t age group5. together with Nelson that data arre insufficient for this

2.1.2.3.

Dellay between scre eening and spec cific mortality red duction

Tabar publishe ed in July 2011 the last follow-up p result (29-yearr) of the Swedish Two-C County Trial14. T This publication modulated m breastt cancer mortality reducttion in function of length of follow up. u In this report both b data issued from loc cal end point com mmittees and con nsensus-based da ata were presented. The validity of local e end point committe ee data was criticized, we c data. For women age ed 39 to 74 yea ars, this present here consensus publication sho owed specific morrtality reductions of 20% ((RR) 0.8 80, 95% (CI) 0.62 to 1.0 05), 27% ((RR) 0 0.73, 95% (CI) 0..59 to 0.92), and 27% at respectively 10 0, 15 and 20 to 2 29 years of follow w up. In the sam me time,

25

deaths from breas d st cancer preventted in the study g group increased along le ength of follow-u up. They were re espectively 50, 9 99, 114, 122 and d 126 d deaths prevented at 10, 15, 20, 25 and 29 years of ffollow-up for all wo omen in ncluded in this study. s Author emp phasized that bre east cancer screening p prevents deaths more m in the mediu um to long term than in the imme ediate fu uture. So most of the breast canc cer deaths would have occurred (iin the a absence of screen ning) more than 10 0 years after rand domization. A Authors did not calculate mortaliity relative risks for each age group g s separately. Resultts presented are based on 133 06 65 women aged 40-74 4 (77 080 in the scre eening group and 55 985 in the con ntrol group), while e they w were 10 568 wome en aged 70-74 ye ears in the screening group and 7 462 4 in th he control group p. In Kopparberrg, cancers diag gnosed after the e two s screening rounds in women aged 70-74 years and breast cancer deaths frrom these cases were w still included d in the results14. A cited on previo As ous point, the grou up of women aged d 70-74 years included in n the Swedish Tw wo-County Trial was w relatively sma all (approximately 5000 w women in each gro oup) and this stud dy is underpowere ed13.

2 2.1.2.4.

All-cau use mortality

The Cochrane SR T R has reported data on all-cause mortality. For wo omen a aged at least 50 y at randomization, two trials with ad dequate randomiz zation (n=73654) did nott show a significant reduction in all-cause mortality at 13 y years (Relative Risk (RR) 1.00, 95% % (CI) 0.95 to 1.0 04). The two trials s with s suboptimal rando omization (n=982 261) also did no ot show a significant re eduction in all-cause breast cance er mortality (RR off 0.99 (95% CI 0..97 to 1.02))4. U Unfortunately stud dies did not have statistical power to detect an all-c cause m mortality reduction n. According to th hat disease speciific mortality is a small frraction of all-caus se mortality in cancer screening trrials, detect a mo ortality re eduction would re equire inclusion off millions of subjecct.

2 2.1.2.5.

Morbid dity reduction

We found no data W a related to the cancer c related mo orbidity in our selected s sources. In other words, we do no ot accept or reje ect the hypothesis s that s screening reduces s the morbidity of the t breast cancerr disease.

26


2.1.3. Descrription of screening harms 2.1.3.1. Sou urces This part is bas sed on the 5 SR se elected in our main search4-8. As ex xplained in part 2.3.5, we e updated those iin July 2011 startiing from the last literature search date. Se ee more details in appendix 1.4.

KCE Reportt 176

screening round). Conversely, false s e-negative mamm mography results are a little more commo on among women aged 70 to 79 9 years (1.5 per 1000 w women per screen ning round)5.

2 2.1.3.4.

Additio onal diagnostic tests t

SR written by Götzsche and N Nelson are descrribed in point 3.1 1.1. The n by Biesheuvel a and Jorgensen6, 7 were focused on o overreviews written diagnosis and subsequently on n overtreatment. Each author us sed very ods to address this issue. Biesheuvel analysed reports different metho issued from the first RCTs whiile Jorgensen an nalysed data issu ued from zed screening prrogrammes. The review written by b Virnig publicly organiz was focused on n ductal carcinoma a in situ (DCIS)8.

Rates of additiona R al imaging are rela atively low among women aged 70 to 79 y years (64.03 per 1000 women pe er screening round). Biopsy rates s are h higher among wo omen aged 70 to o 79 years (12.2 per 1000 women per s screening round) than among youn nger women. As expected, the nu umber o screen detected of d cancer is highes st in this age grou up. Results indicatte 6.5 s screen-detected in nvasive cancer and 1.4 screen-de etected DCIS per 1000 w women per screen ning round. The BCSC B results indiccate that for every y case o invasive breast cancer detected by mammograph of hy screening in wo omen a aged 70 to 79 yea ars, 154 women have h additional mammography, 10 have o other imaging test, and 2 have biopsies5.

2.1.3.3.

2 2.1.3.5.

2.1.3.2.

Stu udy description

Perrformance of ma ammography

The sensitivity of first mammog graphy for women n aged 70-74 ye ears was wo County trial. T This includes ove er-diagnosis and may be 81% in the Tw difficult to interpret. This data cannot be applied to individual patients ed for patient fa actors (use of hormone h because they are not adjuste herapy, mammog graphic breast de ensity), technical factors replacement th (quality of mam mmography, number of mammogrraphic views) or provider factors (the ex xperience of radio ologists and their propensity to la abel the results of an examination e abno ormal)9. Provider factors may explain that sensibility may y vary between countries4. In the Two County trial, t the specificity of a single mammogrraphic examinatio on was 95.6% forr women ears. This indicate es that 4% of women w who did not n have aged 40-74 ye cancer underw went further diagn nostic evaluation. The positive predictive value of one-tim me mammograph hy was 12% for abnormal a results requiring r further evaluatiion and from 50% to 75% for ab bnormal results requiring r biopsy. Positive e predictive value increases with age a and ranged fro om 18% to 20% among women 70 years of age or older9. Nelson reporte ed data from the Breast Cancer Surveillance Con nsortium (USA) BCSC fo or regularly screen ned women that are a based on resu ults from a single screen ning round. False e-positive mammography results are less common amon ng women aged 70-79 years (68.8 per 1000 wom men per

Over-d diagnosis

Over-diagnosis off breast cancer at screening ma O ay be defined as s the d detection with scre eening of cancer that would not ha ave presented clin nically d during the woman n’s lifetime (and th herefore would no ot be diagnosed in i the a absence of screen ning)6. N Nelson reported ra ates of over-diagn nosis varying from m less than 1% to o 30% w with most from 1% 1 to 10%. She e explained varia ations by inclusio on or e exclusion of DCIS S cases, by wheth her cases are inciident or prevalentt, and b age. She conclluded that the stu by udies are too hete erogeneous to com mbine 5 s statistically . G Götzsche reported d that the level of over-diagnosis w was about 30% in i the R RCT’s that did no ot introduce early screening in th he control group, and s somewhat larger in the sub optimally randomized tria als before screening of th he control group. He found also a 40% to 60% inccrease in inciden nce of b breast cancer in observational o stud dies performed in Australia, Europe e and U USA after beginnin ng of the screenin ng4. B Biesheuvel analy ysed publications s issued from tthe first RCTs (New Y York/HIP, Malm III, Two County, Canada C a and b, Stockholm, Göte eborg, E Edinburgh) and fro om four populatio on-based program mme (Sweden, No orway, N Netherlands and Italy). He selected papers that a attempted to estimate o over-detection of invasive breast cancer by mam mmography scree ening.

KCE Report 176 6


Note that he did not include DCIS. He excluded potentially y biased B were descriibed as: differen nt breast cancerr risk in publications. Bias screened and unscreened u population, low particip pation in screenin ng group and high partic cipation in non-sccreening group, offering o screening g to the control group before b or during fo ollow up, inapprop priate adjustment for lead time. After exc clusion, he seleccted 22 estimates s of over-detection from several (some overlapping) sources. Publicatio ons were categorrized as e-incidence or incidence-rate methods m being based on cumulative t are in appe cluding biased stu udies as endix 1.4.3). Exc (definitions of terms described before, he selected tthe least biased over-detection o es stimates. S cases, over-dettection ranged fro om 7% to 21% forr women Excluding DCIS aged 60–69 yea ars6. Jorgensen ana alysed data issued from public cly organized sc creening programmes. He H selected pape ers that published trends in incid dence of breast cancer before and affter the introduction of mamm mography e that when data were present, DC CIS were included d. If not, screening. Note he estimated that t they would ccontribute to 10% % of the diagnos ses in a screened population. After exclu usion of the impllementation phase of the ast seven years s before screening, he compared data covering at lea y after scree ening in screening with data covering at least seven years n screened age e groups. The most common age-range for screened and non mammography screening progra ammes was 50-69 years. No data specific e increase in incid dence of for women aged 70 to 79 years are available. The elated to the inttroduction of sc creening. breast cancer was closely re ase was compen nsated for by a drop in Surprisingly, litttle of this increa incidence of breast cancer in women older than 70 years. Jo orgensen for invasive cance er was 35%. The e rate of calculated that over-diagnosis fo n this meta-analys sis (95% over-diagnosis including DCIS ccases was 52% in CI 46% to 58%)7. sheuvel or by Jo orgensen Discrepancies between results reported by Bies ot of controversial discussions. have led to a lo The approach Biesheuvel B et al. tto adjusting for lea ad time was conte ested by Zahl, Jorgense en and Götzche (2008), who stated that their estimations were substantia ally downwardly biased, due to over-adjustment, o u use of a hypothetical inc crease in incidencce based on theoretical models and use of

27

ong term follow w up data that are considerablyy diluted. They also lo considered estima c ation unhelpfully wide. w J Jorgensen & Gö ötzsche used line ear regression tto compare obse erved in ncidence with a in an (hypothettical) population that did not und dergo s screening. They assume a a linear in ncrease extrapola ated from prescreening trrends, following the same pattern as the linear tren nd observed in wo omen to oo young to be sc creened. It is difficult to judge if thiis assumption hollds or n not, the graphs the authors prresent show no on-linear increase es in in ncidences before e screening was introduced in the e UK and Norwa ay for w whom no explanattion was given.

2 2.1.3.6.

DCIS

Historically, DCIS H S was rare and diagnosed by ssurgical removal of a s suspicious breast mass. Since the wide use of mammograph hy, a in ncreasing numbers of patients werre diagnosed with h DCIS. The prog gnosis o the disease is excellent. Maass of s reported data isssued from the SEER S d database (Surveillance, Epidemiolo ogy and End Re esults database of o the U United States National Cancer Ins stitute). Those da ata showed a 10 0-year s survival rate of 96.6% 9 for cases s between 1978 and 1983, whe en no s screening was pe erformed. The rate e was 98.1% bettween 1984 and 1989, w when screening was w performed3, 15. R Recent changes in i DCIS incidenc ce in USA were e emphasized by Virnig. V T This author perfo ormed a SR on incidence, treatm ment and outcomes of D DCIS in name of Agency for Healthcare Research h and Quality (AH HRQ). S She included 63 publications ad ddressing inciden nce for analysis. She c compared data obtained before th he screening (19 973-1975) with cu urrent c century data collected in US where e screening is com mmon. DCIS incid dence ro ose there from 1.87 per 100 000 in 1973–1975 to o 32.5 per 100 000 0 in 2 2004. Incidence in ncreased most in women older tha an 50 years. Incre eased u use of mammogrraphy may explain some but nott all of this incre eased in ncidence8.

28

2.1.3.7.


Ove ertreatment

Götzsche reported that the num mber of mastecto omies and lumpe ectomies T trials with adequate a was significantlly larger in the sccreened groups. Three randomization showed a sign nificant increase e in mastectomiies and ( Risk (RR R) 1.31, 95% (CI)) 1.22 to 1.42). Tw wo trials lumpectomies (Relative with suboptimal randomization sshowed the same increase in interv ventions 5% CI 1.26 to 1.61 1)). The RR for alll five trials combined was (RR of 1.42 (95 1.35 (95% CI 1.26 to 1.44)4. Based on recent data from the UK Breast Scree ening Programme e, Dixon mbers of patients s with DCIS. In 1998/99 emphasized the increasing num proximately 1500 cases, but in 200 07/08 there were close to there were app 3500 cases. Although, A most DCIS cases ma ay be treat by breastconserving surrgery, the percen ntage of patients s being treated with w this method has rem mained constant at 30% during this period. Becaus se of the increasing incid dence of DCIS tre eatments, the abs solute numbers off women having mastecttomies has increased from just und der 500 in 1998/99 9 to over 1 900 in 2007/0811 .

2.1.4.

Scree ening conditions

The sojourn tim me (ST) is the avverage duration of o the preclinical screendetectable phase. Estimation off sojourn time ca an be performed by from matical estimates or using mic crosimulation tec chniques simple mathem (mainly Markov v Models)12. Sojou urn time provides an absolute uppe er limit to the lead time obtainable. If the sojourn time is long, the maximum m nding long16. A lo onger sojourn time e results attainable lead time is correspon ber of additional breast cancer detected, d more liife-years in higher numb gained and high her number of yea ars with cancer du ue to lead-time17.

2.1.4.1.

Lite erature search

In a first stage, studies assesssing sojourn tim me were searche ed. Ovid c from 19 948 to October Week W 1 2011. Th he main Medline was consulted search terms (MESH) were: Breast Neoplasm ms/ Mass Screening/ or was included in frree text. The sea arch was Mammography//. Sojourn time w limited to paperrs written in Engliish, Dutch, Frenc ch, or German. Re eference lists of the sele ected studies were e checked for add ditional relevant citations. c See more details in appendix 1.4 4.4.

KCE Reportt 176

Selection criteria S a A retrieved refe All erences were as ssessed against pre-defined inclusion c criteria (in terms of o population, inte ervention, outcom mes, and design-T Table 1) in a two-step procedure: initial assessment of the title, abstractt and k keywords; followe ed by full-text as ssessment of the e selected refere ences. E Estimation of sojjourn time not based b on data were excluded. After e excluding of 3 du uplicates, 40 unique citations we ere identified from m the d databases. Of this s total of 40 refe erences, 23 did n not meet the inclusion c criteria based on title and abstract evaluation. Am mong the 17 cita ations re etained for full-tex xt assessment, 6 did not fulfill the population criteria18-23 a and 1 did not fulfill the outcom me criteria24. Fina ally, 10 studies were 16, 17, 25-32 re etained O search was based Our b on ST dura ation estimations as search. We found f s several publication ns were ST estim mations were issue ed from others sttudies c cited as references by the author. For F example, Zappa in 200332referrred to 29 d data published by y Tabar in 1995 . Duffy in 200526 referred also to those 29 d data . Therefore, we used origina al publications. If one author published tw wo or more articles based on the t same data, we choose the most 30, 31 a accurate for our study s . Finally, 7 publications arre summarized in n data e extraction table (se ee appendix 1.6.7 7).

2 2.1.4.2.

Resultts

Sojourn times ca S alculated on RCT T’s data W found 4 studies based on the results of the Tw We wo- County Trial. The T TwoCounty Tria al is described in n chapter 2 (poiint 2.2.1.1.)10, 13. First e estimates of sojou urn time publishe ed by Tabar and Duffy were base ed on a approximately the same data. Both h authors used th he same Markov chain m model, but results s were not the sam me. Shen underlin ned that the differrence 25, 29 in n estimates publis shed by the two authors a may be caused by diffferent s statistical methods s or by discrepanc cy in the data. Shen applied his rec cently d developed statistic cal methods base ed on the maximu um likelihood estim mates to o data from the Two T County Triall. Authors estima ated the sensitivitiies of e early detection modalities m as 0.92 2 (SD, 0.09) and the mean ST as a 4.4 y years (SD, 0.76)27.

KCE Report 176 6


Sojourn times calculated on sc creening program mmes data Spratt estimate ed the duration of breast cancer be efore detection by dividing prevalence rate es at first screenin ng round by incide ence rates in the following f years. Thereforre, he used data ffrom 10 000 wome en aged 35 to 70y y at start included in the Breast Cance er Detection and d Demonstration Project d that sojourn time e ranged (Louisville). Forr women aged 70-74, he estimated between 2.5 y to t 3.8 y28. Fracheboud co ompared the resu ults of the Dutch breast cancer sc creening programme for women aged 70--75 with the hypotthesis developed by Boer optimistic and pes ssimistic assumpttions for in 1995. Boer had described o SCAN model. Op ptimistic assumpttion assumed no o further use in his MIS increase in pre eclinical duration n of breast cancer after 65years of age although pessim mistic assumption n assumed a furth her increase in prreclinical duration with age a 33. Based on 187 207 screenin ng examinations (women aged 70-74 years), Fracheboud d found that dete ection rates in bo oth initial nt screens increa ased steadily witth age and got close to and subsequen assumption which assume a continuously increas sing sojourn time e beyond b tumours le ead to a the age of 69. This increasing sojourn time of breast e in detection of cancers, but also to t more life- years s in lead strong increase time17. Weedon constrructed one inventive solution for sc creening program mme who do not have fu ull registration off interval cancers s or where oppo ortunistic screening is common. Although h Norwegian reg gistration is of ve ery high nce data from the e first screening round, interval between b quality, inciden screening exam mination or registra ation of interval ca ancer may be insufficient. Therefore, he replaced data la acking by data is ssued from questtionnaire 5 women in the Norwegian Breast B Cancer Sc creening send to 336 533 Programme (NBCSP). This new w approach gave estimation of MS ST to 6.9 en aged 60-69 yea ars, although STS S was estimated to o 60%30. years for wome

2.1.4.3.

2 2.1.5.

29

Key data a

D Data issued from literature l search are a summarized in n table 2.1. T Table 2.1: Data is ssued from clinic cal literature reviiew Question 1: Sho Q ould breast canc cer organized sc creening extende ed in w women between 70 and 74 years? ? P Population

Women be etween 70-74 yyears of age without breast canc cer and without p particular risk of breast b cancer.

In ntervention

Organized screening with mammography

C Comparison

No organized screening

O Outcomes: M Mortality (specific)

For women n >50 y at rando omization, the sp pecific mortality re eduction after a fo ollow-up of 13 yea ars is 23% (RR: 0.77, (CI) 0.69 to 0.86). In the Two al, specific mortality reduction rea ach at County tria significant reduction r of 27% (RR: 0.73, (CI) 0.59 to 0.92) at 15 1 years of follo ow up and incre eases afterwards..

M Mortality (all caus se)

Studies did d not have statistical power to dete ect an all-cause mortality m reduction.

F FP

68.8 per 1000 women age ed 70 to 79 yearrs per r (BCSC-USA A) screening round

F FN

1.5 per 10 000 women aged d 70 to 79 years s per screening round r (BCSC-USA A)

A Additional imagin ng


B Biopsy


Discussion

Most estimates s of sojourn time have been ba ased on Models (mainly Markov chain models). Such m models assume a chronological stepwise s er. Unfortunately, it remains unkno own whether canc cer really growth of cance develop accord ding to a chrono ological sequence e. Estimations of sojourn time must consequently be interp preted with caution.

30


KCE Reportt 176

DCIS

1.4 scre een-detected DCIS S per 1000 wome en aged 70 to 79 9 years per screen ning round (BCSC C-USA)

2 2.2. Review of o modeling stud dies

Over-diagnosis

Over-de etection (excluding DCIS cases), ranged from (7% % to 21%) to 35 5% (no data spe ecific for women a aged 70 to 79 yea ars are available)..

Over-treatmen nt

The num mber of mastecto omies and lumpe ectomies was sig gnificantly larger in the screened groups (RR:1.35 5 (95% CI 1.26 to o 1.44).

In n a first stage, ran ndomized clinical trials analysing th he impact of screening o morbidity and mortality on m were sea arched (see abovve). Then, becaus se the e effectiveness of sc creening require a lot of information n from a wide ran nge of s sources to corre ectly inform decision makers, modeling studies were 35 s searched . M Medline, Embase,, NHS EED and Econlit databasess were consulted from J January 2000 up to t September 2011 (see appendixx 2.1). The search h was limited to papers written in English h, Dutch, French,, Spanish, or Gerrman. R Reference lists of the selected studies were checked d for additional relevant c citations. T keywords use The ed and the results s are detailed in appendix 2.1. The main s search terms (MES SH) were:

2.1.6.

Concllusion

At this age gro oup, performance e of mammograp phy is high and rates of additional imag ging are relativelyy low. Breast canc cer screening ach hieves a specific mortality reduction of 23% to 27% according to autho ors. This ear in the first ye ears after screeniing. The mortality reduction did not appe gnificant before 10 1 years specific mortaliity reduction is not statistically sig after screening g ((RR) 0.80, (CI) 0.62 to 1.05). Breast cancer mortality m reduction must be put in perspecctive with life-expe ectancy for this ag ge-group in our country. elated to quality of life raises questions On the other hand, aspects re cussion of the ben nefit and harms of breast cancer sc creening pertinent to disc in this age-grou up. First, over-diag gnosis being an in nevitable consequ uence of cancer screening, the risk of overtreatment pers sists. Secondly, the t lead ough difficult to esstimate, may be crucial for older women. time bias altho Screening diagnosed breast can ncer and consecu utive treatment ma ay mean h condition” some years earlier than n clinical the end of “the life in good health ast cancer34. diagnosed brea

2 2.2.1.

Literaturre search strateg gy

•

Breast Neopla asms; and

•

Mass Screening or Early Detec ction of Cancer ; a and

•

hy; and Mammograph

2 2.2.2.

Selection n criteria

All retrieved refe A erences were as ssessed against pre-defined sele ection c criteria (in terms of o population, inte ervention, outcome es, and design - Table T 2 2.2.) in a two-step p procedure: initia al assessment off the title, abstrac ct and k keywords; followe ed by full-text ass sessment of the sselected referenc ces. It s should be noted that studies assessing screening g techniques (suc ch as d digital mammography) were exclude ed because such topic was investig gated in n KCE report 1722.

KCE Report 176 6


Table 2.2: Sele ection criteria

Population

Intervention

T Table 2.3: Modeliing studies exclu uded after full-tex xt assessment

Inclusion crite eria

Ex xclusion criteria

E Exclusion criteria a

Studies

caucasian wom men without breast cancer and without particular risk

Otther (e.g. woman n at risk, As sian women, etc.)

P Population

Messecar 2000; 2 Wen 200560, 61.

Screening mam mmography

Otther, including ma ammography tec chniques (e.g. digital mammo ography)

O Outcome

Outcomes

Morbidity and d Mortality (e.g. LYG and Q QALYs)

Otther outcomes (e e.g. over dia agnosis)

Design

Modeling studie es

Otther designs

LYG: life-year ga ained; QALY: Qualityy-adjusted life-year gained

2.2.3.

31

Quantity of research a available

After excluding 195 duplicates, 1058 unique citattions were identiffied from g did not allow us to identify ad dditional the databases.. Hand searching citations. Of this total of 1058 re eferences, 1016 did d not meet the inclusion criteria based on title and absstract evaluation. Among the 42 citations he population critteria and retained for full-text assessmentt, 2 did not fulfill th odeling publicatio ons were 15 did not fulfill the design criterria. Finally, 25 mo erning 6 models d developed by modeling groups inv volved in retained, conce CISNET, 2 app plications of these models on differe ent context and 7 models developed by other groups or authors, as som me models have several 3 . The flow ch hart of this selec ction is presented d in the publications17, 36-59 appendix 2.2.

In ntervention

D Design

Advisory Committee C on B Breast Cancer 2006; 2 Anonymou us 2000; Barratt 2 2002a; Barratt 20 002b; Bonneux 2009; 2 Caplan 2001; Carney 2007 7; De Koning 20 000; Feuer 200 04; Grivegnee 2001; 2 Habbema 2006; Mandelblattt 2003; Prevost 2000; 2 auch 2000, Xu 200 0062-76. Rautenstra

2.2.4. Selected 2 d studies 2 2.2.4.1. The CISNET C Project The Cancer Interrvention and Surrveillance Modelin T ng Network (CIS SNET) (http://cisnet.cance er.gov) is a con nsortium of National Cancer Ins stitute ose focus is mo odeling the impa act of (NCI)-sponsored investigators who c cancer control inte erventions on population trends in incidence and mo ortality fo or breast cancer. These models arre also used to prroject future trends s and to o help determine optimal cance er control strateg gies40. Seven grroups d developed their own o breast cancer models spann ning a wide rang ge of m modeling philosop phies: The Univerrsity of Texas M.. D. Anderson Ca ancer C Center model37, University U of Wisc consin model, Ge eorgetown47, Erasmus 5 44 (MISCAN) model57 , Dana-Farber model m Universityy of Rochester mo odel43 51 a Stanford model ). and T The seven models were first used to assess the relative and abs solute c contributions of screening mammo ography and adju uvant treatment to the re eduction in breast-cancer mortaliity in the United States from 197 75 to 77 2 2000 . Mandelbla att et all48 used 6 of those CISNET models to prrovide e estimates of pote ential benefits an nd harms of mam mmography screening u under different scrreening schedules s. One of the 7 mo odels, the Univers sity of

32


Texas M. D. Anderson A Cancer Center model37 was not used as s it was purely descriptive. The models we ere developed byy different groups but not indepe endently, they were com mpared, discusse ed and adapted during the deve elopment process, they also a used a comm mon set of variab bles and inputs, based on US datasets BCSC B (Breast Ca ancer Surveillanc ce Consortium), SEER S 9 (Surveillance, epidemiology e and d end results), Co onnecticut Tumorr registry and the Berkele ey mortality Datab base. A detailed dis scussion of each h of this models s can be found d in the publications and d on the CISNET website, we will not n discuss each model m in detail, but sum mmarize the poole ed comparison off Mandelblatt et al. a 48 and discuss the ma ain limitations an nd implications fo or our research question. q The models es stimated a large e number of sce enarios, but we will w only present the re esults of the partt relevant to ourr research questtion, the comparison of a screening pollicy screening ag ge 50-69 to a sc creening g age 50-74. policy screening Feuer et al.40 identifies two d dimensions to ch haracterize the types t of surveillance mo odels used here. The first dimen nsion incorporate es micro simulation mod dels at one end o of the spectrum, where w individuals are run through the model one at a tiime, where at each transition a random dividual life histo ories are genera ated, to number is generated and ind mechanistic orr analytic modells, where a sett of analytically derived equations desc cribe the relation nships between key k health states s and/or tumor growth and a metastasis. T The University off Texas M. D. Anderson A Cancer Centerr, University of Wisconsin, Geo orgetown, and Erasmus E models could be characterized as micro simula ation models; the e Danac be characte erized as analytic c; and the remain ning two Farber model could models (University of Rocheste er and Stanford)) could be descrribed as d dimension off model having some aspects of each. The second n runs from bio ologic, where th he model goes beyond characterization observable qua antities to model tthe underlying dis sease onset, grow wth, and progression of disease, to epid demiologic, wherre only a portion n of the ually the observab ble portion). disease process is modeled (usu art with estimatess of breast cance er incidence and mortality m The models sta trends without screening and ttreatment and th hen look at the effect e of a improvementss in survival assoc ciated with treatm ment. screening use and

KCE Reportt 176

Breast cancer is assumed to ha B ave a preclinical,, screening-detec ctable p period (sojourn time) and a clinical detection po oint. On the bas sis of m mammography se ensitivity (or thresholds of detection n), screening iden ntifies d disease in the prreclinical screenin ng-detection perio od and results in the id dentification of ea arlier-stage or smaller tumors than might be identifie ed by c clinical detection, resulting in redu uction in breast ccancer mortality. Age, e estrogen receptor status, and tumor size– or stage–sspecific treatment have in ndependent effec cts on mortality. Women W can die o of breast cancer or of o other causes. as mentioned before e, the 6 models use a common set s of a age-specific varia ables for breast cancer incidence e, mammography y test c characteristics, tre eatment algorithm ms and effects, a and non-breast ca ancer c competing causes s of death. On the other hand, unob bserved variables such a preclinical dete as ectable times (sojourn time), lead time, dwell time within w s stages of disease e, were in these models estimated d intermediate ou utputs th hat followed from the model structture and assumpttions concerning tumor t g growth. T The stage distribu utions in unscree ened versus scree ened women in these t m models were also o intermediate outcomes, this in ccontrast to some other m models that use th his observable va ariable as input. A As end output from m the m model reductions in mortality, life ye ears gained were e calculated, no QALYs Q w were used. The ha armful effects fals se positive mamm mograms, unnece essary b biopsies and overr diagnosis follow wed from the model, also here no direct o observed input wa as used, no attempt was made to q quantify those harrms in te erms of QALYs. Morbidity M associa ated with surgery for screening-detected d disease or decre ements in quality y of life associatted with false-po ositive re esults living with h earlier knowle edge of a cance er diagnosis or over d diagnosis was nott considered, whic ch makes the mod dels less useful fo or our p purposes. T Table 2.4 gives the results of the e different modelss in terms of mo ortality re eduction and yea ars of life gained for f the different m models. Gains are fairly limited and there is some variabilitty between mode els, with number years g gained per 1000 women screened d ranging from 9 to 17 and numb ber of d deaths averted ran nging from 4 to 6. T This class of mode els relies heavily on o unobservable vvariables, and as most m models are indiv vidual bases the ey are not alwa ays very transpa arent. In ndependent validation was made difficult because results from trials s and

KCE Report 176 6


the main US breast cancer rregistries were used u to parameterize or m Model outp puts are similar to o the results from m RCT’s calibrate the model. and some observational studiess, but this does not say much ab bout the dies were partly used to validity of the model as data from those stud odel. calibrate the mo Table 2.4: res sults of the diifferent models in terms of mortality m reduction and years of life ga ained per 1000 women w screened d for the els different mode Model Mortality (specific) re eduction over the whole period in % Screening in agegroup 50-69 Screening in agegroup 50-74 eduction screening in Incremental mortality re agegroup 50-74 compa ared to screening in agegroup 50-69 p 1000 women Years of life Gained per screened Screening in agegroup 50-69 Screening in agegroup 50-74 Incremental years of liffe gained screening in agegroup 50-74 compa ared to screening in agegroup 50-69 Incremental days of liife gained per women screened p 50-74 compared to Screening in agegroup screening in agegroup 50-69 women screened

D

E

G

M

S

W

16 22

23 27

17 21

16 21

15 20

23 28

6

4

4

5

5

5

88 106

107 116

111 128

82 96

99 121

84 95

18

9

17

14

22

11

women screened for a biannual scrreening in the age w e group 50-74, with an in ncremental beneffit for biannual screening s 50- 74 4 of 1.7% in term ms of m mortality and 2 liffe years gained per p 1000 women screened. As au uthors h had no choice th han to use US data for most ke ey variables one e can q question in what degree this can really be called an adaptation to the C Catalan context. Carles C et al, 2011 138 finally used th he results of Rue et al 58 a Vilaprinyo et al and a to do a cost effectiveness e analysis, including QA ALYs. T They found 3990 life years gained d for a cohort of 100 000 women for a b biannual screening g in the age group 50-74, with an incremental bene efit for b biannual screening 50- 74 of 299 life years gained d per 100 000 wo omen. T They found 3891 QALYs gained per 100 000 wo omen screened with w a b biannual screening g in the age group 50-74, with an incremental bene efit for b biannual screening 50- 74 of 277 life years gained d per 100 000 wo omen c compared to a sch hedule 50-69. The ey did not report tthe QALYs gained d with e extending the scrreening to 50-74 from 50 -69, ass it was dominate ed by s screening from 45 5- 69, but reporte ed that 186 QAL LYs per 100 000 were g gained by extendin ng the screening to 45-74 from 45 -69. Interestingly, they d did not incorpora ate the results of Vilaprinyo ett al,200958 into their c calculations, but used u US survivall data. They did not take into account o over diagnosis.

2 2.2.4.2. 6,6

3,3

6,2

5,1

8,0

4,0

Model group abb breviations: D _ Dan na-Farber Cancer In nstitute; E _ Erasmu us Medical Center; G _ Georgetown Un niversity; M _ M.D. Anderson A Cancer Center; C S _Stanford Univerrsity; W _ Universityy of Wisconsin/Harv vard

Stout et al 200 0656 used the Wissconsin model to o do a cost effec ctiveness analysis, includ ding the use of QA ALYs, but compa arisons of the age e groups 50-74 with age groups 50 - 69 were not made. Rue et al.55 ad dapted de Dana-F Farber Cancer Institute model of Lee L and Zeelen44 to datta in Catalonia. B Because there wa as insufficient info ormation on Catalan surv vival they combin ned the survival da ata from the SEE ER in the US with Catalan data in a prrevious publicatio on of Vilaprinyo, 200958. milar to the ones Lee & Zeelen originally o Obtained results were very sim ality reduction of 21% and 131 life e years gained per p 1000 found, a morta

33

Modells not related or not using CISNE ET methodology y

3 78 Carter et al, 200539, C developed a micro simulation model based on tumor t g growth using main nly SEER data. Th he model lacks crredibility though mainly m b because of unrealistic assumptions s concerning stag ge specific surviva al, as th hey assume a fix xed survival of 2 years y for stage 4 and complete cure for s stages 1, 2 and 3. This leads to con nsiderably higher years of life gaine ed for s screening than otther models but is in absolute con ntradiction to wha at we k know about stage specific survival. R Rojnik et al, 2008 produced a time dependent d Marko ov model with 4 stages, D DCIS, local, regio onal and distant. Overall model structure was desc cribed b details on how but w the model was parameterized p are e lacking so we ca annot ju udge how this wa as done or if ass sumptions were rreasonable. They y only re eport ICERs so we w have no inform mation on assumed gains in Life Years Y G Gained and QALY Ys.

34


Neeser et al developed d a sim mple Markov mod del comparing orrganizes screening with a coverage of 70% with opporttunistic screening g with a 0%. They assumed that the orga anized screening reduces coverage of 20 breast cancer mortality m with 15% % based on the IARC handbook, but it is unclear how th hey come to thiss figure as IARC C postulates a re eduction ranging from 5 to 20%. They ca alculated the yea ars of life gained for a 10 ng beginning at 70 (they evaluatted other schedu ules not years screenin relevant for ou ur research quesstion as well. They found that orrganized screening would save 41 lives p per 100 000 and add 0.008 life ye ears (2.9 men screened for 10 years. The model m is somewha at overly days) per wom simplistic by not n taking into account lead time e but applying assumed a reductions imm mediately. No QA ALYs were used and effects on morbidity m was not taken into account. Rauner et al, 2010 2 developed a an ant colonizatio on optimization model but only evaluated the effect of scrreening amongst women 50-70 and a their ental model is nott useful for our pu urposes. It is also o unclear rather experime how they actually modeled stage e specific survival.. 46 Mahnken et al,, 2008 develope ed a method to adjust a for lead tim me bias, length bias and d over-detection and applied this to SEER data, but provided p only adjusted Hazard H ratio’s. Rijnsburger et al, 200453 use ed the MISCAN micro-simulation n model t Rotterdam57 (see above) to replicate r the data a of the developed by the Canadian CNBSS-2 trial on brea ast cancer screen ning among women aged ur purposes. 50–59, so their findings are not rreally useful for ou 36 2 constructe ed a Markov mo odel for two hypothetical Barratt et al 2005 cohorts, with one o cohort wome en undergoing bie ennial screening and the other not, assuming 100% particcipation. Within th his model, they ev valuated o women over 70 0 years old underg going 10 years of biennial the outcomes of screening. The ey assume a 37% % mortality reduc ction, adjusting the t 25% reduction from for non compliance, and assum me that benefit accrues ximal level over first five years afte er starting screen ning and linearly to max that benefit de eclines linearly to o nothing over five f years after stopping s screening. For women who conttinue screening fo or 10 years after the age wer women per thousand die from breast cancer than in of 70s, two few women who sto op screening (sixx v eight deaths from f breast canc cer). The number of diagnoses of breast ccancer in screened women is about 41 and

KCE Reportt 176

he number in uns screened women about 26. assum ming a risk reductiion of th 50% brings the nu 5 umber of deaths in the screened g group down 6.2 to o 5.1. T This simple mode el has the advanta age of transparen ncy, but does nott take in nto account the efffects of lead time e and stage-shifts on morbidity.

2 2.2.5.

Conclusiion

Models described are give useful in M nsights and eleme ents but it is diffic cult to a adapt them to the Belgian situation n as we do not ha ave the necessary y data to o parameterize th hem. The CISNET T models give a m modest gain in ye ear of life between 9 an 22 2 years per 1000 0 women screene ed.

2 2.3. Review of o quality of life studies Because breast cancer B c screening g programs are expected to hav ve an im mpact on the qu uality of life (QoL L) of the patientss, models with a oned dimensional health h-outcome measu ure in terms of su urvival are not en nough in nformative. It is important to take e into account all the multidimens sional h health outcomes in the assessmen nt of breast cance er screening progrrams. T value these multidimensional ou To utcomes into a single measure, qu ualitya adjusted life-year (QALY) must be b used. QALYs permit to adjus st the e expected length of life by the health-related q quality of life. These T a adjustments are made m using utilitie es derived from iindividuals’ preferrence fo or different health h states. D Determination of utility values, needed for the ccalculation of QA ALYs, re equires two steps s: 1. The health state description. According to the e pharmaco-econ nomic ealth Care Know wledge Centre (K KCE), guidelines off the Belgian He s should be des scribed on a sta andardized descrriptive health states system. Ideallly, the descriptio on should be don ne by Belgian pa atients using a gene eric descriptive system, s such as the EQ-5D. If health h states descrriptions from Belgian B patients are not available, descriptions frrom similar patien nts in other countrries may be used7 79.

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2.

The valuattion of these he ealth states. Acco ording to the pharmacoeconomic guidelines g of the K KCE, health state e values should be e valued on a 0 (=v value for death) to o 1 (=value for perfect p health) sca ale by a representa ative sample of th he general public c. Ideally, they sh hould be valued by the Belgian popu ulation but if no original Belgian data d are m other countrie es can be use ed and collected, valuations from 79. discussed7 In this section, the availability a and the quality of o published utility y values ase due to breas st cancer (screen ning and describing the burden of disea ssessed. treatment) is as

2.3.1. Metho ods 2.3.1.1. Lite erature search sttrategy Electronic data abases were con nsulted for origin nal publications on o utility estimates for different health states associatted with breast cancer matic searches were w carried out up u to the screening and treatment. System er 2011 in the fo ollowing databas ses: Medline (via a OVID), end of Octobe Embase (via Embase.com), HTA A and EED (via CRD NHS) and Psycinfo P (via OVID). g various qualifierrs for “quality of life” were used as Subject Searches using heading or tex xt word. See app pendix 3.1 for an n overview of the e search strategies and terms t used.

2.3.1.2.

Sellection criteria

Identified refere ences were assesssed against pre--defined selection n criteria (in terms of pop pulation, intervention, outcome and d design –Table 2.5) 2 in a two-step proced dure: initial assesssment of the title e, abstract and ke eywords; followed by full-text assessmen nt of the selecte ed references. When W no a and the e citation was un nclear or ambiguo ous, the abstract was available citation was assessed based on n keywords and fu ull-text. Reference e lists of udies were scrutin nized for additiona al relevant citation ns. the selected stu

35

T Table 2.5: Article selection criteriia I Inclusion criteria a

Exclus sion criteria

P Population

Screened or treatted S p patients for breast c cancer, with a Caucasian o origin and withoutt high r risk factors

diseases, non Other d Caucasian, high risk wo omen

In ntervention

Any intervention relevant A r t the Belgian setttings to

Interve entions not used in n Belgium m

O Outcome

Unique QoL weights U a allowing to derive QALYs ( (=utilities)

Multi-d dimension HRQoL L scoress, DALYs, HYEs, …

D Design

Direct (TTO, PTO D O, SG) o indirect (EQ-5D or D, SF6 HUI, QWB) va 6D, aluation m methods in primary s studies

Letterss, secondary studiies, CUA w with QALYs derive ed from th he literature, … Direct valuations using VAS V (not recommended in the mic KCE pharmaco-econom guidelines)79.

QoL: Quality of Life. QALY: Quality adju Q usted life year. HRQ QoL: Health-Related d Q Quality of Life. DALY Y: Disability-Adjuste ed Life-Years. HYE: healthy-yearse equivalent; TTO: Tim me-Trade-Off. PTO:: Person Trade-Off. SG: Standard-Gam mble. H HUI: Health Utility In ndex. QWB: Quality of Well Being scale e. CUA: cost-utility a analysis. VAS: visua al analogue scale

36


2.3.1.3.

Sellection process

The flowchart of o the selection p process is presen nted in appendix 3.2. 3 The searches on th he databases retu urned 524 citation ns. After exclusion n of 172 duplicates, 352 2 unique citationss were left (see also a appendix 3.2 2). Hand searching allow wed us to identifyy 3 additional cita ations. Two-hund dred and ninety (290) refferences were discarded based on title and abstract, leaving 65 references for f full-text evaluation. Another 49 references r were excluded e at this stage, mostly m because off the unmet desig gn and population criteria. Overall, we sele ected 16 primary sstudies (see appe endix 3.2).

2.3.2.

Resullts

A summary of the t selected studiies can be found in appendix 3.3. It I should be noted that this summary on nly report metho ods used to deriv ve utility w not values and their results. If other parameters were measured, they were reported in the summary. o utilities was don ne according to the e following stages s: The selection of •

Determinattion of health state es for which utilitie es were needed

•

Selection of o utilities Selection of o a basecase stud dy Selection of o other studies

•

Pooling of selected utilities a and calculation of percentage changes

2.3.2.1.

Dettermination of he ealth states

Health states fo or which utility valu ues are needed are a listed in Figure e 2.1. It should be no oted that this fig gure is a schema atic representation n of the reflection proce ess but not the model itself (de escribed in section 3.2).

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KCE Report 176 6


37

Figure 2.1: Hea alth states for wh hich utilities are needed (reflection process)

Before e screening

Short term m impact of the sc reening

After scre eening (First year) y

After screening (Folllowing years)

Women ag ged ≥ 70 years

Negative e results

Women aged ≥ 70 years

Women aged ≥ 70 years

Positive results False positive p

Non me etastatic

No on metastatic

Breast canccer stage I

Breastt cancer stage I

Breast cance er stage II

Breast cancer stage II

Breast cance er stage III

Breast cancer stage III

Metasstatic

Metastatic

Breast cance er stage IV

Breast cancer stage IV

True po ositive

38

2.3.2.2.


Sellection of utilitiess

To select utility values, we first ttried to find Belgia an data as recom mmended co-economic guid delines of the KCE E79. However, no Belgian by the pharmac data could be fo ound. Then, we tried to find the mosst complete study y which best fit with w our m was to avoid as much as possible the use of multiple model. The aim instruments and d multiple popula ations to derive them. Indeed, acco ording to the pharmaco-e economic guidelin nes of the KCE, it is strongly recom mmended to use the sam me descriptive insstrument and the e same set of va alues for quality of life we eights coming from m different studies s79. However, no sttudy assessing all of the heath sta ates described in n section 2.3.2.1 with the e same design w was found. We th herefore tried to find the study with the greatest g number o of health states co orresponding to ou ur model and to use it at the starting point of the selection process. p Selection of th he base case study We found only y one study haviing assessed utility values for bo oth nonmetastatic and metastatic patien nts, i.e. the study of o Lidgren et al80. We had strument the chance that this study alsso used the bettter available ins he pharmaco-econ nomic guidelines of the KCE, i.e. the EQaccording to th 5D79. This study y was therefore th he starting point of our selection pro ocess. Utility values in i the study of Lidgren et al.80 were derived frrom two methods, i.e. a direct valuatio on method (i.e. the time-trade-offf (TTO) S patients and an indirect valuation v method using a technique) by Swedish generic instrum ment (i.e. the E EQ-5D instrumen nt). Because pharmacoeconomic guide elines of the KCE E recommend the e use of the EQ-5 5D, only these valuations were retained (i.e. utility values from f EQ-5D and not from ents and TTO). In this sttudy, health statess were described by Swedish patie valued using UK K tariffs (because e no tariffs from the Swedish popula ation are available). Hea alth states descriptions can be fo ound in Table 2.6 6. Utility values for non-metastatic patients in the first year y (i.e. the yea ar of the ars as well as utility values for metastatic treatment) and the following yea scribed in Table 2 2.8. patients are des This study had the following limittations:

KCE Reportt 176

•

Utility values were measuring g during out-patie ent visits at a breast b cancer outpattient clinic (Karolinska University hospital), implying the following limita ations: Utility values for f non-metastatic c patients did not fully take into account the shortt term impact of surgery. s Howeverr, on an annual basis, b this shortt term impact was expected to co over a limited leng gth of time and was therefore nott included in the m model. Utility values for metastatic patients p did not represent patien nts in hat these utility values v palliative care. It was therrefore assumed th ected the quality of life of metasta atic patients durin ng the only refle first year of diagnosis. The short term m impact of diagn nosis is also not ffully taken into account (not meas sured at the mom ment of the diagno osis), even if autho ors of this study y reported that this s impact was expected to be includ ded in the valua ation (measured th he year of diagnossis).

•

Non-metastattic patients were divided d in only tw wo groups, i.e. the e first year of diagnosis and the follo owing years. It w was therefore assu umed emained constant. This that after the year of treatment, utility values re i supported by an US study where no significant assumption is difference in utility u values (from m EQ-5D using U US tariffs) was fou und at year 5, 10 and d 1581. This US sttudy is described in the appendix 3.3.

•

It should also be noted that utility estimates for n non metastatic pa atients ast cancer in the first year of diag gnosis) and meta astatic (primary brea patients werre similar (0.696 and 0.685 respectivelly). This inconstistency y may be due to th he following reaso ons: Metastatic patients p only inc clude patients going in out-patient consultations (best cases). Generic instru uments such as the EQ-5D are lesss sensitive to ca apture relevant changes in healtth in a specific d disease than dise easei How wever, diease-spe ecific instruments s can specific instruments. only be used u if validated mapping m functionss to derive utilities s from these instruments are avaiilable, which was not the case79.

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Table 2.6: Health states descriptions for the study of Lidgren et e al. Primary b breast cancer (year 0-1)

Patients who had prima ary diagnosis brreast of within 1 year or le ess prior to answe ering the cancer w question nnaire, no recurre ence and no metastatic disease

Recurrence (y year 01)

Patients who had at least one recurrenc ce (locoeral) within 1 year or less regional and/or contra-late prior to answering the questionnaire, and no metastattic disease.

Primary b breast cancer and recurrence following yearrs

d with a primary Patients who had been diagnosed ancer or their last recurrence more e than 1 breast ca year prio or to answering th he questionnaire,, and no metastattic disease.

Metastatic patients

Patients who had metasta atic disease

39

As showed in this A s table, the description include the following stage: being in nvited for screen ning, having a brreast screen, waiiting for results, being re ecalled for furth her examinations, having furthe er examinations and o obtention of a diagnosis, i.e. no o evidence of brreast cancer. Fo or the a assessment, only three of the five EQ-5D E dimensions were used, i.e. usual a activity; pain/disco omfort; and anxietty/distress and it was assumed tha at the re emaining two dimensions (i.e. mobility m and ability of self-care) were u unaffected. The quality q of life effec cts associated with true negatives s and fa alse positives las sted 12 months while true positivve and false neg gative w were measured for f the remaining life expectanccy. These values s can th herefore not be used u to measure the t short term im mpact of screening g. We d decided to make th he following assumptions: •

True negativ ve patients have e utility values e equal to the ge eneral population.

•

m impact of positive results at scre eening is measure ed by The short term the percentag ge change betwee en true negative and false positive.

Selection of otther studies

•

For other health states, we trried to find stud dies having used d similar ation. The study of o Lidgren et al.80 allowed instruments for the same popula ng utility values for the general Swedish S us to identify a study assessin population strattified by age and gender using the same instrument (EQ-5D with UK tariffs),, i.e. the study of Burström et al.82 These utility valu ues were therefore used for women aged 7 70 and over (see Table 2.8). For the short term t impact of p positive results affter screening, on ne study using the EQ-5 5D instrument wa as identified (Gerard et al.)83. Th his study assessed utility y values for false positive, true positive, false nega ative and true negative. Health H states were e described by the UK population (and not the Swedish po opulation) but UK K tariffs were used d to valuate these health states (as in the other selectted studies). A description d of the “false s given in Table 2 2.7. positive” state is

•

This impact is s present until the diagnosis, i.e. on n average 45 days s after screening acc cording to IMA da ata. After, either vvaluations of Burs ström et al.82 (generral population for false positive) orr valuations of Lid dgren et al.80 (non metastatic m or mettastatic disease yyear 1 for true po ostive) were used. U Utility values for fa alse positive and true t negative can be found in Table e 2.8. Itt should be noted that the study of Domeyer et al.84 described in app pendix 3 assessed the short term impact of biopsy. How 3.3 wever, to avoid model m c complexity and be ecause the biopsy y is included in the e description of a “false p positive” in the stu udy of Gerard et al. a 83, we decided tto not take the stu udy of 84 D Domeyer et al. in nto account. C Concerning the ev volution of utility values for patientss with metastatic breast b c cancer in the long term, no study wa as found.

40


KCE Reportt 176

Table 2.7: Description of a “fallse positive” statte (Gerard et al)83 •

S She is invited by letter for routine breast b screening.

•

T The appointment is about 2 weeks from receiving the e invitation.

•

T The visit at the bre east screening ce entre takes about half an hour, whic ch may include wa aiting time.

•

A female radiogra apher asks about any a symptoms or history of breast disease and expla ains what will hap ppen.

•

T To take the X-ray y she is asked to undress to the waist. w Each breast is placed in turn n between two sp pecial X-ray plates s and ccompressed to ge et the best possiblle picture.

•

S She is asked by le etter to go to the breast b screening centre c the followin ng week.

•

O Other tests are ne eeded because the breast X-ray res sult is not clear.

•

T This visit may take e up to half a day.

•

T The breast X-ray is repeated.

•

T The doctor examines her breasts.

•

T The doctor may carry out an ultraso ound examination n.

•

F Fluid from the affe ected area is take en for laboratory analysis a using a fin ne needle to do th his her breast mayy again be compre essed b between the X-ray y plates.

The results of the tests are ready within the week

•

T The tests show no o evidence of brea ast cancer.

Quality of life effects e of routine breast ort term) screening (sho

QoL of some wom men is affected by y the experience of routine breast screening and brreast cancer diagnosis. The effects s may The Q continue for some time e.

Receiving invitation

•

M Most women are pleased to receive e the invitation.

•

S Some women are e made nervous, anxious a or depressed, and are worrried about having breast cancer.

•

M Most women carry y on with their usu ual activities and interests. i

•

S Some women are e anxious and dep pressed, unable to o concentrate, sleep badly and are moody and irritab ble. They are unable to ccarry on with theirr usual activities and a interests.

•

P Personal and sexual relationships may m be affected.

Routine breastt screen

Further tests

the

Waiting for th he day of the appointme ent

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At the breast screening s clinic

Waiting for the e results

41

•

M Most women are nervous, but are not n anxious or dep pressed.

•

M Most women are not embarrassed by the screening procedure.

•

M Most women are not unduly worried d about breast ca ancer developing.

•

M Most women find the breast X-ray is i uncomfortable and a slightly painfu ul, but this is shortt lived.

•

S Some women find d the breast X-ray y very uncomfortab ble and painful.

•

M Most women carry y on with their usu ual activities and interests. i

•

S Some women are e anxious and dep pressed, un-able to concentrate, sleep badly and arre moody and irrittable. They are unable tto carry on with th heir usual activities s and interests.

• P Personal and sexual relationships of o some women may m be affected. If reccalled for further te ests:

Clear results after the test

•

M Most women are very v anxious at be eing recalled for further tests.

•

O One of the tests, where w the doctor removes fluid from m the affected are ea, is painful.

•

M Most women are reassured by the clear results.

•

S Some women rem main anxious for up u to a year before e they are back to o their usual self.

Table 2.8: Description of the se elected utilities Author (year)

Instrument

P Population for he ealth state d description

Lidgren et al. (2007)80

EQ-5D

S Sweden patients ((Mean age: see health states)

Burström et al. (2001)82

EQ-5D

Gerard et al. (1999)83

EQ-5D

Po opulation for valu uation

Hea alth state

Mean valu ue

UK K tariffs (general population) p

Prim mary breast cance er (Year 0-1); Mea an age: 56

0.696


Brea ast cancer (follow wing years); Mean age: 58

0.779


Meta astatic patients; Mean M age 56

0.685

Wom men aged 50-59

0.833

Wom men aged 70-79

0.792

Wom men aged 80-88

0.740

True e negative

0.940

S Sweden patients ((Mean age: see health states)


W Women from UK aged a 40-64 yyears (eligible for screening)

K tariffs (general population) p UK

42

2.3.2.3.


Poo oling of selected d studies and callculation of percentage cha anges

A summary of selected utilities and of calculation of percentage changes c n Figure 2.2. The e utility values of the study of Burs ström et can be found in al.82 were chosen as the initial values of the mode el (first state of th he model ding to women ag ge. Then, the perrcentage (A)). These values varied accord e to these valuess was applied. It was assumed that these change relative percentage cha anges did not varyy according to the women age (no data). d hort term impact of the screening The next stage e concerns the sh g. It was assumed that utility u values for ttrue negative wom men were equal to utility values in the general g populatio on (A). Then, the percentage decrrease in utilities betwee en true negative women and false positive wom men was calculated, i.e. -16% (B). Initia al values were thus t maintained for true en and decreased d by 16% for wom men with a positiv ve result negative wome after screening (false or true possitive). As mention ned in the section 0, these m for 45 days. utilities will be maintained

KCE Reportt 176

For the first year of screening, wo F omen without bre east cancer had utility v values equal to th he general popula ation (A). For true e positive, utility values v o the study of Lid of dgren et al. were used.80 To make e the link betwee en the s study of Lidgren et al.80 and the study of Burström m et al.82, percentage c changes between values for the sa ame population w were used, i.e. Sw wedish w women aged 50-5 59 (and UK tariffs s). Utility values w were therefore red duced b 16% ((0.696-0..833)/0.833) for non by n metastatic pa atients (C) and by y 18% ((0.685-0.833)/0.833) for metastatic c patients (E). F the next yearrs, people from the For t general popu ulation who developed n non-metastatic or metastatic breas st cancer had utility values reduce ed by 16% (C) and 18% % (E) respectively y (as calculated a above). Non-meta astatic p patients who stay yed in this stag ge had their utiliity decreased by y 6% c compared to the general g population ((0.779-0.833)/0 0.833) and maintained th he years after (D D). Metastatic patients maintained their utility until death d (G).

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43

Figure 2.2: Perrcentage change e in utilities Before e screening

Short term m impact of the screeniing (45 days)

After screening A (First year)

After screeniing (Following yea ars)

Women age ed = 70 years

True negative

Wome en aged = 70 years

Women aged = 7 70 years

A

A

A

A

N metastatic Non

Non metasta atic

Brea ast cancer stage I

Breast cancer sstage I

Brea ast cancer stage III

Breast cancer sttage II

Brea ast cancer stage III

Breast cancer sttage III

Positive P results False positive True positive B

C

C

D

Metastatic Brea ast cancer stage IV V F

E

Metastaticc Breast cancer sttage IV F

G

44


2.3.3.

Discu ussion

To include the quality of life im mpact of screenin ng in the analysiis, utility h health state of tthe model had to be identified. The e aim of values for each this chapter wa as therefore to select these values. The method wa as based on the KCE pha armaco-economicc guidelines79. We e tried to avoid the use of multiple instrum ments and multiple valuations and focused on utility y values derived from the e EQ-5D instrume ent. •

The analys sis had the following limitations:

•

No Belgian n data were availa able and a transfferability analysis was not possible (n no access to prim mary data). Even ifi we expected th hat using UK tariffs instead of Belgia an valuations wo ould not greatly in nfluence be interesting for future models. results, Belgian data would b

•

t impact of su urgery and of diag gnosis was not ta aken into The short term account be ecause no valid da ata were available e.

•

Even if the e EQ-5D is one o of the best availa able instrument to o assess these utilitiies (according to the KCE pharma aco-economic guid delines), this instrum ment is less sen nsitive than disea ase specific instrruments. Consequen ntly, it can be exp pected that the im mpact of some co onditions such as a mastectomy (p partial or total) would have bee en more important if a disease sp pecific instrumen nt instead of a generic nsitivity could exp plain the instrument had been used. This lack of sen ntage change be etween patients with breast cancer and low percen women in the general pop pulation or between metastatic and a non q of life from disease metastatic patients. The asssessment of the quality struments was ne evertheless not investigated in this chapter specific ins because th hese instruments d do not permit to derive QALYs.

•

Finally, the e review of the literature showed d an important variability v between re eported utility estimates for breast cancer health sta ates (see appendix 3.3), 3 revealing a high level of uncertainty u aroun nd these parameters s. Because of th his uncertainty, a sensitivity analysis on these parameters should be e done in the chap pter on model resu ults.

KCE Reportt 176

3 DECISIO 3. ON ANALY YSIS To quantify whatt the implications T s of our findingss are on the Be elgian s situation we cons structed a decisio on analysis model using two diffferent a approaches. For the first simple approach, we ap pplied data from IMA, c cancer registry an nd data from the literature l on the B Belgian life tables s (see b below). For the se econd, we constrructed a simple ttime dependent cohort c w annual cycles with s. W consider perfo We orming one Belgia an decision analyysis a better apprroach th han trying to ada apt the models discussed d in cha apter 2 to the Be elgian s situation. Indeed, Belgian data nee eded to paramete erize these modells are n available and not d we would merely reproduce tthe already published fiindings of these models, m as we wo ould be obliged to o use the same (m mainly U data. US) W look at the effe We ect of introducing mammography sscreening in addition to th he currently existing situation with the opportunistic screening going on at th he current level. This T has the adva antage that we ca an use Belgian da ata as b baseline without having h to modify then, as this can only be done making u of an addition use nal number of no on verifiable assu umptions. We des scribe h here: •

a used in this deciision analysis; Available data

•

Additional lite erature review foc cused on qualityy of life related to the screening and d to the breast can ncer as such;

•

The model us sed for this decisio on analysis.

KCE Report 176 6


3.1. Data so ources Belgian life tab ble (2009) Overall surviva al was taken fro om the Belgian life table of 200 09 from be.STAT (http:///statbel.fgov.be) Belgian Cance er Registry (BCR R) The Belgian Cancer C Registry F Foundation is an n public institution which collects data concerning c new ccancer cases in Belgium and ma akes up statistics from these data (http://w www.kankerregistter.org/). Belgian organized screening As recommend ded by European Commission, Be elgium started a national organized scree ening programme e. The target age groups as defined by the program are wo omen aged 50 to 69 years. Belgian n breast cancer sc creening programs a are organized d by: Brrumammo (Bruxelles, http://www.brum mammo.be/), Cen ntre Communauta aire de Référence e pour le dépistage des s cancers (CCR Ref: http://www.c ccref.org/) (Comm munauté Française) and d BorstKankerOp psporing (BKO) (Vlaamse ( Gemee enschap: http://www.zorg g-en-gezondheid.b be/). Intermutualistiic Agency (IMA) The Intermutua alistic Agency (IMA A) centralises data coming from all Belgian sickness funds s. IMA compiled and published several reports on the national screen ning program con ntaining data on the t target age grroups as defined by the e program (50-6 69 years). IMA complemented this with information on persons outside e the target age-group, with a particular p t used, delayys between scree ening tests and possible focus on the tests confirmation an nd treatments follo owing testing (http p://www.nic-ima.be e/). Dutch Nation nal Evaluation Team for Bre east cancer sc creening (DNETB)85. The Dutch National Evaluatio on Team for Breast B cancer sc creening eport with their findings covering g the period 1990-2007 published a re containing inforrmation on age sspecific stage disttributions in the screened s population.

45

SEER database S T Surveillance, Epidemiology, an The nd End Results (S SEER) Program of o the N National Cancer In nstitute works to provide informatio on on cancer stattistics in n an effort to red duce the burden of cancer among the U.S. Population (http://seer.cancerr.gov/). SEER colllects data on canccer cases from va arious lo ocations and sourrces throughout th he United States. Data collection began b in n 1973. As they used an outdated distribution we could not incorp porate th hese in the model.

3 3.2. Model de escription In n a first simple approach a we app plied the 22% redu uction in breast ca ancer m mortality caused by b screening com ming from RCT and its range, res sulting frrom the results of o the meta-anallysis of Gøtzsche e et al, 20084 on the B Belgian life table. We assume here e that the reductio on in women age ed 707 is similar to the 74 t reduction in other age group ps. We also ass sume, fo ollowing Barratt et e al 200536 that benefit accrues linearly to a ma aximal le evel over first five e years after startting screening and that benefit dec clines linearly to nothing g over five years s after stopping screening. Life years s saved can then be derived from th he life table. How wever, effects of harms h a effects on qua and ality of life resultin ng from earlier dia agnosis, over-diag gnosis a stage-shift is more difficult to assess and a in this ap pproach. Therefore e this a approach was onlly used for cross validation by com mparing it with a more c complex approach h that makes use of o the stage-shift caused by screen ning. T The second apprroach makes use e of the Belgian C Cancer Registry (BCR) d data on incidence e of invasive canc cer and DCIS forr the construction n of a tiime dependent state transition cohort model with annual cycles. T model compares 2 cohorts: The •

A cohort of women w starting at age 70 where screening is extend ded to the population n in the age group 70-74, where a part of the wo omen participates in n the screening an nd where a part o of the cancers is found f by screening,, depending on participation p rate and sensitivity of o the screening. Th here is a mix of sc creen detected an nd not screen detected cases (interva al cancers and cancers c amongstt unscreend wom mens). The screen detected d cancers will have a diffe erent stage distrib bution than the cancers not detected by b screening.

46


•

A cohort of o women starting at age 70 whe ere the screening is not extended beyond b the age off 69 years. For th his cohort all wom men have the stage distribution d of the non screened. All women are followed to death h. The cumulative number of life ye ears, the horts are number of QALYs and deaths to breast cancer of the two coh erall mortality is no ot compared as in n the end everybod dy dies. compared. Ove We assume tha at: •

Survival an nd quality of life of the women depe ends only on the stage of the tumor at the moment tthe tumor is dete ected and the age of the nd not on the pressence or absence of screening; women, an

•

All benefit of the screening rresults from the stage-shift, the diffferences stribution caused by the screening.. in stage-dis Harm caused by false positivves at the mome ent of the scree ening is s by asssuming 3 screening rounds with a 2 years accounted for separately, interval in the e participation women and apply ying recall rates s at the proportion wom men that are alive and without brea ast cancer at the moment the screening ro ound actually take es place. Figure 3.1 show ws the different ccompartments in the two cohorts and the transitions betw ween them. In the unscreen ned cohort, transiitions between co ompartments from m year to year are determ mined by: •

Incidence of o breast cancer;

•

Stage distrribution of unscree ened cancers;

•

Stage spec cific survival; and

• Age specific overall mortalityy due to other cau uses. On top of that, for f the cohort whe ere screening take es place, transition is also determined by some s aspects of tthe screening: •

Lead time as a part of the cancers will be found d earlier;

•

The propo ortion of cancers found by scree ening and proporrtion not found by sc creening and their respective stage e distributions.

KCE Reportt 176

As survival and quality of life depends on both age and time since A d diagnosis in the model, m a separate e compartment is made for each age a of d diagnosis and stage, and stage specific survivall is than applied d. As s screening is applie ed during 5 years and there is an a assumed lead time e of 2 y years (or 3 in sen nsitivity analysis) the number of co ompartments remained m manageable. T Transitions betwee en stages are nott included as stage es are assessed at a the m moment the diagn nosis is made folllowed by treatme ent. Even if the ca ancer e evolves after trea atment it does no ot necessarily go through the 4 stages a anymore.

KCE Report 176 6


47

Figure 3.1: Comparison of the two cohorts with h and without a screening s progra am

IInvasive cancer d detected by screeniing

Healthy women

iinterval cancer in s screened women

Invasive cancer in unscreened womeen Cohorrt with screeening

I II III IV I II III IV

All ccause deaths

I II III IV

DCIS

Co ohort w without screeening

Invasive cancer in unscreened womeen

Healthy women

I II III IV

DCIS All ccause deaths

48


Figure 3.2: Compartments in th he two cohorts and a the transition ns between them m

DCIS & over‐ d diagnosed Breast cancer stage I Breast cancer stage II Healthy women

Death Breast cancer stage III Breast cancer stage IV

KCE Reportt 176

KCE Report 176 6


3.3. Descrip ption of the parrameters 3.3.1.

Age specific s overall survival

Overall surviva al was taken fro om the Belgian life table of 200 09 from be.STAT (http:///statbel.fgov.be) after adjusting fo or breast cancer specific mortality based on data from the Belgian Cancer register. r

3.3.2.

Breas st cancer inciden nce

For the baseline e without screenin ng the BCR data on o incidence of DCIS D and the 4 stages for invasive for the age group 70-74 4 of the period 2004-2008 ere is some opporrtunistic screening g in that age grou up. From were used. The the IMA data we w infer that in Flanders the cov verage with at le east one mammography in the past 2 yea ars is 18% (for de etails see the KC CE report ps)2. Given that we can 172 on breastt cancer screening in risk group assume that an n important part o of this is also for diagnostic d and follows up purposes, so we w choose to use e data issued from m Flanders becau use they are less contam minated by opportu unistic screening. For the situatio on where screen ning takes place,, incidence in the 70-74 group will increa ase with a numbe er of cancers coming from two sourrces: •

Lead time, cancers that would have appeare ed later but are fou und now o lead time. This will lead to a co ompensatory decrease in because of number of cases in the folllowing years. The e moment and de egree of d on the a assumed lead tim me (see point 3.2 2.2). We this shift depends used 2 yea ars lead time in tthe baseline and 3 years in the se ensitivity analysis.

•

gnosis invasive cancer, we mod deled the over diagnosis Over diag based on the findings in th he literature as described d in the literature ove under 2.1.3.5.. We assume a ra ange of 2 to 30% for over review abo diagnosis excluding e DCIS.

•

Over diag gnosis DCIS, we e model the overr diagnosis of DC CIS in a different way: w we use the o observation that in Flanders the in ncidence DCIS per 100 1 000 is twice in the group 60-6 69 where screenin ng takes place com mpared to the age e-groups 70-74 and a 75-79 where e only a limited am mount of opportunistic screening takes place. Th his is in contrast with the Brussels ca apital region and Walloon W region where w the CIS is much less pronounced. So we e take as an estim mation of drop in DC

49

over diagnosis the difference in i DCIS incidence e in Flanders bettween ps 60-69 and 70--74, augmented b by 1.5 to adjust fo or the the age-group fact that scree ening coverage is only 60% as a prroxy for overdiagn nosed DCIS. This brrings us to an ove er diagnosis of DC CIS of 40 per 100 0 000 women per ye ear.

3 3.3.3.

Participa ation rate

W used a 70% pa We articipation (plaus sible range 60% to o 80%) as baselin ne.

3 3.3.4.

Proportio on of screen dettected breast ca ancers

The data of the Be T elgian screening program p show tha at in the age grou up 506 49% of the cas 69, ses are found by screening, and th he rest is either interval c cancer or not partticipating in the sc creening. Among the screened wo omen, 7 75% of the found cancers are scree en-detected and 2 25% is interval ca ancer. W used a proporrtion of cancers fo We ound among the w women participating in s screening of 70% (plausible range 60% 6 to 80%).

3 3.3.5.

Recall ra ate

We assume a rec W call rate of 3.5% % based on the d data from the Fle emish s screening program m concerning follo ow up rounds (ass the screening would w b an extension of the screening be g among women aged 50-69. Fo or the s sensitivity analysis s we used 2% in an a optimistic scen nario and 5 and 10 0% in th he more pessimistic scenario (10% recall rates are observed fo or the m moment in certain regions). A a baseline we assume a delay of 45 days, base As ed on IMA data, with w a p plausible range fo or the sensitivity analysis a of 36 and d 45 days (subtra acting a adding 20%). and T short term im The mpact of positive results r at screeniing were measure ed by th he percentage ch hange in utility va alues between trrue negative and false p positive results.

50

3.3.6.


Stage e distribution and d stage shift

We take estima ations of the stag ge distribution for breast cancer amongst a screened and unscreened u from the BCR data on o the Flanders and a data provided by the e Flemish screenin ng program. For the stage distribution d in the unscreened wom men, we can cons sider the stage distributio on amongst wom men in the group 70-74 7 in Flanders s for the years 2004 - 2008 a good esstimation. The stage shift will be e slightly d as there is som me opportunistic screening in tha at group underestimated going on, see above. a For stage distribution in the scre eened population, the base case es stimation e data from the D Dutch National Ev valuation Team fo or Breast is based on the cancer screenin ng report of 2009 9 (DNETB)85 who o provide data spe ecifically for the age group g 70-74 from 1998-2007. Although A using 2 stage distributions fro om different sourrces is a subopttimal way of mod deling a stage shift we think t this approxim mates best the Be elgian situation, as a we do not have date on screen detectted cancer in this s age group. We assume on of cases amon ng the non screen ned and interval cancer c to stage distributio be the same, ba ased on the data from the Flemish screening program. The Flemish screening s program provided data a on the stages among screen detecte ed cancers, interrval cancers and d cancers amongst non participants, co ollected amongstt women who ga ave their consen nt in the period 2001-2006. Stage distribu ution of interval ca ancers and cancer among s is very similar. non participants

KCE Reportt 176

Table 3.1: Stage distribution amo T ong screen dete ected breast can ncers, in nterval cancers and cancers among a non partticipants, age 50-69, 5 F Flemish screenin ng program 2001-2006. Screen n cancerrs

detected

In nterval cancers

Cancers amongst non participan nts

S Stage

n

%

n

%

n

%

I

2586

62.5%

62 24

41.5%

1454

41.8% %

III

1306

31.6%

65 56

43.6%

1460

42.0% %

IIII

232

5.6%

20 00

13.3%

493

14.2% %

IV V

15

0.4%

24 4

1.6%

71

2.0% %

T TOTAL

4139

100%

15 504

100%

3478

100% %

T This baseline stag ge shift we call Sce enario 1: Stage distribution S n of c cancers not foun nd by s screening B BCR data (Flemis sh p population,70-74y y, 20042 2008)

S Stage

% %

I II III IV

31.6 6% 42.3 3% 16.6 6% 9.5 5%

Sta age distribution of o can ncers found by scrreening Da ata of the DNETB B scrreening report 20 009

Sttage

%

I II III IV

80% % 18.7% 0.8% % 0.5% %

KCE Report 176 6


Important rem mark: It is importtant to note that this shift concerrns only screen detecte ed cancers and that in the cohort with screening interval cancers and nonparticipants n ke eep the stage distribution of can ncer not found by screening. In most casses this is around 50% but depends on the er values of the sccreening and varie es in time. other paramete For the sensitiv vity analysis we usse 2 supplementary scenario’s: As the stage distribution d from the Dutch National Evaluation Team T for Breast cancer screening s report o of 2009 may be more m favorable th han what can be achieved in the Belgian ccontext, we used as a an alternative scenario s bution for screen detected patients s of the age grou up 50-69 the stage-distrib from the Flemis sh cancer screenin ng program. This we call Sce enario 2: Stage distributtion of cancers not fo ound by screening BCR data (Flem mish population,70--74 years, 2004-2008)

Stage distribu ution of cancers found d by screening (Fle emish screening pro ogramme (50-69 years)

Stage

%

Stage

%

I II III IV

31.6% 3 4 42.3% 1 16.6% 9.5%

I II III IV

62 2.5% 31 1.6% 5 5.6% 0 0.4%

In a third scena ario we use a sligh htly different mode eling approach. Instead of usin ng stage distributtions amongst sc creened and uns screened women, we ass sume that introducing screening in the group 69-74 will shift the stage distrib bution amongst alll breast cancer cases c in the popu ulation to the stage distribution of the wom men 60-69 in the same period, using data om the Belgian bre east cancer registtry. for Flanders fro

51

T This we call scena ario 3 Stage distribution S n of c cancers not foun nd by s screening B BCR data (Flemis sh p population,70-74 years, 2 2004-2008)

Sta age distribution am mongst all breast can ncers if screenin ng lev vels are similar to o lev vels among 60-69 9 in Fla anders

S Stage

%

Staage

%

I II III IV

31.6 6% 42.3 3% 16.6 6% 9.5% %

II II IIII IV V

45.7% 35.9% 12.5% 5.9%

3 3.3.7.

Stage sp pecific relative survival

Stage specific su S urvival was taken n from Belgian stage specific annual s survival data (take en from KCE repo ort 150A)86. We o only have data up p to 5 y years. We used data from the Dutch D cancer reg gister taken from m the w website (http://ww ww.cijfersoverkank ker.nl) to supplem ment until 7 years s (see a appendix 4.1). We e assumed that survival conditiona al on stage is similar in s screened and uns screened breast cancer c patients. A As a sensitivity ana alysis w used also: we •

d for women above 70 years s per Entirely the Dutch survival data T relative surviv val curve shows a lower relative su urvival stagegroup. The for women above 70 compared with the overrall survival. This s may ct that older wome en support the invvasive treatments s less reflect the fac well but it is also a possible thatt there is undertre eatment of the elderly. Moreover, the e data include pa atients that were treated more tha an 20 years ago, this may also explaiin the lower relativve survival.

•

val data coming g from breast cancer research h UK British surviv (http://info.can ncerresearchuk.orrg/) They provide 10 years survival data but survival is s considerably low wer than the Dutch h or Belgian data. One of the problem ms with 10 year survival data is tthe fact that it re eflects survival of persons treated at a least 11 yearss ago, given the e fast evolution in brreast cancer treattment this is a long time.

52


•

urvival data supplemented by Fren nch 10 year survival data Belgian su coming fro om87. The probllem of the evo olution in breast cancer treatment apply a here as for tthe British data. We did not use e US SEER data as they use an outdated o staging method, so that survivall curves per stage e are not comparrable to the other sources and difficult to incorporate in the model. The survival curves can be found d in the annex.

3.3.8.

•

In the study of o Lidgren et al.80, non-metastatic p patients were divid ded in only two groups, i.e. the first ye ear of diagnosis a and the following years. y atients in stage I, II, III (groupe ed as non meta astatic Therefore pa patients) were e assumed to have the same utility. This assumption is supported by the fact that for years y 2001-2006, the treatment wa as the ort on same for patients in stage I, II, III according to the KCE repo ncer86. Note that more recent data a may quality indicattors in breast can change this picture because many cancer found d by screening are e now onservative surge ery. Neverthelesss, data to prove e this treated by co assumption are a not available and we found no o study comparing the impact of partial p versus to otal mastectomyy on quality off life corresponding g to our inclusion criteria.

•

Utility values for f non-metastatic c patients (after th he year of surgery y) and metastatic pa atients were assu umed to remain cconstant across years. y For non-meta astatic patients, th his assumption iss supported by an US study showin ng no significant differences at yyear 5, 10, and 1581. Nevertheless,, as a sensitivity analysis we applyy a 20% decreme ent in QALYs for tak king into account a variation of utilitty values across years. y

QALY Y

Number of life years was calcullated for each sta age and a stage and this or the quality of llife (QALYs), bas sed on a literature e search was adjusted fo (see point 2.3). We made some e assumptions: •

Utility value es at start of the m model (before scrreening) were stra atified by age but percentage changess relative to these e values were ass sumed to ccording to the ag ge of the women (we did not have data on not vary ac this). For the sensitivity a analysis, we app ply a 20% reduction or increase.

•

w negative results had utility values equal to the general Patients with population..

•

In the asse essment of utility values for true ne egative and false positive results, mo obility and ability o of self-care were assumed a to be un naffected by screenin ng.

KCE Reportt 176

•

At baseline, we w did not discou unt QALYs. For th he sensitivity ana alysis, discount rates s of 1.5%, 3% and d 5% were applied d. P Parameters used in i the model are shown s in table 3.2 2.

KCE Report 176 6


53

Table 3.2: Para ameters used in the model Parame eters

No screenin ng

Base case c

Sensitivity ana alysis

3.3.1

Age spe ecific overall survivval

Belgian life-table

Belgian n life-table

Belgian life-tablle

3.3.2

Breast cancer c incidence

BCR data (Flanders population, 20042008)

BCR data (Flemish ation, 2004-2008) popula increas sed by lead time. over-diiagnosis invasiv ve cancer of DCIS

BCR data (Flem mish population, 2004-2008) 2 increased by lea ad time. over-diag gnosis invasive cancer of DCIS

Lead tim me

2 years s

3 years

Over-dia agnosis invasive cancer

10.0%

range from 3 to 30%

Over-dia agnosis DCIS

40/100 0 000 women per year

40/100 000 wom men per year

3.3.3

Participa ation rate

70.0%

range from 60% % to 80%

3.3.4

Proportiion of screened detected d cancers

70.0%

range from 60% % to 80%

3.3.5

Recall rate

3.5% (Flemish ning program) screen

range from 2% to 10%

Duration n of period after positive result

45 day ys

range from 36 to t 54 days

QALYs lost in this period

16.0%

estimated between 13% to 19%

3.3.6

Scenario 2

Scenario 3

Stage distribution

BCR data (F Flemish population, 7074years, 20042008)

Data of the DNETB ning report 2009 screen

Stage distributio on of Flemish screening 0-69) programme (50

ge distribution of Stag BCR R (Flemish women n 60-6 69 (screened and not screened)

Stage I

31.6%

80.0%

62.5%

45.7 7%

Stage II

42.3%

18.7%

31.6%

35.9 9%

54


KCE Reportt 176

Stage III

16.6%

0.8%

5.6%

12.5 5%

Stage IV V

9.5%

0.5%

0.4%

5.9% %

3.3.7

Stage specific relative survival

Belgian stag ge specific ann nual survival data a supplemented until D 7 years by Dutch data

Belgian n stage specific annuall survival data supplemented until 7 b Dutch data years by

Dutch survival or o British survival or Belgian/French h survival

3.3.8

QALY Stage II III IV

-constant

- consttant

-20.0%

Stage III IV

-constant

-consta ant

-20.0%

Stage IV V

-constant

-consta ant

-20.0%

Age rela ated QALY

-constant

-consta ant

range from + 20 0% to -20%

Discoun nted QALY

discounting rate e + 1.5%. 3% and 5%

KCE Report 176 6


3.4. Results s In the baseline scenario the mod del predicts that th here would be 130 07 years er 100 000 (13,1 p per 1000) women invited for screen ning and of life saved pe 395 per 100 00 00 (3.9 per 1000) QALYs. The mod del also predicts that 128 deaths would be b averted per 100 000 women screened s (1.3 pe er 1000), being a reductio on of 21% (numbe er needed to be offered o screening: 782). Because of the e considerable un ncertainty surroun nding the parametters and model structure e we did an exten nsive sensitivity analysis. a Most unc certainty is not due to ra andom error but d due to issues rela ating to the right choice c of source of inforrmation on the p parameter. We did not do a prob babilistic sensitivity ana alysis, as it wa as not possible to choose app propriate probability-distrributions in a meaningful way. Table 3.4 show ws the results of th he sensitivity analysis, the plausible e ranges used for this an nalysis was discu ussed in 3.3, desc cription of the parrameters and justification n of chosen valuess. The number off years of life gain ned remains fairly y constant under different T number of QA ALY gained or lostt varies much more under assumptions. The different assum mptions. This is partly due to th he fact the a lott of the uncertain or va ariable parameters have an impa act on the quality of life gained rather th han on mortality, such as high rec call rates, over dia agnosis, apart from the values v accorded tto the QALYs. Assumed degre ee of over-diagno osis has a strong impact on QALYs s gained and under the higher assumed d values of 20% or 30% even im mply that b lost instead o of gained. Years of life gained in ncreases QALY would be slightly, this due e to the fact that an over diagnose ed case cannot be ecome a new case in the e model, one could argue that this is i somewhat of an n artifact but the effect is s very small. Recall rates of 10% also can sh hift the balance to owards a loss of QALYs. ecall rates are actu ually found in som me parts of Belgium m. Ten per cent re Assumptions on n the choice of th he appropriate surrvival curve have both an impact on years of life gained and QALYs gained. The Dutch and the e number of life years y gained but lead to a British survival data increase the val data suppleme ented by loss of QALYs in certain scenarios. Belgian surviv where in between. French 10 yearr survival is somew

55

In ncreasing the ass sumed lead time to t 3 years has an n impact on both years of life gained and QALYs. o Q T model’s estim The mation of the numb ber of QALYs gain ned or lost depends on th he valuation of th hese QALYs. Dim minishing the age related QALYs, this t is th he decrease in quality q of life due e to old age, deccreases the numb ber of Q QALYs gained, as s could be expecte ed. T estimations co The oming from the Lidgren’s paper are e fairly uniform an nd do n vary much in function of the different stages. W not We introduced a larger l d decrement in qua ality of life due to o increasing stage e at diagnosis, with w 3 s scenarios: (i) decrreasing stage II III and IV with 20% %, (ii) decreasing stage IIII and IV with 20 0% or (iii) decrea asing stage IV with 20%. This ha as the e effect of increasing the number of QALYs gained, b because there are e also g gains in QALYs du ue to the stage sh hift alone outside the effect on morrtality, a persons in stag as ge I have in this scenario a better a assumed quality of o life, in n contrast to the Lidgren L data. A could be expec As cted, introducing discount d rates decreases the numb ber of Q QALYs gained. A a worst case scenario, As s we set th he estimation of o over diagnosis at 20%, re ecall rate at 10% %, loss of QALYs per recall at 0.19 9 during a period of 54 d days and using th he stage distributiion coming from the Flemish screening p program (scenario o 2). This gives a gain of 872 Years of Life but a lo oss of 3 QALYs per 10 307 00 000. A a best case sc As cenario, we set the estimation of over-diagnosis at 3%, re ecall rate at 2%, loss of QALYs per p recall at 0.13 during a period of 36 d days and using th he stage distribution coming from m the Dutch screening p program (scenario o 1). This gives a gain of 1704 Years of Life and a gain of 1626 QALYs per 100 1 000. A Applying the 22% % reduction in mortality m from the meta-analysis from G Götzsche et al. to o the Belgian life table, t as describe ed above, gives a very s similar result, 139 cancers deaths due d to breast can ncer avoided and 1145 y years of life saved d.

56


Table 3.3 Mode eling results: bas seline, worst and d best case scen nario. Scenario

Assump ptions

Years of life Per 100 00 00 women

Quality ad djusted years of life l Per 100 00 00 women

Baseline

Over diagnosis: 10% 3.5% 3 recall rate at QALYs per recall 0.16 loss of Q during a period of 45 days stage distribution com ming gram Dutch screening prog o 1) (scenario

1307 gaine ed

395 gained d

Worst case

Over diagnosis: 20% recall rate at 10% QALYs per recall 0.19 loss of Q during a period of 54 days stage distribution com ming gram Flemish screening prog o 2) (scenario

872 gained d

307 lost

Best case

Over diagnosis: 3% recall rate at 2% QALYs per recall 0.13 loss of Q during a period of 36 days stage distribution com ming gram Dutch screening prog o 1) (scenario

ed 1704 gaine

1626 gaine ed

KCE Reportt 176

KCE Report 176 6


57

Table 3.4 Mode eling results: sen nsitivity analysis s. Stage eshift scena ario 1

Stageshift scenario 2

Sttageshift sc cenario 3

Years s of life

QALYs

Years of life

QALYs

Ye ears of life

QA ALYs

1307

395

1014

186

12 246

420 0

0.03

1304

526

1011

317

12 245

551 1

0.05

1305

489

1012

280

12 245

514 4

0.1

1307

395

1014

186

12 246

420 0

0.2

1310

208

1018

0

12 249

232 2

0.3

1314

22

1022

-187

12 251

45

0.02

1307

442

1014

234

12 246

459 9

0.035

1307

395

1014

186

12 246

420 0

0.05

1307

348

1014

139

12 246

380 0

0.1

1307

190

1014

-19

12 246

249 9

36 days

1307

417

1014

208

12 246

438 8

45 days

1307

395

1014

186

12 246

420 0

54 days

1307

373

1014

164

12 246

401 1

QALYs loss pe eriod 13%

1307

416

1014

207

12 246

449 9

QALYs loss pe eriod 16%

1307

395

1014

186

12 246

434 4

QALYs loss pe er period 19%

1307

374

1014

166

12 246

420 0

1120

281

869

102

na a

na

Baseline Assumed overrdiagnosis

Recall rate

Period betwee en false positive e and confirmation test: duration

Period betwee en false positive and confirmatio on test:% QALYs lost

Participation rate r 0.6

58


KCE Reportt 176

0.7

1307

395

1014

186

na a

na

0.8

1493

509

1159

270

na a

na

0.6

1120

281

869

102

na a

na

0.7

1307

395

1014

186

na a

na

0.8

1493

509

1159

270

na a

na

Dutch survivall

1607

710

1181

310

14 481

505 5

Britisch surviv val

1714

399

1148

-3

15 585

374 4

Belgian surviv val supplemented d by French data a

1460

473

1045

96

13 365

477 7

Assumed lead d time 3 years

1098

118

875

77

11 169

187 7

All QALYs min nus 20%

1307

-948

1014

-1089

12 246

-787

All QALYs plus s 20%

1307

1587

1014

1310

12 246

153 34

Stage II III IV -2 20

1307

903

1014

465

12 246

na

Stage III IV -20 0

1307

648

1014

370

12 246

na

Stage IV -20

1307

450

1014

241

12 246

na

Discount rate 1.5% for QALYs

1307

297

1014

121

12 246

274 4

Discount rate 3% 3 for QALYs

1307

215

1014

67

12 246

193 3

Discount rate 5% 5 for QALYs

1307

138

1014

15

12 246

114 4

Effectiveness screening amon ngst participants

Survival curve e by stage from o other sources

Discounted QA ALYs

KCE Report 176 6


3.5. Discussion Under baseline e assumptions, sscreening in the age group 70-74 4 has a limited impact on o breast cancer d deaths avoided and number of yea ars of life saved, amountiing to 1.4 death a avoided per 1000 women offered sc creening in that period an nd 13 years of life e saved per 1000 women, amountin ng to 4.7 days of life gain ned per women offfered screening. This results falll within the range e that the modele ers of the CISNET T project found as reportted by Mandelblattt et al in 200948, where w years of life e gained ranged from 9 to t 22 per thousan nd women screen ned. This, despite the fact that completely y different data and d model structures were used. Years of life ga ained remained fairly constant in the sensitivity analy ysis. We choose a worstt and best case sscenario, with yea ars of life gained ranging from 872 to 170 04. It correspondss also with the sim mplified estimatio on based on the meta-analysis of Götzsche et al.4 and the Belgian B life tables,, despite ation comes from a completely diffferent source of data d and that this estima estimation meth hod. This indicate es that the estima ations of the years of life gained are fairly y robust and conssistent with other studies. s The gain in quality adjusted life years (QALYs) is i considerably le ess, with Ys per 1000 wom men (1.4 quality adjusted day of life per only 3.9 QALY women) offered d screening and uncertainty is large er. One can prese ent these data in anothe er way by statin ng that 250 wom men need to be offered screening for 5 years to gain one year of life. The sensitivity analysis shows that und der certain assumptions introducing g breast cancer sc creening in this age gro oup would actuallly generate a lo oss of QALYs. Th he most important of these is an assum med recall rate off 10%, as is the case in es should certainly y first be certain parts off Belgium, so thesse high recall rate ore proceeding. addressed befo The worst case e scenario would imply a loss of 3 QALYs per 1000 0 women screened, we made m sure that the assumptions off this worst case scenario s are still reason nable assumption ns and not unduly extreme. A nu umber of elements were not considered in the worst cas se scenario beca ause the aseline estimation n for the effect is sometimes mixed. Bringing down the ba p age-group inccreases or decrea ases the final nu umber of quality of life per QALYs gained depending on the chosen values of the other para ameters. ng induces losses s due to This is due to the fact that intrroducing screenin a over diagnosiis but gains due to o the stage shift. false positives and

59

Under the best ca U ase scenario one would w gain 16 QA ALYs per 1000 wo omen s screened. T The higher variab bility seen in the estimation of the e QALYs comparred to y years of life lost has a numbe er of reasons. T There is conside erable u uncertainty around key parameterrs that determine e a loss of QALY Ys, in p particular concern ning over-diagnosis. Variability due e to recall rates on o the o other hand rather reflects real und derlying difference es in practice bettween c countries and in Belgium between regions. There e is also conside erable u uncertainty around d the valuation off the quality of liffe, and this is nott only u uncertainty conce erning the quality of life surroun nding different breast b c cancer states but also age specific quality of life in B Belgium. If in the future f c cost-effectiveness analyses are considered, thiss problem should be a addressed if we want w to have mea aningful results. Q Quality of life attrib buted to o stage IV has on nly a limited impact on overall num mbers of QALYs gained o lost as survival in this stage is short and proportio or on of stage IV pa atients is s low. C Carles et al. 201138, in an adaptation of the CISNET model of Lee L & Z Zeelen, found an incremental bene efit for biannual sccreening 50-74 off 2.78 life years gained per p 1000 women compared c to a sch hedule 50-69. The ey did n report the QA not ALYs gained with extending the sccreening to 50-74 from 5 50-69, as it was dominated by screening from 45-- 69, but reported d that 1.86 QALYs per 1 000 were gaine ed by extending tthe screening to 45-74 4 estingly, they did not n incorporate th he results of Vilap prinyo frrom 45-69. Intere e al, 201158 into th et heir calculations, but used US survvival data. T model takes into account over--diagnosis and lea The ad time bias. How wever, itt does not take into account leng gth bias, the factt that screen-detected c cancers would ha ave a slower clinical course and have a better su urvival b because screening tends to pick-u up slow growing ttumors some of which w a not life threate are ening. Follow up studies s of screen detected cancers s and n non screen detectted cancer in the e literature show tthat survival of sc creen d detected cases is better than case es among non parrticipants, indepen ndent o stage, and thatt survival of interv of val cases is somewhat in between n88-91. T This indicates tha at there may ind deed be a lengtth time bias, thrrough s selection of less aggressive a cancers by screening. However, the fac ct that in nterval cancers have h a better su urvival than cance er among women not a attending screenin ng indicates that other factors also o play a role, suc ch as

60


selection bias (such as the so ocial class or other health related d factors en non attending screening) and re esidual confounding after amongst wome adjustment for stage. s However le ength time has no o direct impact on efficacy and on effectiveness, as dete ection of slow grrowing tumors does not gatively correlate e with the ability to detect potentiially lifenecessarily neg threatening can ncers at an earlierr stage. Length tim me has indeed a negative n impact on effic ciency, as detection of indolent tu umors means mo ore harm and greater cos st for no benefit to o women. We unfortunate ely did not have data on stage spec cific survival for tu umors in unscreened wo omen, tumors fo ound by screenin ng and interval cancers. c Moreover, there e is in general co onsiderable uncerttainty around the survival curves that will apply in the future, as treatment ev volves and actual data on e outdated. survival may be Another majorr source of unccertainty is the right choice of o stage distributions of the diagnosed ccancers and stage e-shift. The Flemish data at the stage disttributions of the interval on stage distribution show tha o do not participatte in the cancers and the cancer amongsst the people who v similar. screening are very We choose a modeling m approacch that is essenttially based on th he stage shift and its co onsequences, in ccontrast to most CISNET models that are essentially tumo or growth modelss. This has the adv vantage that it allo owed us to stay closer to the data and make less use of unobserved va ariables, arameters based on Belgian data, but has the disad dvantage incorporating pa that the model is less flexible an nd has more simp plifications. We model m an o screening on tthe proportion of cancers that are e screen overall effect of detected based d on Belgian data a in the group 50-69. This implies that we can only evalua ate the effect of th he screening sche edules actually in place in Belgium, we ca annot vary the screening interval. We W do not have the data however neede ed to parameterize e the CISNET mo odels and would be b forced to use the same e parameters thatt are already used d in the published models, we would just merely m replicate th hem. In conclusion, there t is considera able structural uncertainty around the right choice of the parameters, p so a lot of caution is needed n when inte erpreting the results. This uncertainty is reflected in the wide range of es stimated g and QALY Ys gained in the end e result. Neverrtheless, Years of Life gained there is evidence that continuing g screening until the age of 74 ye ears has

KCE Reportt 176

modest effect on the m t number of Life e Years Saved bu ut there is conside erable u uncertainty on the e effect on quality y adjusted life yea ars, and the data show th hat under reason nable assumptions the intervention n may even lead d to a lo oss of quality adju usted life years. Itt is important to b bring the recall rattes to a acceptable level before extending screening. s

KCE Report 176 6


4. ANSW WER TO CL LINICAL QU UESTIONS S What are clin nical benefits an nd specific harm ms of an exten nsion of breast cancerr organized scre eening in wome en between 70 and 74 years?

4.1. Breast cancer related d mortality What is the effe ect of an extension (70-74 years) of breast cancer orrganized screening on th he breast cancer rrelated mortality? The continued sc creening for breast canc cer between the ages of 70 and 74 makes it pos ssible to obtain an extra 13 years of life fo or 1,000 women screened. s The mo odel also 28 deaths would be averted per 100 000 women screened s predicts that 12 (1.3 per 1000), being a reduction n of 21%.

4.2. Delay between b the sccreening and th he mortality red duction How long is the delay between the screening and the associated d breast d mortality reducction? The morttality reduction appears cancer related between 4 and 7 years after scre eening

4.3. Overall mortality What is the effe ect of an extension (70-74 years) of breast cancer orrganized screening on the t overall morta ality? The effect of an extension n (70-74 years) of breas st cancer organizzed screening on n the overall mo ortality is unclear. Studie es did not have statistical powerr to detect an all-cause a mortality reducttion.

4.4. Morbidity What is the effe ect of an extension (70-74 years) of breast cancer orrganized screening on morbidity? m We found no data relate ed to the cancer morbidity m in randomized control c trials. In other words, on this basis we do no ot accept or reject the hy ypothesis that scre eening reduces th he morbidity of the breast cancer disease. Aim of screening is to detect minor tumors. Conse equently, b diminish by lesss aggressive treatment. The Belg gian data morbidity may be currently at ourr disposal do not enable us to ratiffy this assertion. Actually, A the most recentt data (KCE reporrt 150)86 show 58% % of the interventtions are conservative surgery s versus 3 38% of total ma astectomies in th he least advanced stage es (C Stage I an nd II). Nearly 90% % of patients und dergoing

61

conservative surge c ery also receive radiotherapy treatm ment, 38% are giv ven a trreatment of neo o-adjuvant chemo otherapy, and 41% receive hormone trreatment.

4 4.5. False pos sitive or false negative n resultss What are the spe W ecific harms in te erms of false possitive or false neg gative re esults? The Belg gian data currently y at our disposall show a recall ra ate of 3 3,5% in Flanders s and of 10% in Walloon and Brussels region n per s screening round. At A this age group, performance of mammography is s high a rates of false negative results are and a relatively low. For USA, rate off false n negative results are 1.5 per 100 00 women aged 70 to 79 years s per s screening round (B BCSC-USA).

4 4.6. Additiona al diagnostic tes sts What are the spec W cific harms in term ms of additional dia agnostic tests? Tw wenty to o forty additional punctures or biop psies may be expe ected per 1000 wo omen o offered screening (three rounds).

4 4.7. Over-diag gnosis and ove er-treatment What are the sp W pecific harms in n terms of overr-diagnosis and overtrreatment? Based d on selected studies, over-detecction (excluding DCIS c cases), ranged fro om (7% to 21%) to o 35% (no data sp pecific for women aged 7 to 79 years are 70 a available). Götzsche G reported d that the numb ber of m mastectomies and d lumpectomies was w significantly llarger in the scre eened g groups (no data specific s for wome en aged 70 to 79 9 years are availa able). T Three trials with adequate a randomiization showed a significant increa ase in m mastectomies and d lumpectomies (R Relative Risk (RR R) 1.31, 95% (CI)) 1.22 to o 1.42). Two trials with suboptimal randomizatio on showed the same in ncrease in interve entions (RR of 1.4 42 (95% CI 1.26 to o 1.61)). The RR for f all fiive trials combined was 1.35 (95% CI 1.26 to 1.44).

62


4.8. What attitude a should be recommend ded for women n in case off self referral? It is advisable that when a pattient asks her doctor for a screen ning, the d a strategyy minimizing the drawbacks d of scre eening92. doctor should develop In this way, an attitude stru uctured around three phases can be recommended: •

n specific to the ag ge bracket93 Information

•

Decision making m according tto the patient pers sonal assessmentt94

•

Steering off the person who o so wishes towarrds a screening involving methods th hat minimize the d drawbacks. The criteria deffined in the frame ework of the European Programme e notably make provision for the monitorin ng of the technical quality of the eq quipment ble reading of the e mammographies s, and an optimiz zation of used, the doub the recall rate955. In Belgium, the e approved mamm mography units meet m the criteria laid dow wn in the contexxt of the Europea an Programme, and a it is therefore logica al to steer those w women who explicitly request a sc creening towards these structures. s

KCE Reportt 176

KCE Report 176 6


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cancer mortality reducttion in Catalonia a (Spain). BMC Cancer. 2009;9(326). N Rosenberg MA A, Trentham-Diettz A, Smith MA, Robinson R Stout NK, SM, Frryback DG. Retrrospective cost-e effectiveness ana alysis of screeniing mammography. J Natl Cancer Inst. I 2006;98(11):774-82. Tan SY Y, van Oortmarsssen GJ, de Konin ng HJ, Boer R, Habbema H JD. The e MISCAN-Fadia continuous tumor growth model fo or breast cancer.. J Natl Cancer Inst Monogr. 2006;M Monographs.(36):56-65. Vilaprin nyo E, Rue M, Marcos-Gragera R, Martinez-Alo onso M. Estimattion of age- an nd stage-specific Catalan breast cancer surviva al functions using g US and Cata alan survival data a. BMC Cancerr. 2009;9(98). Wang H, Karesen R, Hervik A, Thore esen SA. Mamm mography esults from the firs st screening round in four screeniing in Norway: Re countie es and cost-efffectiveness of a modeled nationwide screeniing. Cancer Causes Control. 2001;12(1):39-45. Messec car DC. Mammog graphy screening for f older women with w and withoutt cognitive impairrment. J Gerontoll Nurs. 2000;26(4 4):14-24; quiz 52 2-3. Wen YP P, Sheu ML. A co ost-benefit analysis of preventive ca are: The case of o breast cancer screening. Taiwain J. Public Health. 2005;24 4(6):519-28. Advisorry Committee on n Breast Cancer S. Screening fo or breast cancer in England: past and future. J Me ed Screen. 2006;1 13(2):5961. Anonym mous. Landelijk bevolkingsonderrzoek naar bors stkanker volledig g ingevoerd; resultaten van de implementatiefase e 19901997. Landelijk L Evaluattie Team voor be evolkingsonderzo oek naar Borstka anker. Ned Tijdsch hr Geneeskd. 200 00;144(23):1124-9 9. Barratt A, Irwig L, Glasziiou P, Salkeld G, Houssami N, Kerllikowske y reduces with age. Evid.K, et al. Relative benefit of mammography 4):156-7. Based Healthc. 2002;6(4 M, Glasziou PP, Salkeld S GP, Hous ssami N. Barratt AL, Les Irwig M m in n women Benefits, harms and cossts of screening mammography

6 66.

6 67.

6 68.

6 69. 7 70.

7 71. 7 72.

7 73.

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KCE Reportt 176

70 years s and over: a systematic review. Med J Aust. 2002;176((6):266-71. Bonneux L. De vooren nadelen n van borsstkankerscreening g: tijd dence-based info ormatie. Nederla ands Tijdschrift voor voor evid Geneesku unde. 2009;153. Caplan LS S. To screen or not to screen: the issue of breast ca ancer screening in older women.. Public Health R Rev. 2001;29(2-4)):23140. Carney PA A, Abraham LA, Miglioretti DL, Ya abroff KR, Sickles s EA, Buist DSM M, et al. Factors associated a with im maging and proce edural events used u to detec ct breast canccer after screening mammogrraphy. Am. J. Roe entgenol. 2007;188(2):385-92. De Koning g HJ. Breast canc cer screening; cosst-effective in prac ctice? Eur J Radiol. 2000;33(1):32 2-7. Feuer EJ, Etzioni R, Cronin n KA, Mariotto A. T The use of modeling to S. mortality: exam mples understand the impact of screening on U.S mmography and PSA testing. Sta at Methods Med Res. from mam 2004;13(6 6):421-42. Grivegnee e AR, Autier P. Approche A econom mique du depistag ge du cancer du sein en Belgique e. Rev Med Brux. 2 2001;22(4):A277--81. Habbema JD, Tan SY, Crronin KA. Impact of mammograph hy on st cancer mortality y, 1975-2000: are e intermediate outcome U.S. breas measures informative? J Natl Can ncer Inst Mo onogr. 5-11. 2006;Monographs.(36):105 Mandelbla att J, Saha S, Teu utsch S, Hoerger T, Siu AL, Atkins D, et al. The co ost-effectiveness of o screening mammography beyond d age 65 years: a systematic re eview for the U.S S. Preventive Serrvices ce. Ann Intern Med d. 2003;139(10):8 835-42. Task Forc Prevost TC, T Abrams KR R, Jones DR. Hierarchical mode els in generalize ed synthesis of ev vidence: an exam mple based on sttudies of breast cancer c screening. Stat Med. 2000;1 19(24):3359-76. Rautenstra auch J. Is mam mmography screening only a poin ntless waste of money? m MMW-Fortschr. Med. 2000 0;142(12):4-10.

KCE Report 176 6

76. 77.

78. 79.

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86.


Xu W, Vnenchak P, S Smucny J. Scre eening mammogrraphy in n aged 70 to 79 ye ears. J. 2000;49(3 3):266-7. women Berry DA, D Cronin KA, Ple evritis SK, Frybac ck DG, Clarke L, Zelen Z M, et al. Effect E of screenin ng and adjuvant therapy t on mortality from breast cancer. c N Engl J Med. 2005;353(17 7):1784-92. Carter KJ, Castro F, Kesssler E, Erickson B. A computer model m for dy of breast cance er. Comput Biol Med. M 2003;33(4):345-60. the stud Cleemp put I, Van Wilder P, Vrijens F, Huyb brechts M, Ramae ekers D. Recommandations pour les évaluations pharmacoéconomi p iques en ue. Health technology Assessment (HTA). Bruxelles s: Centre Belgiqu fédéral d'expertise des ssoins de santé (K KCE); 2008. KCE Reports 78B (D//2008/10.273/24) Lidgren n M, Wilking N, Jonsson B, Reh hnberg C. Health h related quality of life in differen nt states of breas st cancer. Qual Life L Res. 6(6):1073-81. 2007;16 Freedm man GM, Li T, An nderson PR, Nicolaou N, Konski A. A Health states of o women after co onservative surgerry and radiation fo or breast cancer.. Breast Cancer R Res Treat. 2010;12 21(2):519-26. Burstro om K, Johannesso on M, Diderichsen n F. Health-related d quality of life by disease and d socio-economic c group in the general Health Policy. 2001 1;55(1):51-69. populattion in Sweden. H Gerard K, Johnston K, Brown J. The ro ole of a pre-score ed multie health classifiication measure in validating co onditionattribute specific c health state desccriptions. Health Econ. E 1999;8(8):6 685-99. Domey yer PJ, Sergentan nis TN, Zagouri F, Zografos GC. Healthrelated quality of life in vvacuum-assisted breast biopsy: sh hort-term y of Life effects,, long-term effectts and predictors. Health & Quality Outcom mes. 2010;8(11):2 2010. Borstka anker LETvb bn. Landelijke e evaluatie van bevolkingsonderzoek na aar borstkanker in Nederland 199 90-2007. 2010. ur S, Vrijens F, Beirens K, Vlay yen J, Devriese S, Van Stordeu Eycken n E. Quality indiccators in oncolog gy: breast bance er. Good Clinicall Practice (GCP). Brussels: Belgian n Health Care Knowledge Centre (KCE); 2010. KCE reports 15 50C (D/2010/10.2 273/101)

8 87. 8 88.

8 89.

9 90.

9 91.

9 92. 9 93.

9 94. 9 95.

67

Available from: 211&CREF=1884 47 http://kce.ffgov.be/index_en.aspx?SGREF=52 INC. Surv vie attendue des patients p atteints d de cancers en Fra ance : état des lie eux. 2010. Mook S, Van V 't Veer LJ, Ru utgers EJ, Ravdin PM, van de Velde e AO, van Leeuw wen FE, et al. In ndependent progn nostic value of sc creen detection in invasive brreast cancer. J Natl Cancer Inst. 2011;103((7):585-97. Cortesi L, Chiuri VE, Rusce elli S, Bellelli V, N Negri R, Rashid I, et al. s of screen-dete ected breast ca ancers: results of a Prognosis population n based study. BM MC Cancer. 2006;6:17. Joensuu H, H Lehtimaki T, Ho olli K, Elomaa L, T Turpeenniemi-Hujjanen T, Kataja V, et al. Risk fo or distant recurre ence of breast ca ancer hy screening or o other methods. Jama. J detected by mammograph 2004;292((9):1064-73. Olsson A, Borgquist S, Buttt S, Zackrisson S S, Landberg G, Manjer M a prognosis in b breast cancer detected J. Tumourr-related factors and by screening. Br J Surg. 20 012;99(1):78-87. Physicians s AAoF. Summa ary of Recomme endations for Cllinical Preventive e Services. In: AA AFP Policy Action AAFP; 2010. Woloshin S, Schwartz LM. The bene efits and harm ms of AMA. mammogrraphy screening: understanding tthe trade-offs. JA 2010;303((2):164-5. Jorgensen n KJ, Gotzsche PC. Content of invitations for pu ublicly funded screening mammog graphy. BMJ. 2006 6;332(7540):538-4 41. Perry N, Broeders B M, de Wolf W C, Tornberg S, Holland R, von Karsa K L. Europe ean guidelines fo or quality assura ance in breast ca ancer screening and diagnosis. Fourth F edition--sum mmary documentt. Ann 08;19(4):614-22. Oncol. 200

68

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57.

58.

59.

60.

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63.

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cancer mortality reducttion in Catalonia a (Spain). BMC Cancer. 2009;9(326). Stout NK, N Rosenberg MA A, Trentham-Diettz A, Smith MA, Robinson R SM, Frryback DG. Retrrospective cost-e effectiveness ana alysis of screeniing mammography. J Natl Cancer Inst. I 2006;98(11):774-82. Tan SY Y, van Oortmarsssen GJ, de Konin ng HJ, Boer R, Habbema H JD. The e MISCAN-Fadia continuous tumor growth model fo or breast cancer.. J Natl Cancer Inst Monogr. 2006;M Monographs.(36):56-65. Vilaprin nyo E, Rue M, Marcos-Gragera R, Martinez-Alo onso M. Estimattion of age- an nd stage-specific Catalan breast cancer surviva al functions using g US and Cata alan survival data a. BMC Cancerr. 2009;9(98). Wang H, Karesen R, Hervik A, Thore esen SA. Mamm mography screeniing in Norway: Re esults from the firs st screening round in four countie es and cost-efffectiveness of a modeled nationwide screeniing. Cancer Causes Control. 2001;12(1):39-45. Messec car DC. Mammog graphy screening for f older women with w and withoutt cognitive impairrment. J Gerontoll Nurs. 2000;26(4 4):14-24; quiz 52 2-3. Wen YP P, Sheu ML. A co ost-benefit analysis of preventive ca are: The case of o breast cancer screening. Taiwain J. Public Health. 2005;24 4(6):519-28. Advisorry Committee on n Breast Cancer S. Screening fo or breast cancer in England: past and future. J Me ed Screen. 2006;1 13(2):5961. Anonym mous. Landelijk bevolkingsonderrzoek naar bors stkanker volledig g ingevoerd; resultaten van de implementatiefase e 19901997. Landelijk L Evaluattie Team voor be evolkingsonderzo oek naar Borstka anker. Ned Tijdsch hr Geneeskd. 200 00;144(23):1124-9 9. Barratt A, Irwig L, Glasziiou P, Salkeld G, Houssami N, Kerllikowske K, et al. Relative benefit of mammography y reduces with age. Evid.Based Healthc. 2002;6(4 4):156-7. Barratt AL, Les Irwig M M, Glasziou PP, Salkeld S GP, Hous ssami N. Benefits, harms and cossts of screening mammography m in n women

6 66.

6 67.

6 68.

6 69. 7 70.

7 71. 7 72.

7 73.

7 74.

7 75.

KCE Reportt 176

70 years s and over: a systematic review. Med J Aust. 2002;176((6):266-71. Bonneux L. De vooren nadelen n van borsstkankerscreening g: tijd voor evid dence-based info ormatie. Nederla ands Tijdschrift voor Geneesku unde. 2009;153. Caplan LS S. To screen or not to screen: the issue of breast ca ancer screening in older women.. Public Health R Rev. 2001;29(2-4)):23140. Carney PA A, Abraham LA, Miglioretti DL, Ya abroff KR, Sickles s EA, Buist DSM M, et al. Factors associated a with im maging and proce edural events used u to detec ct breast canccer after screening mammogrraphy. Am. J. Roe entgenol. 2007;188(2):385-92. De Koning g HJ. Breast canc cer screening; cosst-effective in prac ctice? Eur J Radiol. 2000;33(1):32 2-7. Feuer EJ, Etzioni R, Cronin n KA, Mariotto A. T The use of modeling to understand the impact of screening on U.S S. mortality: exam mples from mam mmography and PSA testing. Sta at Methods Med Res. 2004;13(6 6):421-42. Grivegnee e AR, Autier P. Approche A econom mique du depistag ge du cancer du sein en Belgique e. Rev Med Brux. 2 2001;22(4):A277--81. Habbema JD, Tan SY, Crronin KA. Impact of mammograph hy on U.S. breas st cancer mortality y, 1975-2000: are e intermediate outcome measures informative? J Natl Can ncer Inst Mo onogr. 2006;Monographs.(36):105 5-11. Mandelbla att J, Saha S, Teu utsch S, Hoerger T, Siu AL, Atkins D, et al. The co ost-effectiveness of o screening mammography beyond d age 65 years: a systematic re eview for the U.S S. Preventive Serrvices Task Forc ce. Ann Intern Med d. 2003;139(10):8 835-42. Prevost TC, T Abrams KR R, Jones DR. Hierarchical mode els in generalize ed synthesis of ev vidence: an exam mple based on sttudies of breast cancer c screening. Stat Med. 2000;1 19(24):3359-76. Rautenstra auch J. Is mam mmography screening only a poin ntless waste of money? m MMW-Fortschr. Med. 2000 0;142(12):4-10.

KCE Report 176 6

76. 77.

78. 79.

80.

81.

82.

83.

84.

85.

86.


Xu W, Vnenchak P, S Smucny J. Scre eening mammogrraphy in women n aged 70 to 79 ye ears. J. 2000;49(3 3):266-7. Berry DA, D Cronin KA, Ple evritis SK, Frybac ck DG, Clarke L, Zelen Z M, et al. Effect E of screenin ng and adjuvant therapy t on mortality from breast cancer. c N Engl J Med. 2005;353(17 7):1784-92. Carter KJ, Castro F, Kesssler E, Erickson B. A computer model m for the stud dy of breast cance er. Comput Biol Med. M 2003;33(4):345-60. Cleemp put I, Van Wilder P, Vrijens F, Huyb brechts M, Ramae ekers D. Recommandations pour les évaluations pharmacoéconomi p iques en Belgiqu ue. Health technology Assessment (HTA). Bruxelles s: Centre fédéral d'expertise des ssoins de santé (K KCE); 2008. KCE Reports 78B (D//2008/10.273/24) Lidgren n M, Wilking N, Jonsson B, Reh hnberg C. Health h related quality of life in differen nt states of breas st cancer. Qual Life L Res. 2007;16 6(6):1073-81. Freedm man GM, Li T, An nderson PR, Nicolaou N, Konski A. A Health states of o women after co onservative surgerry and radiation fo or breast cancer.. Breast Cancer R Res Treat. 2010;12 21(2):519-26. Burstro om K, Johannesso on M, Diderichsen n F. Health-related d quality of life by disease and d socio-economic c group in the general populattion in Sweden. H Health Policy. 2001 1;55(1):51-69. Gerard K, Johnston K, Brown J. The ro ole of a pre-score ed multiattribute e health classifiication measure in validating co onditionspecific c health state desccriptions. Health Econ. E 1999;8(8):6 685-99. Domey yer PJ, Sergentan nis TN, Zagouri F, Zografos GC. Healthrelated quality of life in vvacuum-assisted breast biopsy: sh hort-term effects,, long-term effectts and predictors. Health & Quality y of Life Outcom mes. 2010;8(11):2 2010. van Borstka anker LETvb bn. Landelijke e evaluatie bevolkingsonderzoek na aar borstkanker in Nederland 199 90-2007. 2010. Stordeu ur S, Vrijens F, Beirens K, Vlay yen J, Devriese S, Van Eycken n E. Quality indiccators in oncolog gy: breast bance er. Good Clinicall Practice (GCP). Brussels: Belgian n Health Care Knowledge Centre (KCE); 2010. KCE reports 15 50C (D/2010/10.2 273/101)

8 87. 8 88.

8 89.

9 90.

9 91.

9 92. 9 93.

9 94. 9 95.

69

Available from: http://kce.ffgov.be/index_en.aspx?SGREF=52 211&CREF=1884 47 INC. Surv vie attendue des patients p atteints d de cancers en Fra ance : état des lie eux. 2010. Mook S, Van V 't Veer LJ, Ru utgers EJ, Ravdin PM, van de Velde e AO, van Leeuw wen FE, et al. In ndependent progn nostic value of sc creen detection in invasive brreast cancer. J Natl Cancer Inst. 2011;103((7):585-97. Cortesi L, Chiuri VE, Rusce elli S, Bellelli V, N Negri R, Rashid I, et al. Prognosis s of screen-dete ected breast ca ancers: results of a population n based study. BM MC Cancer. 2006;6:17. Joensuu H, H Lehtimaki T, Ho olli K, Elomaa L, T Turpeenniemi-Hujjanen T, Kataja V, et al. Risk fo or distant recurre ence of breast ca ancer detected by mammograph hy screening or o other methods. Jama. J 2004;292((9):1064-73. Olsson A, Borgquist S, Buttt S, Zackrisson S S, Landberg G, Manjer M J. Tumourr-related factors and a prognosis in b breast cancer detected by screening. Br J Surg. 20 012;99(1):78-87. Physicians s AAoF. Summa ary of Recomme endations for Cllinical Preventive e Services. In: AA AFP Policy Action AAFP; 2010. Woloshin S, Schwartz LM. The bene efits and harm ms of mammogrraphy screening: understanding tthe trade-offs. JA AMA. 2010;303((2):164-5. Jorgensen n KJ, Gotzsche PC. Content of invitations for pu ublicly funded screening mammog graphy. BMJ. 2006 6;332(7540):538-4 41. Perry N, Broeders B M, de Wolf W C, Tornberg S, Holland R, von Karsa K L. Europe ean guidelines fo or quality assura ance in breast ca ancer screening and diagnosis. Fourth F edition--sum mmary documentt. Ann Oncol. 200 08;19(4):614-22.

OPSPORING VAN BORSTKANKER TUSSEN 70 EN 74 JAAR

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