Bijlagen behorende bij NOPHO-DBH AML 2012 protocol

Bijlagen behorende bij NOPHO-DBH AML 2012 protocol voor kinderen en adolescenten met nieuw gediagnosticeerd acute myeloïde leukemie

Versie 3, 31 maart 2015 Implementatiedatum 02 april 2015 Implementatiedatum versie 2 01 januari 2014

NOPHO-DBH AML 2012 protocol Nederlandse bijlagen

Disclaimer This DCOG protocol is for clinical research purposes only, and should not be copied, redistributed or used for any other purpose. The procedures in this DCOG protocol are intended only for use by pediatric oncologists in a carefully structured setting and following approval by a competent research ethics committee. They may not prove to be more effective than standard treatment. The investigator responsible as mentioned in the protocol should be consulted first before using or attempting any procedure as described in this DCOG protocol unless this procedure is already part of the standard treatment.

Leden Ziektecommissie Myeloïde Maligniteiten Dhr. Prof.dr. G.J.L. Kaspers, voorzitter Mw. Prof. Dr. E.S.J.M. de Bont Dhr. Dr. Ch.M. Zwaan Mw. Drs. A.M.J. Reedijk Leden Protocolcommissie Dhr. Prof. dr. G.J.L. Kaspers, voorzitter Mw. Prof. Dr. E.S.J.M. de Bont Mw. Dr. M. vd Heuvel-Eibrink Mw. Dr. D.M.W.M. te Loo Mw. Dr. A.B. Versluys Mw. Drs. A.M.J. Reedijk (trialbureau) Contactgegevens Protocolvoorzitter Dhr. Prof. Dr. Gertjan Kaspers, kinderoncoloog- hematoloog VU medisch centrum, Amsterdam Tel.: 020 – 444 2420 E-mail: [email protected] Raad van Toezicht SKION Dr. W.J.W. Kollen, voorzitter Dr. M.B. Bierings Prof. Dr. E.S.J.M. de Bont Prof. Dr. G.J.L. Kaspers Dr. D.M.W.M. te Loo Dr. H. Merks Dr. M. van Noesel Dr. Ch.M. Zwaan Raad van Bestuur SKION Dr. J.G. de Ridder-Sluiter Laboratorium Dr. V. de Haas, hoofd laboratorium Dr. E. Sonneveld, plaatsvervangend hoofd laboratorium Trialbureau Drs. J.A. Lieverst, hoofd trialbureau Drs. A.M.J. Reedijk, trialmanager


Inhoudsopgave Nederlandse Bijlagen 1.

Nederlandse samenvatting

2.

Advies van Taak- en disciplinegroepen

Pagina 4- 5

2.1 Taakgroep Supportive Care

6- 9

2.2 Taakgroep Late Effecten

10

3.

Laboratoriumonderzoek SKION bij diagnose en follow-up

11 - 14

4.

Logistiek datamanagement

15 - 16

5.

Add-on studies Overzicht van de add-on studies

17

5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse

18 - 23

5.2 Integrating proteomics and kinomics in pediatric acute myeloid 24 - 32 leukemia (AML): detailed cellular insights to improve outcome 5.3 Prognostic relevance of detection Minimal Residual Disease for children with acute myeloid leukaemia

33 - 41

5.4 Predictive value of post-transplant minimal residual disease 42 - 47 and myeloid progenitor chimerism in children with high-risk acute myeloid leukemia: a prospective study 5.5 Prognostic significance of early AML blast clearance and of 48 - 51 routine bone marrow and peripheral blood monitoring by simple morphology during and after chemotherapy in pediatric AML 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia

52 - 63

Nederlandse bijlage versie 1.0 gold van 1-1-2014 t/m 1-4-2015 In Rood de bijlagen die in versie 2.0 zijn aangepast. De Nederlandse labbijlage is aangepast, de tabel met afname punten is iets aangepast. Voor het datamanagement zijn SAE definities toegevoegd. Add-on studie 5.5 is herschreven en speciale aandacht voor dagelijkse PB afname totdat de blasten uit het bloed zijn geklaard. Add-on studie 5.6 is herschreven en uitgebreid met actigrafie en melatonine bepalingen. De aanpassingen in deze SLAAP studie heeft ook consequenties voor de PIFs, deze worden nu ook door een nieuwe versie vervangen.

Inhoudsopgave

3

NOPHO‐DBH AML 2012 protocol Nederlandse bijlagen

Bijlage 1 Nederlandse samenvatting De prognose van acute myeloide leukemie (AML) bij kinderen is weliswaar sterk verbeterd de laatste decennia, maar nog steeds onbevredigend gezien de kans op een recidief tijdens of na initiële behandeling van gemiddeld 30% en de huidige kans op overleving van rond de 70%. Het primaire doel van dit klinisch onderzoek is het verbeteren van de prognose van initiële AML bij kinderen en adolescenten tot 19 jaar bij diagnose. Patiënten met een onderliggend myelodysplastisch syndroom, met Down syndroom, en/of met acute promyelocyten leukemie komen niet in aanmerking voor dit behandelprotocol, voor hen zijn separate SKION protocollen beschikbaar. Het onderzoek wordt uitgevoerd in samenwerking met andere groepen, namelijk de NOPHO (Scandinavië), BSPHO (België) en Hongkong. De belangrijkste elementen die moeten bijdragen aan een verbetering van de prognose betreffen intensieve inductiechemotherapie enerzijds, en risicogroep gestratificeerde chemotherapie op basis van flowcytometrische metingen van minimal residual disease (MRD). Op basis van literatuur én op basis van de NOPHO AML‐2004 studie zullen patiënten met een FLT3‐ITD zonder gelijktijdige NPM1 mutatie én patiënten met een slechte therapierespons op basis van MRD na 2 inductiekuren worden beschouwd als hoog‐risico (HR) patiënten. Deze HR patiënten komen in aanmerking voor allogene stamceltransplantatie. Alle andere patiënten krijgen na de inductie nog 3 consolidatiekuren, met uitzondering van degenen met een inv(16) of t(16;16) die als consolidatie 2 kuren krijgen. Meerdere studies tonen het prognostisch gunstige belang van lage hoeveelheden MRD na inductie. In dit onderzoek worden 2 randomisaties gedaan, beide gericht op de effectiviteit van inductiechemotherapie. In de eerste randomisatie wordt de eerste inductiekuur volgens de Japanse groep inclusief mitoxantrone vergeleken met dezelfde chemotherapie, behalve dat als anthracycline liposomaal daunorubicine wordt gebruikt. In de 2e randomisatie die de 2e inductiekuur betreft wordt ADxE vergeleken met FLADx. In feite is dit een vergelijking tussen een kuur met of zonder etoposide en met lagere versus hogere doseringen cytarabine. Voor beide randomisaties is de MRD‐status het primaire eindpunt voor effectiviteit van de behandeling, uiteraard zijn er secundaire eindpunten voor toxiciteit en effectiviteit. Het is de intentie dat in dit onderzoek 300‐350 patiënten worden geïncludeerd in de loop van ongeveer 5 jaar. Uiteraard zal het onderzoek worden gedaan volgens de “Good Clinical Practice” richtlijnen. ‐ Ethische aspecten ‐ 1. Regelgeving: De studie zal worden uitgevoerd met inachtneming van de declaratie van Helsinki (versie: 59th WMA General Assembly, Seoul, October 2008) en de Wet Mensgebonden Onderzoek (WMO). 2. Inclusie en consent Kinderen met acute myeloide leukemie hebben in het algemeen een acuut beloop en worden allen in Nederland snel gezien in een kinderoncologisch centrum aangesloten bij SKION. De behandelend kinderarts‐oncoloog zal normaliter deze studie aankaarten, die voor wat betreft de standaard‐arm kan worden gezien als “best available treatment”. De 1e randomisatie betreft al de initiële therapie en zal dus vroeg in het ziekteproces moeten worden aangekaart. Gezien de sterke relatie met behandeling van de leukemie zelf en de vraagstelling van de randomisatie, zal in het algemeen de kinderarts‐oncoloog de benodigde informatie verstrekken. De bedenktijd zal meestal enkele dagen kunnen bedragen. Indien de behandeling eerder moet starten en er niet voldoende bedenktijd is voor de ouders en eventueel patiënt, dan zal voor de standaardbehandeling worden gekozen.

Nederlandse samenvatting Augustus 2013, auteur Gertjan Kaspers

4


3. Voor‐ en nadelen, noodzaak voor onderzoek bij kinderen De standaardarm wordt door de beroepsgroep (SKION) gezien als “best available treatment”. De experimentele arm bevat louter reguliere, conventionele cytostatica, en in andere landen bestaan behandelprotocollen die sterk lijken op deze “experimentele” arm. Het is goed te beseffen dat de vooruitgang in de kinderoncologie de laatste decennia vrijwel geheel is bereikt door het beter toepassen van conventionele middelen. Daarom is dit onderzoek op deze manier uitgewerkt, om te onderzoeken of een ogenschijnlijk relatief gelijkwaardige behandeling toch beter is voor de gehele groep patiënten, of voor een of meerdere subgroepen. Een voordeel van de experimentele arm kunnen zijn een betere effectiviteit. Met name het gebruik van liposomaal daunorubicine is mogelijk effectiever dan de standaard mitoxantrone, en in de tweede kuur is mogelijk de hoge‐doses ara‐C effectiever dan de gebruikelijke lagere doses. Het is ook mogelijk dat in totaliteit de toxiciteit minder is, doordat in de tweede kuur geen etoposide wordt toegediend en omdat er aanwijzingen zijn dat liposomaal daunorubicine minder toxisch is dan conventionelere middelen zoals mitoxantrone. Nadelen kunnen zijn dat de effectiviteit minder is, met name dan doordat in de tweede kuur geen etoposide wordt gebruikt, en dat er meer toxiciteit is met name doordat in de tweede kuur hogere doses ara‐C wordt gebruikt. Het betreft hier therapeutisch onderzoek bij kinderen, die grotendeels jonger dan 12 jaar zijn. Hoewel acute myeloide leukemie (AML) ook bij volwassenen voorkomt, is het absoluut noodzakelijk om dit soort onderzoek juist bij kinderen te doen. De biologie van AML bij kinderen is anders en bovendien is de farmacokinetiek van de gebruikte middelen anders. Aldus is bijvoorbeeld de kans op genezing van AML gemiddeld veel hoger (ruim 70%) dan bij volwassenen. 4. Verzekering De UMC’s waar de kinderen worden behandeld zullen zorgdragen voor de proefpersonenverzekering en de algemene aansprakelijkheidsverzekering, op basis van de WMO en de richtlijnen genoemd door de CCMO. 5. Vergoeding voor deelnemers aan de studie Omdat het onderzoek direct gekoppeld is aan de behandeling zelf, is er geen vergoeding voor de deelnemers.

Nederlandse samenvatting Augustus 2013, auteur Gertjan Kaspers

5


Bijlage 2 Advies van Taak‐ en disciplinegroepen 2.1 Taakgroep Supportive Care Protocol ondersteunende maatregelen bij kinderoncologische behandeling Inleiding Uitgangspunt is dat elk centrum beschikt over eigen richtlijnen voor supportive care, die mede op grond van lokale overwegingen in het betreffende ziekenhuis door de behandelende artsen als optimaal worden beschouwd. Het doel van de onderstaande tekst is om aandachtspunten aan de orde te stellen ten behoeve van de artsen, die ter plekke veranwoordelijk zijn voor de behandeling van individuele patiënten. De informatie over medicatie wordt ingegeven door de aard van de medicatie, de toedieningsweg, de toedieningsperiode en de dosering. Een deel van deze informatie is niet gerelateerd aan een specifiek medicament maar geldt als ondersteunend in algemene zin. Uiteraard heeft elk medicament bestaat een breed spectrum aan bijwerkingen en complicaties, die onder andere zijn terug te vinden in het Farmacotherapeutisch Kompas en kinderoncologische handboeken. Verder wordt verwezen naar het binnenkort te verschijnen werkboek “Supportive care in de kinderoncologie” onder redactie van W. Kamps, M. Naafs, N. Schouten en W.J.E. Tissing, eindredactie C.M.F. Kneepkens. Op grond van de ervaringen met o.a. de toxiciteit bij protocol MRC AML‐10 wordt geadviseerd de patiënt na elke kuur opgenomen te houden tot de neutropenie begint te herstellen. Verder wordt aanbevolen kinderen met AML te behandelen in een centrum voor leukemiebehandeling bij kinderen. Medicament Potentiële bijwerking Preventieve maatregelen Anthracyclines: Daunorubicine / Idarubicine / Mitoxantrone/ Daunoxome

Cardiotoxiciteit

Echocardiografie vóór de eerste kuur (indien mogelijk), voor elke volgende kuur, drie maanden na het einde van de chemotherapie, één jaar na diagnose en vervolgens à 3 jaar. Indien de shortening fraction < 28% jaarlijks echo hart. Voor de cumulatieve doseringen van anthracycline‐ combinaties zijn nog geen specifieke afspraken over standaard echocardiografie Bij shortening fraction < 28% of > 10% reductie: overweeg dosis‐ aanpassing of staken van anthracyclines in overleg met de protocol voorzitter

Emesis

Anti‐emeticum 5HT3‐antagonist

Extravasatie

ijs applikatie 4 – 6 uur per dag, steeds gedurende ongeveer 15 min; evt kan DMSO 100 % worden geappliceerd: penselen en laten opdrogen zonder verband: 4 dd gedurende 14 dagen

Bijlage 2.1 Advies Taakgroep Supportive Care Opgesteld 30‐7‐2012 door SKION taakgroep Supportive care bestaande uit W.J.E. Tissing (vz), F.C.H. Abbink, L.M. Ball, A. Mavinkurve, E. Michiels,M.F. Raphael, I. Vonk & M.D. vd Wetering

6


Potentiële bijwerking Cytosine arabinoside

Preventieve maatregelen

Hydratie

2,5 l/m2

Emesis


Keratitis/ conjunctivitis

Oogdruppels corticosteroïden 4 dd tijdens kuur

Risico infectie Str. viridans

Profylaxe met behulp van pheniticilline‐G (50 mg / kg in 3 dd) tot na herstel uit neutropenie. In geval van penicilline‐resistente Streptococ in keelkweek: overweeg claritromycine

CZS & mucosa

In tegenstelling tot voorgaande protocollen wordt geen pyridoxine meer geadviseerd aangezien er geen enkele evidence is dat dit profylactisch werkt.

Etoposide

Matig oplosbaar

Concentratie maximaal 0,4 mg/ml

Allergeen Cave hypotensie of allergische reactie

Controle pols, bloeddruk voor en tijdens infusie In geval van allergische reactie: –> onderbreek infusie –> hervat bij herstel op lagere snelheid Eventueel vooraf antihistaminicum, hydrocortison

Fludarabine

Lymfopenie Intrathecale medicatie

Bestraalde bloedproducten tot 1 jaar na toediening

Risico toediening foutieve medicatie Pijn / belasting

Gebruik 3‐weg kranenblok‐toedieningssysteem Adequate sedatie en analgesie

Emesis


Liquorverdeling

Voor verspreiding cytostaticum in liquor 4 uur platliggen na toediening


7


Overige ondersteunende maatregelen Emesis Indien 5 HT3‐antagonist ontoereikend is, overweeg dexamethason 10 mg/m2 in 2 of 3 dd en toevoeging van lorazepam

Pneumocysitis carnii profylaxe

Cotrimoxazol 1 x daags 3/15 mg/kg op 3 dagen/week

Transfusies

Bestraalde bloedtransfusieprodukten bij lymfopenie < 0.5 x 109/l en gedurende 6 maanden na stamcel transplantatie en na Fludarabine Intensieve chemotherapie en in het bijzonder totale lichaamsbestraling bij beenmergtransplantatie kunnen leiden tot infertiliteit. Overweeg daarom de eventuele opties voor spermapreservatie.

Infertiliteit

Teratogeniciteit

De meeste chemotherapeutica zijn (potentieel) teratogeen. Bij oudere kinderen is het soms zinvol hiervoor te waarschuwen en anticonceptive maatregelen te nemen.

Neutropenie en koorts

Start breed spectrum antibiotica indien de temperatuur een aantal uur achtereen > 38,5 °C is. Overweeg gamma globuline substitutie op geleide van de spiegel.

Potentiele problemen tijdens inductie therapie

Hyperleucocytose

Tumor lysis syndroom

Totdat de leucocyten onder 50 x 109/ l zijn gedaald, dient men terughoudend te zijn met erythrocyten transfusies (in ieder geval niet als Hb>5). In zeldzame gevallen kan een wisseltransfusie overwogen worden bij een zeer hoog leucocyten aantal. Voor de start van de anti‐leukemische therapie moet gestart worden met hyperhydratie en goede controle van de diurese. Ter voorkoming van uraat nefropathie wordt gestart met allopurinol (200‐ 500 mg/m2/dag 2 dd oraal) in combinatie met Natriumbicarbonaat (streef urine pH 6.5 – 7) of met Rasburicase (bij een leucocyten aantal > 100 x 109/ l of een urinezuur > 0.45 mmol/l). Cave hyperkaliaemie, hypocalciaemie of hyperfosfataemie, waarvoor eventueel gerichte maatregelen moeten worden genomen.

Veneuze toegang

Plaatsing van een dubbel lumen centraal veneuze lijn of Port‐A‐Cath wordt aanbevolen

Mondverzorging

Tijdens chemotherapie is een goede mondverzorging van belang. Meestal is goed poetsen voldoende. Als dat door een pijnlijke mucositis moelijk is, kan de mond gespoeld worden met een NaCl 0,9% of chloorhexidine.

Profylactische antibiotica en antimycotica

Selectieve darmdecontaminatie of een andere vorm van profylactische antibiotica toedienning wordt sterk aangeraden. Infecties door schimmels, met name Aspergillus, zijn berucht tijdens AML behandeling. Schimmelprofylaxe moet overwogen worden met Itraconazol, Voriconazol en Posaconazol. De evidence is mager dat het daadwerkelijk schimmel infecties voorkomt. Daarom moeten alle kinderen goed gemonitored worden voor een aspergillus infectie. Er wordt geadviseerd 2 wekelijks een


8


galactomannan te bepalen, en bij verdenking luchtweg problematiek een Xthorax, HR CT scan en evt een BAL te verrichten.

G‐CSF (Filigastrim)

G‐CSF wordt in dit protocol niet electief gegeven, maar kan worden overwogen in geval van zeer lange aanhoudende neutropenie of als secundaire profylaxe na zeer ernstige infecties.

Trombocyten transfusies

De aanbevelingen voor trombocytentransfusies zijn als volgt: 1. Bij actieve bloedingen door trombopenie 2. Electief: voor lumbaalpunctie indien trombocyten < 50 x 109/l, tijdens de inductiefase en na BMT indien trombocyten < 20 x 109/l. 3. Overige indien < 5 x 109/l


9


2.2 Taakgroep Late Effecten Richtlijnen betreffende de zorg voor 5-jaars overlevenden van Kinderkanker (Richtlijn SKION LATER) zijn vanaf eind 2009 beschikbaar via www.SKION.nl. Deze richtlijnen zijn met financiële ondersteuning van Zonmw ontwikkeld in een samenwerkingsverband van de 7 kinderoncologische centra in Nederland. Op basis van de oncologische behandeling en de hiermee samenhangende potentiële late schadelijke gevolgen wordt aangegeven welke zorg deze kinderen en volwassenen minimaal nodig hebben. Voor de zorg tussen het einde van de behandeling en 5 jaar na diagnose is nog geen richtlijn beschikbaar. In afwachting van de ontwikkeling van een richtlijn voor deze periode kan voorlopig de SKION LATER richtlijn dienen als uitgangspunt voor de zorg.

Bijlage 2.2 Advies Taakgroep Late effecten Opgesteld september 2009 door SKION Taakgroep Late Effecten bestaande uit: HN Caron, LC Kremer, A Postma, JG de Ridder-Sluiter, AB Versluis Oktober 2009

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NOPHO-DBH AML 2012 protocol Nederlandse Bijlagen

Bijlage 3 Laboratoriumonderzoek op SKION laboratorium bij diagnose en follow-up 3.1 Tijdstippen afname beenmerg en bloed: Beenmerg (BM) + bloedafname (PB) op de volgende tijdstippen  bij diagnose  perifeer bloedonderzoek op leukocyten plus differentiatie 3 x per week, tot het verdwijnen van blasten uit het bloed (deze strijkjes hoeven niet naar SKION gezonden te worden).  op dag 22 na 1e kuur  indien onvoldoende geregenereerd en <5% blasten: wekelijks herhalen tot geregenereerd  voor kinderen met <5% leukemische cellen na de 1e kuur: afname BM en PB vlak voor de 3e kuur (=start consolidatie), dus bij regeneratie  voor kinderen met ≥5% leukemische cellen na de 1e kuur: afname op dag 22 na 2e kuur en vervolgens op geleide van protocol, afhankelijk van cellulariteit en % leukemische cellen, in ieder geval vlak voor de 3e kuur (=start consolidatie), dus bij regeneratie  high-risk patiënten: voor elke volgende kuur en binnen 2 weken voor allo-SCT  standard-risk patiënten: voor laatste kuur (FLA), optioneel voor HA3E  bij (verdenking) recidief  bloed voor MRD elke 2 maanden na einde consolidatie gedurende 1,5 jaar bij patiënten met afwijking in AML cellen die qPCR monitoring mogelijk maakt Bij elke beenmergafname, eveneens ook bloedafname met in ieder geval bloedbeeld inclusief leukocytendifferentiatie. Indien onvoldoende diagnostiek mogelijk is op basis van de beenmergpunctie(s), b.v. bij een “dry-tap”, dient een botbiopt te worden overwogen. Het is uitermate belangrijk dat de eerste aspiratie beenmerg naar de SKION gezonden wordt, om verstoring van de MRD bepalingen tgv verdunning door bloedbijmenging te voorkomen.

3.2 Aanmeldingsprocedure: A) Patiënt aanmelden bij de SKION: voor procedure aanmelding, zie website www.SKION.nl. B) Verzenden per Fiege (BLS koerier) naar het SKION laboratorium. Instructies voor verzenden, zie website www.SKION.nl. Let op: in weekend/feestdagen geldt andere procedure.

3.3 Onderzoek bij diagnose en gedurende follow-up 3.3.1 Cytomorfologische diagnostiek Benodigd materiaal  Voorafgaande aan de behandeling worden 6 ongekleurde beenmergpreparaten (zowel plet als uitstrijk) en 3 ongekleurde bloedpreparaten gestuurd naar het laboratorium van de SKION.  Tijdens en na behandeling volstaan 3 ongekleurde beenmerg preparaten en 3 ongekleurde bloedpreparaten. Bij (verdenking) recidief dient dezelfde procedure te worden gevolgd als bij diagnose. Doel Op de preparaten wordt standaard een May-Grünwald-Giemsa kleuring gedaan voor het tellen van het percentage blasten. Beoordeling en typering geschiedt volgens de WHO-classificatie, met tevens FAB typering.

Versie 2; Wijzigingen hebben betrekking op add-on PBBC Auteur Valerie de Haas

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3.3.2 Immunofenotypering Immunofenotypering geschiedt op het laboratorium van de SKION in meervoudige labeling en volgens de richtlijnen van de SIHON (www.sihon.nl) in een gefaseerde aanpak.

3.3.3 Moleculaire diagnostiek (bij diagnose en verdenking recidief) Onderstaande moleculaire fusiegen trancripten worden bepaald middels Real-time quantitative RT-PCR (qPCR). t(9;22)(q34;q11) t(8;21)(q22;q22) t(15;17)(q22;q21) Inv(16)(p13.1q22) 11q23 MLL rearrangements FLT3 D835 mutatie FLT3-ITD NPM1 mutatie

BCR-ABL CBF/ETO PML-RARA CBFB-MYH11 alle varianten, waaronder AF6, AF9, AF10

3.3.4 Liquordiagnostiek Celgetal en cytomorfologie van de cellen in de liquor wordt bepaald in MGG-gekleurde cytospinpreparaten bij diagnose, bij voorkeur op dag 6 van de eerste kuur. In het geval van CNS involvement (=CNS3) bij diagnose of een CNS2, dan moet op dag 22 opnieuw liquor worden onderzocht op celgetal en cytomorfologie. Bij persisterende blasten op dag 22 moet worden overlegd met de protocolvoorzitter. Bij patiënten met CNS involvement bij diagnose, moet liquor worden onderzocht op celgetal en cytomorfologie voor start van elke consolidatiekuur. TLP speelt bij AML geen rol van betekenis. Indien tijdens de behandeling door de behandelend kinderarts een celaantal van ≥ 5/mm3 in de liquor gevonden wordt, danwel blasten gevonden worden, dient eveneens liquor naar het laboratorium van de SKION te worden gezonden. Van de liquor wordt het aantal cellen bepaald en cytospin preparaten gemaakt. Op de cytospin preparaten wordt een May-Grünwald-Giemsa kleuring gedaan voor het tellen van het percentage blasten.

3.3.5 Cytogenetisch onderzoek (bij diagnose en verdenking recidief) Het chromosomenonderzoek geschiedt in cytogenetische laboratoria in Nederland, verbonden aan de kinderoncologische centra. Deze zijn een gezamenlijk te volgen procedure overeengekomen voor het verkrijgen van materiaal. De uitslagen worden rechtstreeks aan de behandelend kinderoncoloog toegestuurd. De SKION ontvangt eveneens de uitslag van het desbetreffende cytogenetische laboratorium. Door een panel van cytogenetici vindt jaarlijks een review van de cytogenetische uitslagen plaats.

3.4 Bepaling van therapie-respons en kinetiek Complete remissie Op dag 22 na de 1e kuur, en op dag 22 na de 2e kuur, en op de andere hierboven beschreven momenten wordt in het beenmerg hematologische remissie bepaald aan de hand van het blastenpercentage in de perifere bloed- en beenmerguitstrijk.


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Minimal Residual Disease (MRD) onderzoek MRD mbv flowcytometrie Bij diagnose wordt het "leukemia associated immunophenotype" (LAIP) vastgesteld met behulp van flowcytometrie. Door gebruik te maken van dit LAIP is het mogelijk MRD mbv flowcytometrie te vervolgen. Deze uitslag zal zo spoedig mogelijk (<48uur) na afname gecommuniceerd worden met de hoofdbehandelaar, opdat het vervolg van therapie op geleide van MRD ingezet kan worden. Indien MRD niet te vervolgen is met flowcytometrie, zal gehandeld worden op geleide van cytomorfologische beoordeling van het beenmerg. MRD mbv RQ-PCR Indien mogelijk, zal kwantificering van fusiegentranscripten met behulp van kwantitatieve PCR verricht worden op alle genoemde tijdstippen tijdens en na therapie. Deze uitslag wordt niet standaard gecommuniceerd. 3.5 Samenvatting van benodigde afnames Tijdstip Preparaten (ongekleurd) tbv morfologie

Diagnose en (verdenking) recidief Dag van diagnose en eerste week dagelijks in eigen centrum tot verdwijnen blasten Na de eerste week om de dag vanaf dag 8 in eigen centrum tot verdwijnen blasten Dag 22 na 1e kuur indien < 5% blasten op dag 22 en niet geregenereerd: wekelijks herhalen tot geregenereerd en start kuur 2 Indien ≥ 5% blasten op dag 22 kuur 1: Na 2e kuur op dag 22 Bij aanvang van 3e kuur (eerste consolidatiekuur)

BM

PB

6

3

Hemoblok tbv immunofenotypering & flow MRD, moleculaire diagnostiek en MRD-PCR Beenmerg en Perifeer Bloed (2x heparine buis BM, 1x PB) Ja

Liquorblok

Buis met medium aanvullen tot streep ja

VBB + leuko diff

VBB + leuko diff

3

3

Ja

ja

3

3

Ja

#

3

3

Ja

#

3

3

Ja

#


13


Vervolg Samenvatting van benodigde afnames Tijdstip

Preparaten (ongekleurd) tbv morfologie

HR: elke volgende consolidatiekuur SR: vóór laatste kuur (FLA), optioneel voor HA3E Na einde consolidatie: elke 2 maanden gedurende 1,5 jaar Vóór allo-SCT

3

3

Hemoblok Liquorblok tbv immunofenotypering & flow MRD, moleculaire diagnostiek en MRD-PCR Ja

3

3

Ja

3

PB indien qPCR mogelijk is

3

Ja

3

#

# Indien tijdens de behandeling een celaantal van ≥ 5/mm3 of blasten: liquorblok inzenden


14


Bijlage 4 Logistiek Datamanagement 4.1 Datamanagement Direct data entry voor registratie, randomisatie, behandelgegevens, toxiciteiten, events en follow-up De digitale CRFs kunnen door de sites in de database (NOPHO database) worden ingevoerd. Indien er vragen zijn of hulp nodig is bij het invoeren, kan contact worden opgenomen met SKION Trialbureau. Invoerinstructies staan in een aparte handleiding. Voor de eerste randomisatie zijn een aantal basis registratie items verplicht in te vullen. Deze dienen binnen 4 dagen na diagnose van de patiënt ingevoerd te zijn, zodat uiterlijk op dag 5 de randomisatie uitgevoerd kan worden. Dit gebeurt ook in de NOPHO database. Tweeëntwintig dagen na start van de eerste kuur moeten weer een aantal items ingevuld zijn, zodat ook de tweede randomisatie kan worden voltooid. Zie hoofdstuk 10 van het protocol welke items het betreft. Daarnaast zal één en ander ook opgenomen worden in de invoerinstructies.

4.2 Serious Adverse Events Alle Serious Adverse Events moeten binnen 24 uur (kantooruren) van bekend worden van het event bij het SKION datamanagement gemeld worden via het SKION on-line SAE meldings systeem (http://www.skion.nl/sae). Zie ook hoofdstuk 14 van het protocol. De voorzitter van de protocolcommissie initAML of diens plaatsvervanger wordt meteen via email op de hoogte gebracht. De voorzitter zal beoordelen of, en zo ja welke vervolgacties nodig zijn. Het Trialbureau zal desgewenst contact opnemen met de internationale voorzitter van het NOPHO-DBH AML 2012 protocol. Elke SAE moet worden gevolgd tot deze verdwenen of gestabiliseerd is en elke initiële melding moet zo spoedig mogelijk doch uiterlijk binnen 30 dagen nadat het SAE is verdwenen of gestabiliseerd, gevolgd worden door een follow-up rapport. Definition of Serious Adverse Events The definition of a Serious Adverse Event (SAE) is any undesirable sign, symptom or medical condition which:  is fatal or life-threatening  requires prolonged hospitalization or unexpected hospital admission  results in persistent or significant disability/incapacity  constitutes a congenital anomaly or a birth defect  is medically significant, may jeopardize the subject and may require medical or surgical intervention to prevent one of the outcomes listed above. Life- threatening events are defined as:  circulatory/cardiac insufficiency requiring catecholamines/positive inotropes  respiratory failure requiring intubation/ventilation  other clinical situations requiring immediate intervention, e.g. gastrointestinal bleeding or perforation requiring surgery cerebral abscess/bleeding requiring immediate neurosurgical intervention. It is not necessary to report SAEs that only require hospitalization or prolonged hospitalization, because the intensity of the therapy will lead to too many SAEs by this definition. Only the following events have to be reported as SAE within 24 hours of learning of its occurrence: 1. life-threatening SAEs according to the definitions stated above 2. grade IV infections, systemical or invasive fungal infections or severe soft tissue infections Januari 2013, uitbreiding met SAE definitie in april 2015 Auteur Ardine Reedijk

15


3. unexpected grade III/IV SAEs In case of doubt, please contact the study chair. All other grade III/IV toxicities should be registered on the regular toxicity forms in the NOPHO database. Examples of toxicities that occur frequently and that should NOT be reported as SAE are:  Hospitalization for i.v. antibiotic treatment due to non-life threatening or uncomplicated infections (fever with neutropenia after chemotherapy).  Hospitalization for parenteral nutrition or i.v.-rehydratation due to mucositis, anorexia or vomiting/diarrhea.

4.3 Monitoring Volgens Hoofdstuk 14 van het protocol zal er vanuit SKION in de lokale centra gemonitord gaan worden. De nadruk zal hierbij komen te liggen op het checken van Informed Consents, in- en exclusie criteria, data ingevuld in de database, compliance met het protocol, als ook op de efficacy en safety eindpunten. Het SKION Trialbureau zal in principe één maal per jaar gaan monitoren in de lokale centra. Voor deze studie is een specifieke monitor manual gemaakt en deze wordt toegelicht tijdens de initiatie meeting.

Januari 2013, uitbreiding met SAE definitie in april 2015 Auteur Ardine Reedijk

16


Bijlage 5 Overzicht add-on studies Biologie 5.1 AML stem cell frequency and oligoclonality (Cloos & Kaspers) 5.2 Proteomics & kinomics (de Bont) Minimal residual disease 5.3 MRD flow at initial diagnosis & relapse (vdr Velden & de Haas) 5.4 MRD and myeloid progenitor chimerism post-SCT (Lankester) and 5.1 AML stem cell frequency and oligoclonality (Cloos & Kaspers) Klinisch en kwaliteit van leven 5.5 Early treatment response and routine BM/PB monitoring (Klein, Kaspers & de Bont) 5.6 Quality of life, sleep and fatigue (v Litsenburg & Kaspers)

Bijlage 5 Overzicht add-ons

17


5.1

Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse J. Cloos (Research coördinator Pediatric Oncology/Hematology VUMC)* G.J.L. Kaspers (Pediatric Oncology/Hematology VUMC) V. de Haas (SKION/VUMC) B.F. Goemans (Pediatric Oncology/Hematology, VUMC) GJ. Schuurhuis (Hematology, VUMC) V. van der Velden and J. van Dongen (Immunology, Erasmus MC) * Corresponding author VU university medical center Pediatric Oncology/Hematology De Boelelaan 1117 NL-1081 HV Amsterdam The Netherlands 020 - 444 2420 [email protected]

1. Algemeen overzicht van het onderzoeksveld We hypothesize that to further improve the outcome of children with AML, we need to increase our knowledge of AML stem cells and of the presence of molecular abnormalities in minimal residual disease and leukemic stem cells. This will be the focus of our research proposal. The outcome of pediatric AML has improved significantly over the past decades, but seems to have reached a plateau at about 60% survival with contemporary intensive chemotherapy. The leading cause of treatment failure is a relapse. Relapse is thought to arise from minimal residual leukemic cells and leukemic stem cells. The amount of AML stem cells at initial diagnosis and in minimal residual disease (MRD) might provide a novel prognostic factor, which might be useful in risk-group adapted treatment. Indeed, a high AML stem cell burden at initial diagnosis was recently shown to correlate with high levels of MRD and to be a significant adverse prognostic factor in adult AML (van Rhenen, 2005). The implementation of novel targeted agents, such as tyrosine kinase inhibitors, may further improve outcome by reducing relapses, without undue toxicity. Thus, it is important to study the presence of these treatment targets in the populations of AML cells, which are most relevant to target minimal residual disease cells and especially the AML stem cells. We (Cloos, 2006) and others (Tiesmeier, 2004) have shown that the presence of treatment targets such as a FLT3/ITD or KIT mutation is unstable from initial diagnosis to relapse. It is therefore not sufficient to determine the presence of these mutations in the bulk of the leukemic cells at initial diagnosis. Minimal residual disease and AML stem cells can be detected by extensive immunophenotyping and sorted with modern flowcytometers (Rhenen, 2007). Using flowcytometry, our group has the possibility to reliably identify both AML and normal stem cells within one and the same sample by including CLL-1 and other aberrant markers/marker combinations, together with scatter aberrancies. The cause of the instability of these mutations between initial diagnosis and relapse is unknown. One hypothesis is that AML is an oligoclonal malignant disease. This implies that treatment targets may be present in part of the AML cells, but not in all of them. This can be studied using the same sophisticated flowcytometrical techniques mentioned above. Such oligoclonality may explain the instability of molecular abnormalities, since certain subclones may disappear from diagnosis to relapse, while other small subclones, containing molecular abnormalities that were not detected at initial diagnosis, may actually become the relapsing clone, leading to the presence of the molecular abnormality in the relapsing AML cells. An alternative explanation for the emergence of molecular abnormalities from diagnosis to relapse is genetic instability of the AML (stem) cells, leading to either Bijlage 5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse 18


spontaneous or drug-induced additional genetic abnormalities over time. It seems important for our understanding of AML to study these phenomena. 2. Doel/vraagstelling van het onderzoek The general aim of this study is to increase our knowledge on the frequency of AML stem cells and on the presence of molecular abnormalities in MRD cells and more specifically in AML stem cells. The mutational status will be investigated in relation to its presence in different subclones at initial diagnosis, and thereby the existence of oliglclonality of AML in children and adolescents. We want to accomplish this by answering the following questions: 1. What is the burden of AML stem cells at initial diagnosis and at the setting of MRD, how does this correlate with well-known clinical and cell biological features such as FAB type and cytogenetics (including molecular abnormalities), and what is the prognostic significance of both factors. 2. What is the correlation between levels of MRD as determined by more conventional techniques, and the leukemic stem cell load, at different time-points. 3. What are the differences in type I and type II abnormalities from initial diagnosis to MRD (and ultimately to relapse), and when comparing the AML stem cells and the more progenitor type AML cells 4. Is there oligoclonality of AML, and how do subclones develop from initial diagnosis to MRD (and ultimately to relapse).

3. De relevantie van het onderzoek voor AML op de kinderleeftijd The relevance of this research is threefold. First, we may identify a novel prognostic factor by determining the AML stem cell burden at initial diagnosis and at the situation of MRD. Second, we will increase our knowledge of the biology of AML in general, especially concerning stem cells and oligoclonality, which might become useful in future treatment and disease monitoring. Third, this study will provide important information on how and when to apply targeted therapy; especially tyrosine kinase inhibitors in future targeted therapy protocols.

4.

Eventuele preliminaire resultaten

Stem cell load detection in initial and MRD samples The prognostic impact of stem cell frequency in CD34-positive AML was investigated by analyzing whether the CD34+/CD38– compartment at diagnosis correlates with MRD frequency after chemotherapy and clinical outcome in 92 adult AML patients (van Rhenen, 2005l). A high percentage of CD34+/CD38– stem cells at diagnosis significantly correlated with a high MRD frequency, especially after the third course of chemotherapy. Also, it directly correlated with poor survival (figure 1). Figure 1: Kaplan-Meier plot of relapse-free survival (n=60). The cutoff used is 3.5%. The patients with a high stem cell frequency at diagnosis (>3.5%) had a median relapse-free survival of 5.6 months (n = 15). This is in strong contrast to the patients with a low stem cell frequency who had a median relapse-free survival of 16.0 months (n = 45). This difference was significant using log-rank statistics (P = 0.02).

Bijlage 5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse 19


In contrast, the percentage of CD34+ AML cells in total percentage showed no such correlations. In addition, in vivo data showed that engraftment of AML blasts in non-obese diabetic/severe combined immunodeficient (NOD/SCID) mice directly correlated with stem cell frequency of the graft. Both in vivo data, as well as the correlation studies, show that AML stem cell frequency at diagnosis offers a new prognostic factor. From our data, it is tempting to hypothesize that a large CD34+/CD38– population at diagnosis reflects a higher percentage of chemotherapy-resistant cells that will lead to the outgrowth of MRD, thereby affecting clinical outcome. Previously, the group of Schuurhuis at VUMC (van Rhenen) found that C-type lectin-like molecule-1 (CLL-1) has high expression on the whole blast compartment in the majority of AML cases. Moreover, CLL-1 expression is also present on the CD34+/CD38- stem- cell compartment in AML (77/89 patients). The CD34+/CLL-1+ population, containing the CD34+/CD38-CLL-1+ cells, does engraft in NOD/SCID mice with outgrowth to CLL-1+ blasts. CLL-1 expression was not different between diagnosis and relapse (n = 9). In remission, both CLL-1- normal and CLL-1+ malignant CD34+/CD38cells were present. A high CLL-1+ fraction was associated with the development of an earlier relapse. CLL-1 expression is completely absent both on CD34+/CD38- cells in normal (n = 11) and in regenerating bone marrow controls (n = 6). In addition to the LAP and CLL-1, the stem cell fraction can be even further characterized using scatter properties (figure 2).

Figure 2: Additional separation of normal (p11) versus malignant (p12) stem cells based on scatter properties.

These results indicate that malignant stem cell frequency may be an important additional prognostic factor and malignant stem cell fractions can be more specifically detected by combining LAP, CLL-1 expression and scatter properties. Instability of type I mutations in AML We (Cloos et al.) determined FLT3/ITD and D835 point mutations in paired initial and relapse samples from 80 pediatric and adult AML patients. One D835 point mutation was found in an initial pediatric AML sample. FLT3/ITDs were present in 21 initial and 22 relapse samples (26.3 and 27.5%, respectively). Interestingly, FLT3/ITD positivity was related to a significantly shorter time to relapse, most pronounced when the ITD-positive status was found at relapse (P<0.001). However, FLT3/ITD status changed between diagnosis and relapse in 14 cases. In four patients, the FLT3/ITD became undetectable at relapse, in five patients FLT3/ITDs were only detected at relapse, and in five patients the length or number of FLT3/ITDs changed (table 1). Currently we are extending this study by determining all relevant type I/II mutations in 80 paired pediatric AML samples. Preliminary analysis suggests that in about 40% of cases changes in mutations occur and that these are associated with the time to relapse. Our hypothesis is that for some patients the gained mutation at relapse was already present in the initial sample but in a very small subclone. In order to detect the mutations in these very small cell populations, we have set up an method to sort the cells in a 96-wells plate with 25 cells per well. We Bijlage 5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse 20


are able to perform very sensitive mutation analysis on these sorted subpopulations. For example, iIn a sample of leukophoresis material that was supposed not to harbor any tumor cells we have detected the FLT3/ITD in some of the cell fractions. Table 1

Relation between changes in FLT3/ ITD status and time to relapse

FLT3/ITD status Initial

Median # Number of months toANOVA patients relapse (P-value) (n = 80) (p25 – p75)

Relapse

I FLT3/ITD status in initial sample Wild type Any status 59 FLT3/ITD+ Any status 21 II FLT3/ITD status in relapse sample Any status Wild type 58 Any status FLT3/ITD+ 22 III FLT3/ITD changes in initial and relapse sample Wild type Wild type 54 FLT3/ITD+ FLT3/ITD+ 12 Wild type FLT3/ITD+ 5 FLT3/ITD+ Wild type 4 FLT3/ITD+ Different ITD 5

12.6 (9 – 21) 7.8 (5 – 9)

P<0.03

13.5 (9 – 22) 6.6 (5 – 8)

P<0.001

13.4 (9 – 22) 7.4 (5 – 8) 6.3 (5 – 19) 15.4 (5 – 46) 4.7 (4 – 10)

P<0.03

In an AML sample of which we had frozen material available we performed our new cell sorting and PCR method. We could show that the mutation that was gained at relapse was indeed present in the initial sample (figure 3). However, the mutation was found in the CD38 dim population and not in the CD38- as we would have expected. More samples will be analyzed in the near future to determine if this oligoclonality can be found in all patients. For some patients the concept of genomic instability may still be an explanation for the change in mutations.

A

B

P 10 CD34+/CD38CLL1 -

P 10 CD34+/CD38CLL1 +

P 11 CD34+/CD38dim CLL1 -

P 12 CD34+/CD38dim CLL1 +

Figure 3: A) Flowcytometric gating strategy of the initial sample including stem cell markers CD34, CD38 and CLL1; B) FLT3/ITD analysis. The red arrow represents the ITD length that was only present in` the relapse sample while the green arrow is the ITD length that was found in the bulk of the initial sample. CLL1- population represent normal cells and do not show ITD as expected. The relapse ITD was found in the more mature CD38dim fraction of this initial sample.

Bijlage 5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse 21


These results suggest that at least in some patients the subpopulation of cells, harbouring the mutation of the relapse, was already present in the initial sample. This warrants the detection of mutations during treatment and at MRD settings. These data are important for knowledge about relapse development and decision making on targeted intervention for instance using FLT3 inhibitors.

5. Een (korte) beschrijving van de te gebruiken onderzoeksmethoden We will determine stem cell load in initial samples and the subsequent MRD and follow-up samples. We will use flowcytometry methods that were successfully used in our laboratory in adult AML samples. In order to use as few cells as possible we will apply the leukemia associated phenotype (LAP) as determined in The Hague at SKION/DCOG (de Haas et al) in collaboration with the Dept. of Immunology in Rotterdam (van der Velden & Van Dongen et al.). We will determine the stem cell load by FACS analysis using besides lineage markers, CLL-1 and scatter properties. Including these markers is interesting since it may improve the number of patients for whom we can determine the malignant stem cells and it will also enable to quantitate the more specific malignant stem cell load. In addition to the quantification of these stem cells we will sort them and molecularly characterize them for the presence of the known type I and II mutations. We will also determine these mutations in several other leukemic subpopulations, such as the non-stem progenitor cells. Mutation analysis currently included are: FLT3, c-KIT, RAS, NPM1, CEBPα and WT1.

6. Kwantificering van het gevraagde materiaal/gegevens met statistische onderbouwing Overview of requested samples:

Sample

Fresh/Frozen

Number of cells

Application

Initial

Frozen

1 µg DNA

Mutation profiling of the bulk of cells

Frozen (DMSO) vial

MRD

50.10

6

Subpopulation characterization on mutation profile and determination of stem cell load including CLL-1

Residual of fresh Depending on cell Subpopulation characterization on material* number and % MRD of mutation profile and determination of sample preferably 8.106 stem cell load including CLL-1 cells

*after 5-106 cells for immunophenotyping and 5.106 cells for molecular diagnostics at SKION or Rotterdam Logistics of material flow to Amsterdam: Initial sample:  DNA for mutation analysis  Results of LAP as determined by immunophenotyping at SKION and Rotterdam will be communicated with Amsterdam MRD samples at the different time points that bone marrow samples are drawn during the treatment:  Residual fresh material will be sent to Amsterdam after the SKION and Rotterdam have taken o 5-10.106 cells for immunophenotyping o 5.106 cells for molecular diagnostics Bijlage 5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse 22


Cryopreserved cells from initial diagnosis:  Vials containing 50.106 cells will be send in bulk to Amsterdam at a later stage to analyze subfractions and determine stem cell load. An additional option is to send vials of 70.106 cells so we will sort 20.106 cells on CD34+/CD38- and freeze the pellets to be send to Groningen (see add-on study by de Bont et al.) In order to determine the association between the development of relapse and mutation profile (including stem cell load) we need to perform our analysis on the whole cohort of patients included in the clinical protocol. This includes the patients with no known type I mutation and those who do not change in their mutational status during MRD of which we expect they will have a lower probability of relapse.

Stem cell frequency To be able to show a statistically significant difference between the prognosis of patients with a lowversus a high -stem cell load we consider the data as has been published by van Rhenen et al. (2005) from the Hematology Laboratory of our institute. This implies that taking into account the same variation in stem cell frequencies we would need approximately 60 patients of whom we can determine the stem cell fraction (estimated to be 80% of pediatric patients). So a total of 80 patients would be required. Successful identification of the stem cells will differ among patients and depends on the stem cell load and available aberrant markers. Oligoclonality To know the standard mutational status of the initial sample we will determine the most relevant type I/II mutations. After analysis these data will be sent to the SKION. Our preliminary studies in pediatric and adult AML have shown that we need 50.106 cells to sort different leukemic subpopulations and determine all type I/II mutations. We have established collaboration with the Immunology laboratory in Rotterdam (van Dongen/van der Velden) and SKION (de Haas) to use the LAP they define as a starting point for our analyses. In this way we are able to limit the amount of cells needed to a minimum. In addition, we will agree to share the sorted cell populations of the initial samples with other research groups when feasible. We could for instance arrange that when we have ≥70. 106 cells we will sort 20.106 cells on CD34+/CD38- and freeze the cells to be shipped to Groningen. Despite the collaborations between research groups to reduce the amount of cells needed, it would be very helpful if a second bone marrow aspirate (which can be done without an extra puncture through the skin) will be performed to obtain as many leukemia cells as possible, without diluting the bone marrow with blood in case of one extended aspiration. 7.

Literatuurlijst van het onderzoeksveld

Van Rhenen et al. High stem cell frequency in acute myeloid leukemia at diagnosis predicts high minimal residual disease and poor survival. Clin. Cancer Res., 2005;11:6520-7. Cloos et al. Stability and prognostic influence of FLT3 mutations in paired initial and relapsed AML samples. Leukemia, 2006;20:1217-20. Tiesmeier et al. Evolution of FLT3-ITD and D835 activating point mutations in relapsing acute myeloid leukemia and response to salvage therapy. Leuk Res., 2004;28:1069-74. Van Rhenen et al. The novel AML stem cell-associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells. Blood, 2007;110:2659-66. Van Rhenen et al. Aberrant marker expression patterns on the CD34+CD38- stem cell compartment in acute myeloid leukemia allows to distinguish the malignant from the normal stem cell compartment both at diagnosis and in remission. Leukemia, 2007;21:1700-7. Bijlage 5.1 Stem cell frequency and oligoclonality of mutations in childhood AML and their functional consequences for the development of relapse 23


5.2

Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome Dr. E.S.J.M. de Bont (Division of Pediatric Oncology/hematology, UMCG)* Dr. A. ter Elst (PhD) (Division of Pediatric Oncology/hematology, UMCG) Prof. Dr. M. P. Peppelenbosch (Department of Cell Biology, UMCG) Prof. Dr. S.M. Kornblau (Department of Stem Cell Transplantation and Cellular Therapy, University of Texas, and Anderson Cancer Center, Houston, USA) Dr. D. Pe’er (Section of Biological Sciences, Columbia University, New York, USA) * Corresponding author University Medical Center Groningen/ Beatrix Children’s Hospital Pediatric Oncology/ Hematology Hanzeplein 1 PO Box 30001 9700 RB Groningen The Netherlands 050-3614213 [email protected]

Introduction Despite similar clinical features at presentation, there are many different types of acute myelogenous leukemia (AML). Proteins form complex signalling pathways that control how normal hematopoietic cells respond to signals from the body to regulate proliferation, apoptosis and differentiation into functional blood cells. The amount or activity of these proteins is often abnormal in AML cells, and this can affect the response to therapy. The group of Steve Kornblau utilized a new technique called Reverse Phase Protein Array (RPPA) to measure the level of expression and phosphorylation of 176 cell signalling, apoptosis and cell cycle regulating proteins using less material than was previously required to study one protein. Seven signatures were differentiated based on the overall pattern of expression of all these proteins. These signatures showed a clear relation with outcome (Kornblau et al., 2006, 2009). Reversible phosphorylation of proteins on serine, threonine or tyrosine residues is a major signalling mechanism in the cell. Kinases are responsible for the reversible phosphorylation of all proteins. The measurement of multiplex kinase activity is called kinomics. The groups of Maikel Peppelenbosch, who developed a kinomic array, and of Eveline de Bont, pediatric oncology, have used the kinome array to measure the activity of these kinases in leukemic cells on 1024 different sites on the array (Sikkema et al., 2009, ter Elst et al., 2011). A leukemic signalling pathway was elucidated and validated in functional assays using specific inhibitors as well as potential drugable targets listed (Sikkema 2009, Sikkema 2010, Sikkema 2012 in press, ter Elst 2010, ter Elst 2011, Sligte 2011). The two platforms (proteomics and kinomics) complement each other as many of the peptides used in the kinomic array are measured with phosphospecific antibodies used in the RPPA, while several others are the downstream targets of these phosphoproteins. In this add on study we propose to perform functional kinomic profiling and proteomic profiling using RPPA on the same samples. This will provide a functional measurement to complement the measurement of expression and phosphorylation levels. Since these proteins are major signalling molecules of pathways or networks, we will perform highly sophisticated statistical network based analysis that combines data from all these datasets. This will create a map of expression and phosphorylation activity within leukemic cells with a detail and precision that is unprecedented. Previously generated RPPA data are present for adult AML, but we propose to study pediatric AML samples. This will enable us to evaluate the commonalities and distinctions between pediatric/adult cases. These maps will give insight into the different biology present in AML and help to explain why we see differences in response to therapy despite similarity of other clinical features like cytogenetics. The final aim of this add on study is to investigate some of these insights in greater detail to confirm the proteomic, and kinomic based observations. There are many emerging Bijlage 5.2 Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome

24


“targeted” therapies being developed that aim at many of these same proteins, but we lack the means to intelligently match the correct targeted therapy to the correct patient. We believe that this map will enable us to identify which pathways are crucial to the survival and resistance of individual patients’ leukemic cells and that this will facilitate the correct matching of the right targeted therapy to the right patient, thereby improving outcome. Thus, with this add on study proposal in AML we will investigate the biological processes in greater detail and discover new avenues in AML cell biology and AML cell survival. Now, we have a dataset of 107 pediatric AML samples of which proteomics and kinomics will be available. More precise and stronger conclusions can be drawn when these kind of databases are as large as possible. In the meantime, in the preliminary results we presented the first analyses of parts of the cohort. 2. Doel/vraagstelling van het onderzoek The goal of this add-on study is to produce an exceptionally detailed map of protein expression, phosphorylation and enzymatic activation in AML that integrates proteomics and the net functional measurement of kinomic profiles. In this study we will focus on AML cells. Our hypothesis is that this will reveal a phenotypic proteomic based classification system with the ability to discern different means of arriving at the same functional state. This in turn will provide new insights into leukemia biology that can be formally tested in greater detail. These observations will lead to the development of clinical kits based on key measurements that can then be prospectively tested for the ability to classify cases, provide prognostic information and to aid in the rational selection of therapeutic agents. Objectives: 1)

2)

3)

4)

Characterize the deregulated signaling pathways in pediatric AML by means of proteomics and kinomics and integrate the results and compare the bulk of AML cells with the CD34+/CD38- fraction. Compare the obtained results in pediatric AML with already generated data of over 250 adult AML samples from the lab of Steven Kornblau (MD Anderson Cancer Center, USA), in both the bulk of AML cells and the CD34+/CD38- fraction. Identify clusters of pediatric AML patients with overlapping signaling pathways or amino acid profiles and correlate with patient characteristics such as age, cytogenetics, risk groups, remission status and outcome. Identify potential therapeutic targets also related to available small molecule inhibitors and validate these specific inhibitors with targeted therapy with cell survival assays.

The project will start with kinomic and amino acid profiling on the pediatric AML samples (bulk leukemic cells and CD34+ enriched leukemic cell populations) and the same samples will be utilized for RPPA analysis. This will provide a complex dataset, which one might suggest will be a problem to analyze. However, within our collaboration we have a vast experience with gene expression data sets, Amino acid datasets, RPPA datasets and kinomic datasets. In the UMCG we have a substantial and cooperative collaboration with Dr G.Te Meerman and Dr L. Franke, from the bioinformatics group of the department of Genetics. In addition the group of Dana Pe’er, New York, will take care of the integrative statistical analysis of the proteomics and kinomics datasets. The group of Pe’er has wide experience in the use of Bayesian networks for the reconstruction of molecular networks (Sachs et al., 2005)) and seems to be the perfect group to analyze these large datasets. With this detailed map we will be able to compare various populations with each other and correlate the maps to patient details. In the meantime, with these results we will be able to identify clusters of activity and make provisional signal transduction schemes as shown in the prior results. It will be possible to investigate the modulating capabilities of amino acid profiles on the signaling maps. Then Bijlage 5.2 Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome

25


we will continue by discerning possible inhibitors upon the given results. With functional assays we will investigate their potential for clinical studies in pediatric AML patients. Figure of the overall study design:

Figure legend: This figure shows the overall study design of the integration of the kinomics and RPPA, generated in this add on study. We might encounter the criticism that this is a fishing expedition. However, our previous work has been shown that these individual platforms involved have been proven successful in predicting pathways in oncological diseases. We would counter that the bait is appropriate.

Relevance of the study for AML patients The identification of active signal transduction pathways will expand our insight into the malignant progression of pediatric AML. These new insights will lead to new strategies in addition to standard chemotherapeutic treatment and could improve outcome further of pediatric AML patients.

Preliminary results We already have generated kinome profiles in three cohorts of patient samples: pediatric brain tumor tissues (Sikkema et al., 2009), pediatric leukemia samples (ter Elst 2011) and more recently pediatric AML samples carrying a MLL translocation (Fig. 1).

Bijlage 5.2 Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome

26


Figure 1. Heat map representing kinase activity in primary MLL-rearranged AML samples and NBM samples. Unsupervised clustering of phosphorylated peptides, the proteins from which the peptides are derived, and in brackets the possible upstream kinases.

Recently, we succeeded using these high-throughput approaches for kinomic and proteomic profiling to identify specific aberrant kinase signatures in MLL-rearranged AML as compared to normal bone marrow. These signatures resulted in a detailed map which allowed the selection of potential drugable targets (see schematic overview in Fig. 2 and the results of cell survival analysis in Fig 3). New is the possible analysis of dynamic kinome reprogramming of signaling networks in response to the targeted drug. This approach is able to predict the dynamic escape mechanism and allowed to predict the efficacy of novel combination strategies.


27


Figure 2. Provisional scheme of active kinases and phosphorylated proteins in MLLrearranged AML. Receptor tyrosine kinases and downstream kinases that were found to be active and/or phosphorylated in MLLrearranged AML. Active kinases are displayed as green-white ovals, phosphorylated proteins as yellow ovals, and proteins that were active on the kinase array and phosphorylated on the proteome profiler array are presented as green-yellow ovals. Proteins of which the kinase activity was found to be higher in MLL-rearranged AML cells compared to normal bone marrow were included in the provisional scheme as ovals with thick lines, bold receptors and, bold cell cycle proteins. Red arrows indicate the proteins that were used as druggable targets.

Figure 3. Cell survival analysis of AML cell lines, primary pediatric MLL-rearranged AML samples, and NBM upon treatment with different inhibitors Cell survival analysis of A) previously reported insensitive controls; cervical cancer cell line Hela and colorectal adenocarcinoma cell line DLD-1, and AML cell lines; THP-1 and HL60 upon treatment with U0126 (MEK inhibitor). B) Primary MLL-rearranged AML samples upon treatment with U0126. C) NBM samples upon treatment with U0126 D). Primary MLLrearranged AML samples upon treatment with KG-501 (CREB-1 inhibitor). E) NBM upon treatment with KG-501. F) Primary MLLrearranged AML samples upon treatment with JNKII inhibitor. G) NBM upon treatment with JNKII inhibitor. H) A sensitive and an insensitive primary MLL-rearranged patient sample upon treatment with IMC1121 (VEGFR-2 antibody). I) Bijlage 5.2 Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome

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AML cell lines THP-1, MOLM13 and HL60 upon treatment with IMC1121. * Indicates a significant decrease in cell survival. ** Indicates a significant decrease in cell survival that reached the IC50.

By using RPPA the group of Kornblau demonstrated that there were recurrent patterns of protein expression in adult AML samples (Fig. 4) (Kornblau et al., 2009). Proteins from each constellation could be grouped in Signature groups (Fig. 5). These signature groups were found to have significant correlation with outcome. Figure 4. Heat map showing protein expression of 176 proteins in 256 AML cases, clustered by protein constellation (xaxis) and ProExpSig (y-axis). Repetitive patterns of expression are visually evident.

Figure 5. Protein expression against Signature Groups (SG). Proteins were clustered into 10 constellations shown by the 10 colored boxes along the left axis and the yellow lines surrounding each constellation.


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Materials and methods Prior results RPPA: We are able to use the results of over 700 adult AML samples already analyzed for RPPA (Kornblau et al., 2009) and 250 identical samples analyzed for kinomics in the near future. A first pilot experiment of shipping material across the ocean demonstrated reproducible results. Both methods, kinomics as well as proteomics, use a very low amount of material as mentioned above. These two platforms complement each other as many of the peptides used in the kinomics array are measured with phosphospecific antibodies used in the RPPA, while many others are the downstream targets of these phosphoproteins. Kinomics with Pepscan methodology: Arrays were constructed by chemically synthesizing soluble pseudo-peptides, which were covalently coupled to glass substrates. If the design of our peptide array is appropriate, addition of a purified kinase in the presence of ATP should result in the phosphorylation of the appropriate consensus peptide sequences without concomitant phosphorylation of other peptides. The protocol of the kinome array is described in detail at this website: www.pepscanpresto.com/index.php?id=15. Peptide sequences are derived from the human protein reference database: http://www.hprd.org, and in vitro phosphorylation of these peptides is described. Additional verification can come from the fact that for all peptides a corresponding phosphospecific antibody is available. The peptide arrays will be used and analysed as described earlier(Sikkema et al., 2009, ter Elst et al., 2011). Statistical analysis will be ongoing with the group of RC Jansen, Groningen. As shown in the prior result section clusters of activity will be identified and provisional signal transduction schemes will be made. Potential targets will be analysed in more detail and functional assays for specific inhibitors will be performed. Proteomics with RPPA methodology. To enable us to perform proteomic profiling we optimized the techniques necessary to perform RPPA on samples from patients with hematological malignancies. The methodology and validation of the technique are fully described in publications from the Kornblau laboratory.(Kornblau et al., 2006, 2009) The stained slides are analyzed using Microvigene® software to produce quantified data. Supercurve algorithms are used to generate a single value from the 5 serial dilutions. Loading control and topographical normalization (Neeley, In Press, Bioinformatics) procedures account for protein concentration and background staining variations. Analysis using unbiased clustering, perturbation bootstrap clustering and principle component analysis is then performed as fully described.(Kornblau et al., 2009) Integrating statistics. The statistical analysis as used before (Kornblau et al.,2009) of each dataset will include univariate analysis of each protein/peptide ascertaining expression level relative to the median group expression and correlation with clinical, laboratory and cytogenetic features as well as with outcome. Next we will perform unbiased clustering to look for constellations of proteins/peptides that have correlated expression followed by principle component analysis to look for recurrent signatures. The department of Genetics has substantial experience with datasets integrating DNA variation and other levels of molecular expression (see e.g. Fehrmann et al Plos One 2008, Dubois et al, Nature Genetics 2010, Fehrmann et al, PLoS Genetics 2011, Fu et al, PLoS Genetics 2012), including the analysis of expression data of cancer samples related to pathways and transcriptions factors (Crijns et al, PLoS Medicine 2009). Recently, the bioinformatics group has jointly analyzed gene expression data of 25,000 cancer samples, permitting us to determine cellular proliferation rates and metabolic activity. Handling these datasets allows us to study the complex relationships between increased cellular proliferation and increased metabolic activity in many different types of adulthood tumors (Fehrmann et al, manuscript in preparation). However, no such data exist on pediatric tumors and this makes the proposed work in pediatric AML unique. Moreover, with Dr Pe’er together we will learn a Bayesian network that integrates both the protein expression and kinomics in a step-wise manner as follows: We begin with the RPPA data alone and learn network structure as described in8. This structure will be the initial starting point of the second phase, in which we add a random variable for each peptide in the kinome array. Let Xp be a peptide corresponding to phospho-protein X and let Reg(X) be X’s regulators in the Bayesian network, then Bijlage 5.2 Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome

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we set Reg(X) to be Xp’s regulators as well. We use Bayesian network structure learning, enforcing shared regulators between X and Xp during the learning. Given two independent and complimentary measurements for X (total expression and kinomic potential) we gain a much more robust evaluation of the factors influencing X, the combination being more than a sum of each piece of evidence alone. This will provide insights into altered networks at the single patient level. Ex vivo drug target assay. For quantification of leukemia cell viability after drug inhibition, cell survival assays will be performed on primary leukemia samples. A WST-1 colorimetric viability assay protocol will be used (Roche). Cells will be seeded at a density of 4x10E4 cells per well in medium supplemented with 1% FBS. The cells will be subjected in quadruple to different concentrations of inhibitor and incubated at 37 °C for 48 hours. Absorbance will be measured at 450 nm in a microplate reader (Benchmark; Bio-Rad, Veenendaal, the Netherlands). The data are presented as the cell survival percentage relative to untreated cells. The LC50 value (drug concentration needed to kill 50% of the leukemic cells) will be used to compare differences between patients and/or various drugs combinations. LC50 value equation: ([% leukemic cell survival>50%]-50)/([% leukemic cell survival>50%]-[% leukemic cell survival<50%])×(drug concentration when leukemic cell survival<50%drug concentration when leukemic cell survival>50%)+(drug concentration when leukemic cell survival>50%). Requisted samples and data In the abovementioned preliminary results we already showed that we can analyze the signaling signatures in the preliminary tested small groups. The statisticians engaged in this project strongly recommend us to enlarge the group of patient samples and continue the project as a whole to obtain stronger integrative results for the reconstruction of molecular networks. We kindly ask you to join the project. Material requested: 25x106 viable AML cells after thawing (blood or bone marrow cells). The cells can be frozen and stored in the liquid nitrogen following standard procedures. Authorships: Each participating study group is allowed to supply one authorship. More authors can be discussed depending on the number of included patient samples.

References Crijns AP, Fehrmann RS, de Jong S, Gerbens F, Meersma GJ, Klip HG, Hollema H, Hofstra RM, te Meerman GJ, de Vries EG, van der Zee AG. Survival-related profile, pathways, and transcription factors in ovarian cancer. PLoS Med. 2009 Feb 3;6(2):e24. Dubois PC, Trynka G, Franke L, Hunt KA, Romanos J, Curtotti A, Zhernakova A, Heap GA, Adány R, Aromaa A, Bardella MT, van den Berg LH, Bockett NA, de la Concha EG, Dema B, Fehrmann RS, Fernández-Arquero M, Fiatal S, Grandone E, Green PM, Groen HJ, Gwilliam R, Houwen RH, Hunt SE, Kaukinen K, Kelleher D, KorponaySzabo I, Kurppa K, MacMathuna P, Mäki M, Mazzilli MC, McCann OT, Mearin ML, Mein CA, Mirza MM, Mistry V, Mora B, Morley KI, Mulder CJ, Murray JA, Núñez C, Oosterom E, Ophoff RA, Polanco I, Peltonen L, Platteel M, Rybak A, Salomaa V, Schweizer JJ, Sperandeo MP, Tack GJ, Turner G, Veldink JH, Verbeek WH, Weersma RK, Wolters VM, Urcelay E, Cukrowska B, Greco L, Neuhausen SL, McManus R, Barisani D, Deloukas P, Barrett JC, Saavalainen P, Wijmenga C, van Heel DA. Multiple common variants for celiac disease influencing immune gene expression. Nat Genet. 2010 Apr;42(4):295-302 Ter Elst A, Diks SH, Kampen KR, et al. Identification of new possible targets for leukemia treatment by kinase activity profiling. Leuk Lymphoma. 2011;52:122-130. Fehrmann RS, Jansen RC, Veldink JH, Westra HJ, Arends D, Bonder MJ, Fu J, Deelen P, Groen HJ, Smolonska A, Weersma RK, Hofstra RM, Buurman WA, Rensen S, Wolfs MG, Platteel M, Zhernakova A, Elbers CC, Festen EM, Bijlage 5.2 Integrating proteomics and kinomics in pediatric acute myeloid leukemia (AML): detailed cellular insights to improve outcome

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Trynka G, Hofker MH, Saris CG, Ophoff RA, van den Berg LH, van Heel DA, Wijmenga C, Te Meerman GJ, Franke L. Trans-eQTLs reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the HLA. PLoS Genet. 2011 Aug;7(8):e1002197 Fu J, Wolfs MG, Deelen P, Westra HJ, Fehrmann RS, Te Meerman GJ, Buurman WA, Rensen SS, Groen HJ, Weersma RK, van den Berg LH, Veldink J, Ophoff RA, Snieder H, van Heel D, Jansen RC, Hofker MH, Wijmenga C, Franke L. Unraveling the regulatory mechanisms underlying tissue-dependent genetic variation of gene expression. PLoS Genet. 2012 Jan;8(1):e1002431. Fuchs SA, de Sain-van der Velden MG, de Barse MM, Roeleveld MW, Hendriks M, Dorland L, Klomp LW, Berger R, de Koning TJ. Two mass-spectrometric techniques for quantifying serine enantiomers and glycine in cerebrospinal fluid: potential confounders and age-dependent ranges. Clin Chem. 2008;54:1443-1450. Jain M, Nilsson R, Sharma S, Madhusudhan N, Kitami T, Souza AL, Kafri R, Kirschner MW, Clish CB, Mootha VK Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation. Science. 2012;336:10401044. Kornblau SM, Womble M, Qiu YH, et al. Simultaneous activation of multiple signal transduction pathways confers poor prognosis in acute myelogenous leukemia. Blood. 2006;108:2358-2365. Kornblau SM, Tibes R, Qiu YH, et al. Functional proteomic profiling of AML predicts response and survival. Blood. 2009;113:154-164. Ma X, Park Y, Mayne ST, Wang R, Sinha R, Hollenbeck AR, Schatzkin A, Cross AJ. Diet, lifestyle, and acute myeloid leukemia in the NIH-AARP cohort. Am J Epidemiol. 2010;171:312-322. Possemato R, Marks KM, Shaul YD, Pacold ME, Kim D, Birsoy K, Sethumadhavan S, Woo HK, Jang HG, Jha AK, Chen WW, Barrett FG, Stransky N, Tsun ZY, Cowley GS, Barretina J, Kalaany NY, Hsu PP, Ottina K, Chan AM, Yuan B, Garraway LA, Root DE, Mino-Kenudson M, Brachtel EF, Driggers EM, Sabatini DM. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature. 2011;476:346-350. Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP. Causal protein-signaling networks derived from multiparameter single-cell data. Science. 2005 Apr 22;308(5721):523-9. Kinome profiling in pediatric brain tumors as a new approach for target discovery.Sikkema AH, Diks SH, den Dunnen WF, ter Elst A, Scherpen FJ, Hoving EW, Ruijtenbeek R, Boender PJ, de Wijn R, Kamps WA, Peppelenbosch MP, de Bont ES. Cancer Res. 2009 Jul 15;69(14):5987-95. Epub 2009 Jun 30. Visser WF, Verhoeven-Duif NM, Ophoff R, Bakker S, Klomp LW, Berger R, de Koning TJ. A sensitive and simple ultra-high-performance-liquid chromatography-tandem mass spectrometry based method for the quantification of D-amino acids in body fluids. J Chromatogr A. 2011;1218:7130-7136. Wang R, Dillon CP, Shi LZ, Milasta S, Carter R, Finkelstein D, McCormick LL, Fitzgerald P, Chi H, Munger J, Green DR. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity. 2011;35:871-882.


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5.3

Prognostic relevance of detection Minimal Residual Disease for children with acute myeloid leukemia Dr. V.H.J. van der Velden (Immunology, ErasmusMC)* Dr V. de Haas (Central Laboratory DCOG) Prof. Dr. J.J.M. van Dongen (Immunology, ErasmusMC) * Corresponding author ErasmusMC Afdeling Immunologie Dr. Molewaterplein 50 3015 GE Rotterdam 010-704 42 53 [email protected]

1. Algemeen overzicht van het onderzoeksveld Clinical significance of MRD in childhood AML The prognosis of childhood acute myeloid leukemia (AML) has improved considerably over the past decades. The improvements are not only due to intensified chemotherapy, but also to improvements in supportive care, such as antifungal prophylaxis and treatment, as well intensive care and blood product support. Despite these improvements, 30-40% of patients suffer from a relapse, indicating that the current cytotoxic therapy regimens are not always able to kill all malignant cells. Furthermore, the improvement in prognosis is achieved using very intensive chemotherapy, which may result in significant acute toxicity (e.g. mucositis and infections) and late toxicity (e.g. anthracycline-induced cardiomyopathy). To limit unwanted side-effects, it is important to recognize those patients that need intensive therapy for survival and those patients who can be cured with the current treatment protocols, or who may even profit from treatment reduction. Several studies have shown that detection of minimal residual disease (MRD) in AML is an independent prognostic factor. 1-9 Most MRD studies in AML have focused on adults, and relatively little is known about MRD in childhood AML. Sievers et al. showed that, in a retrospective flowcytometric MRD study, the relative risk of relapse in MRD-positive pediatric AML patients was 2.8 times the risk of relapses in MRD-negative patients. 3 MRD was monitored using a standard 3color immunophenotyping protocol and occult leukemia was defined as more than or equal to 0.5% blasts with aberrant surface antigen expression. Also in a more recent study from the same group, using a comparable flowcytometric approach and the same cut-off level of 0.5%, it could be shown that patients with occult leukemia after induction therapy were almost 5 times more likely to relapse than those lacking detectable MRD. 4 A flowcytometric study by Coustan-Smith et al. showed that pediatric AML patients with MRD levels >0.1% after induction therapy had a 2-year survival estimate of 33%, whereas this was 72% for MRD-negative patients. 1 In this 4-color flowcytometric study, an leukemia-associated immunophenotype (LAIP) was detected in 85% of patients and, using patienttailored labelings, sensitivities of 0.1%-0.01% were obtained. In the recent study of the MRD-AMLBFM Study Group 2, a standard four-color flowcytometric analysis was used with cut-off values dependent on the time-point and specificity of the LAIP. MRD positivity before second induction was associated with a more than 2-fold risk of relapse, but MRD was no longer significant in multivariate analysis. 2 In conclusion, currently available data show that MRD analysis in childhood AML can be of prognostic relevance. However, more work is required to further optimize the flowcytometric MRD analysis and additional studies are required in order to determine the most optimal time point(s) and cut-off level for MRD analysis in childhood AML.

Bijlage 5.3 Prognostic relevance of detection Minimal Residual Disease for children with acute myeloid leukemia

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Recent developments in flowcytometric MRD analysis Flowcytometric immunophenotyping so far has mainly been limited due to its applicability and sensitivity. However, the introduction of 3-color immunophenotyping in the early nineties and the introduction of 4-color immunophenotyping in the late nineties have significantly improved its applicability and sensitivity. When using 3-color immunophenotyping, an aberrant immunophenotype could only be found in about 60% of childhood ALL cases,10 but the introduction of 4-color immunophenotyping increased this frequency to over 90%.11 Consequently, it can be expected that the recent introduction of 8-color flowcytometers will further improve the applicability and sensitivity of MRD detection in childhood acute leukemia. Within the EuroFlow network, 12 8color immunostaining protocols have been designed for all hematological malignancies, including AML. These 8-color immunostaining protocol have been optimized for use with the new Infinicyt software, which allows true multiparameter analysis of flowcytometric data.13-14 Flowcytometric immunophenotyping not only has the advantage of being fast en cheap, it also has the advantage of analysis at the single cell level. This is particularly important because childhood acute leukemia cells (especially AML) may be heterogeneous 15 and different subpopulations may respond to therapy differently.16-18 This heterogeneity may be due to the fact that an acute leukemia arises from a small population of ‘cancer stem cells’ that gives rise to phenotypically diverse cancer cells, with less proliferative potential. Several studies have shown that such ‘cancer stem cells’ can be found in AML 19-22 and that these leukemic stem cells possess extensive proliferative capacity and the potential for self-renewal. The possibility that only a small minority of AML cells (<0.01%-10%) have the ability to act as stem cells in vivo and maintain the malignant population has important therapeutic significance, as these cells may be the only relevant target cells for treatment protocols.23 Furthermore, characterization of the leukemic stem cell in AML is fundamental in order to gain insight into the composition of the leukemic clone and into the cellular and molecular mechanisms that underlie leukemogenesis. Immunophenotyping, culture of sorted cells, and leukemic repopulation in NOD/SCID mice, revealed that the immunophenotype of the stem cell probably is CD34+/CD38-/lin-/HLA-DR-/CD71-/Hoechst 33342 efflux+/CD90+/CD123-.19,20,22-25 Also CD117 and CD133 may be expressed on normal stem cells.26 Interestingly, leukemic stem cells may show a slightly different immunophenotype, being Hoechst 33342-efflux-/CD90-/CD123+;22,24-26 also CD132 may only be present on leukemic stem cells.27 Identification of leukemic stem cells at diagnosis and flowcytometric monitoring of these cells during treatment should give more insight in true treatment efficacy, because it might well be that leukemic stem cells and the other (more mature) leukemic cells differ in treatment sensitivity.28-29

2. Doel/vraagstelling van het onderzoek The here proposed clinical research project has the following aims: 1. To investigate whether flowcytometric MRD detection in childhood AML can be improved in order to detect an aberrant immunophenotype in over 95% of patients and to reach sensitivities which are consistently at least 0.01%, preferably 0.001%. Such improvement should particularly be possible by the introduction of 8-color flowcytometric immunophenotyping in combination with the new Infinicyt software. To support the flowcytometric MRD data, MRD data obtained via RT-PCR analysis of fusion gene transcripts derived from chromosome aberrations and/or FLT3ITD will be used. 2. To evaluate the clinical value of MRD in childhood AML by monitoring of MRD during treatment at predefined sampling points. - To determine the prognostic value of the dynamics of tumor-load reduction during induction therapy and thereafter and to analyze whether MRD information can be used for risk group stratification (recognition of low-risk, intermediate-risk, and high-risk groups).


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To determine whether a reappearance of MRD or increase in MRD after stop of therapy is related to relapse. - To determine the prognostic sigmicicance of MRD prior to and after stem cell transplantation. - To determine the correlation between MRD results and known prognostic factors like FAB classification and cytogenetic data. 3. To obtain insight in the characteristics of the leukemic cell subsets, particularly leukemic stem cells, at diagnosis and to monitor these subpopulations by flowcytometry during treatment. -

3.

De relevantie van het onderzoek voor leukemie op de kinderleeftijd

In tegenstelling tot acute lymfatische leukemie, is er bij AML een veel grotere recifiefkans. Zelfs in de "good risk" groep bestaat nog een aanzienlijke kans op recidief. Daarnaast is vroege detectie van een recidief klinisch relevant omdat met een kleinere tumormassa de kans op remissie-herinductie mogelijk groter is en omdat meer tijd beschikbaar is voor het uitwerken van alternatieve behandelingsopties. Gezien onze eerdere resultaten van flowcytometrische bepaling van MRD bij kinderen met ANLL, behandeld met de voorafgaande protocollen (SNWLK ANLL-97, MRC AML 12 en 15), is het zinvol om deze resultaten uit te breiden. Inmiddels is de techniek veel gevoeliger geworden (uitbreiding van 4kleuren naar 8-kleuren flow) en dit zal bijdragen tot een optimalisatie van techniek en uitkomsten. Dit biedt de mogelijkheid vroeger in de behandeling in te grijpen in de therapie, daarnaast zal het mogelijk zijn een patient met een verdenking recidief sneller op te sporen en dus adequater te behandelen.

4.

Eventuele preliminaire resultaten

A. Data from the MRC AML12/DCOG ANLL97 study During the last years we evaluated MRD in 98 pediatric AML patients treated within the AML12/ANLL97 protocol. Bone marrow samples were obtained at diagnosis, before the second course (TP2; n=61), before the third (MACE) course (TP3; n=31), before the second randomisation (TP4; n=27), and at the end of treatment (TP5; n=31).

Identification of LAIP at diagnosis Flowcytometric immunophenotyping at diagnosis confirmed the presence of an acute myeloid leukemia in all cases. In 85% of patients, subpopulations (20% of leukemic cells) could be observed for at least one antigen. In order to limit the risk of false negative MRD results, preferably two or more LAIPs were therefore monitored per patient. This was possible in 68% of cases; in 32% of patients only one LAIP could be defined, and no LAIP could be defined in 6% of patients (this concerned one FAB-M1, one FAB-M2, two FAB-M4, and two FAB-M5). In 61% of LAIPs a sensitivity of at least 0.01% was achieved, in all cases the sensitivity was at least 0.1%. In conclusion, flowcytometric MRD analysis reaching a sensitivity of minimally 0.1% (10-3) is possible in the vast majority of pediatric AML patients. MRD levels at various time-points Out of the 96 patients alive after the first course, 11 patients not being in complete hematological remission were excluded for MRD analysis. As shown in Figure 1A, MRD levels slowly decreased at


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later time points. Comparison between patients who ultimately relapsed and those who remained in remission showed that MRD levels before the second course (TP2) and before the third course (TP3) were significantly higher in relapsing patients (Figure 1B), whereas no difference was observed before second randomization (TP4) and at the end of therapy (TP5).

Figure 1. MRD levels during follow-up. A. MRD levels before the second course (TP2), before the thirds course (TP3), before the second randomization (TP4), and at the end of treatment (TP5). B. Mean (±SE) MRD levels during and after therapy for patients remaining in remission (open symbols) and patients who relapsed (closed symbols). *: p<0.05 between both groups (Mann Whitney test).

Prognostic significance of MRD in the MRC-AML12/DCOG ANLL97 protocol For all time points evaluated, patients were classified in three groups according to their MRD level: MRD-Low risk if the MRD level was within the first tertile; MRD-Medium risk if the MRD level was within the second tertile; and MRD-High risk if the MRD level was within the third tertile. As shown in Figure 2A, MRD levels before the second course (TP2) were significantly related to the risk of relapse. MRD-Low risk patients (n=20) had a 5-year relapse free survival of 81%±9%, MRD-Medium risk patients (n=21) had a 5-y RFS of 65%±11%, and MRD-High risk patients (n=20) had a 5-y RFS of only 15%±8% (p[log rank]<0.0001). MRD-based risk group classification at TP2 was also significantly related to overall survival (p[log rank]<0.0001) (Figure 2B). At TP3 MRD levels were significantly related to the risk of relapse: the 5-y RFS for the MRD-Low risk (n=10), Medium risk (n=11), and High risk (n=10) was 67%±16%, 90%±9%, and 27%±13%, respectively (p[log rank]<0.01). MRD-based risk group classification at TP3 was also significantly related to overall survival: MRD-Low risk, Medium risk, and High risk had on overall survival of 56%±17%, 91%±9%, and 20%±13%, respectively (p[log rank]<0.05) MRD at later time points was not significantly associated with relapse-free or overall survival, also not if other cut-off points were used (data not shown). Combining MRD information at two subsequent time points did not provide additional prognostic information (data not shown). Since the minimum sensitivity of the flowcytometric MRD analysis was 0.1%, we also grouped patients for the various time-points in MRD negative (MRD level <0.1%) and MRD-positive (MRD level0.1%). At TP2, MRD-negative patients (n=22; 35%) had a significant higher RFS than MRD positive patients (n=40; 65%): 81%±9% versus 38%±8% (p[log rank]<0.01)(Figure 2C). Also overall survival was significantly better in the MRD-negative patients (85%±8% versus 50%±8%; p[log rank]<0.01) (Figure 2D). At other time-points, this classification had no prognostics significance.


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Figure 2. Probability of Relapse-free and overall survival according to MRD. Based on MRD levels before the second course (TP2), patients were classified as MRD-high risk, MRD-medium risk, or MRDlow risk (according to MRD tertiles, see text for details) or classified as MRD-negative (MRD<0.1%) or MRD positive (MRD0.1%). All patients included were in morphological remission at TP2. A and B: Relapse-free survival for the various MRD-based risk groups; C and D: Overall survival for the various MRD-based risk groups.

MRD is an independent prognostic factor To evaluate whether MRD (positive vs. negative) was an independent prognostic factor, multivariate analysis including age, the presence or absence of fusion gene transcripts, the presence of absence of FLT3-ITD and MRD before the second course was performed. This analysis showed that MRD at TP2 was an independent prognostic parameters for relapse-free survival. MRD at TP2 also maintained it prognostic significance for overall survival in multivariate analysis.

Stability of LAIP between diagnosis and relapse To investigate whether immunophenotypic shifts occurred between diagnosis and relapse, we compared the immunophenotypes of 27 out of 41 relapsed patients from who paired diagnosis and relapse samples were available. Immunophenotypic shifts at relapse were frequently observed: in 21 out of 27 paired diagnosis and relapse samples (78%), an immunophenotypic shift was observed. We


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observed that CD34, CD117, and HLA-DR were more frequently gained at relapse, whereas CD14, CD11b, and CD15 were more frequently lost at relapse, suggesting that the immunophenotype at relapse was more immature. Of importance, in 23 out of the 27 (85%) relapsed AML patients in our study, detection of MRD would have been possible using the patient-tailored labeling(s). In four patients, a part of the leukemic cells at relapse would have been missed using the LAIP labelings. However, all these four relapsed patients were classified as MRD-High risk at TP2, indicating that the immunophenotypic shift at relapse did not hamper reliable MRD detection at this early time point. At TP3, two patients were classified as MRD-High risk and one patient as MRD-Low risk (no data available for fourth patient).

B. Molecular MRD analysis Our laboratory has ample experience in the detection of fusion gene transcripts associated with chromosomal translocations, including AML1-ETO, PML-RARA, and CBFB-MYH11, and coordinated several international networks in this files (BIOMED-1 Concerted Action.30, ‘Europe Against Cancer’ study.31,32). In addition, the presence of FLT3-ITD is analyzed by RT-PCR analysis and expression of WT1 is determined according to international standardization protocols (European LeukemiaNet;).33,34 In the 98 pediatric AML patients analyzed within the AML12/ANLL97 protocol, AML1-ETO and CBFBMYH11 fusion gene transcripts were detected in 15% and 5% of patients, respectively. FLT3-ITD were detected in 19% of patients, including one patient with AML1-ETO. FLT3-ITD were however lost at relapse in four out of seven patients (57%) in our study; this instability of FLT3-ITD between diagnosis and relapse may hamper its use as MRD target. C. New flowcytometric approaches

Within the EuroFlow network (EU-FP6 LSHC-CT-2006-018708), coordinated by the Department of Immunology, Erasmus MC, and with participation by the DCOG, 8-color immunophenotyping protocols have been designed and standardized. Using new Infinicyt software tools, markers most informative in separating AML cells from normal myeloid cells can automatically be obtained, thereby allowing a more objective and reliable MRD analysis. In addition, the new Infinicyt software will facilitate the recognition of low numbers of residual AML cells between normal (regenerating) myeloid cells.13-14

5. Een (korte) beschrijving van de te gebruiken onderzoekmethoden Voor de MRD detectie zal vooral gebruik worden gemaakt van flowcytometrische MRD detectie en van RQ-PCR gemediëerde MRD detectie van fusiegentranscripten of andere genetische afwijkingen, zoals FLT3-ITD en WT-1. Voor de flowcytometrische MRD analyse zullen patiënten bij diagnose worden getypeerd middels de EuroFlow 8-kleuren panels. Op basis van het immunofenotype zullen middels de Infinicyt software markers worden gedefinieerd die het bese de AML cellen onderscheiden van normale myeloide cellen. Op basis van deze gegevens zullen patient-specifieke 8-kleuren labelingen worden ontwikkeld en ingezet bij diagnose en later tijdens follow-up. De Infinicyt software zal gebruikt worden om residuele AML cellen te onderscheiden van aanwezige normale myeloide cellen. Daarnaast zullen


38


AML stamcellen zowel bij diagnose als tijdens follow-up worden geanalyseerd middels een 8-kleuren labeling. Hoewel het percentage ANLL patiënten met een geschikt RT-PCR target beperkt is (25 à 50%), kan deze MRD techniek wel degelijk relevant zijn voor de studie als aanvulling op en ondersteuning van de flowcytometrische MRD detectie. Toevoegen van deze MRD techniek is makkelijk haalbaar, omdat binnen de BIOMED-1 Concerted Action gestandaardiseerde primer sets zijn ontwikkeld voor de meest voorkomende chromosoomafwijkingen bij ANLL. Daarnaast zijn binnen het ‘Europe Against Cancer Project’ primer/probe sets ontworpen voor de gevoelige en kwantitatieve detectie van fusiegentranscripten gedurende follow-up. De aanwezigheid van FLT3-ITD en overexpressie van WT-1 kunnen worden gedetecteerd met recent opgezette RQ-PCR technieken.

6. Tijdstip van onderzoek, benodigde monsters Bij diagnose wordt het aan te leveren bloed- en beenmergmonster onderzocht op het voorkomen van een aberrant immunofenotype. Naar aanleiding hiervan zullen de beide laboratoria gezamenlijk "patiënt-specifieke" achtvoudige labelingen samenstellen voor flowcytometrische MRD detectie in follow-up monsters. Daarnaast zal bij diagnose worden vastgesteld of er fusiegentranscripten, FLT3ITD, of WT-1 overexpressie aanwezig zijn. Het MRD onderzoek zal plaatsvinden bij alle beenmergmonsters, die in het kader van de behandeling worden afgenomen: na 15 dagen inductietherapie, na ieder behandelingsblok, bij einde behandeling en vervolgens 3-maandelijks in het eerste jaar. Daarnaast zullen ook eventuele recidiefmonsters worden geanalyseerd om vast te stellen of, en zo ja in welke mate, het immunofenotype is veranderd. Deze tijdstipppen vallen samen met de reguliere beenmergpuncties om de remissiestatus vast te stellen. Om zo zorgvuldig mogelijk met materiaal om te springen, is deze add-on studie volledig afgestemd met de add-on studie van Cloos et al., waarbij uitwisseling van gegevens wederzijds zal gebeuren, alsmede zn uitwisseling van restmateriaal. Voor uitgebreide beschrijving van deze logistiek, verwijzen wij u naar de add-on studie van Cloos et al.

7. Kwantificering van het aantal patiënten, toekomstperspectief In Nederland worden ongeveer 25-30 kinderen met ANLL per jaar gediagnosticeerd. Daarnaast zullen ook de Belgische patiënten deelnemen aan deze studie, hun aantal wordt geschat op 10-15 patienten per jaar. Dit betekent reëel een inclusie van ongeveer 30 patienten (uitval door te weinig materiaal, geen informed consent). Totaal zal in een periode van vier jaar daarom maximaal 120 kinderen in de MRD studie worden opgenomen. Alhoewel deze aantallen vrij beperkt zijn om de klinische betekenis van MRD in kinderen met AML zeer betrouwbaar vast te stellen, zullen ze in combinatie met de MRD data verkregen in AML12/ANLL97 en AML15 mogelijk voldoende basis vormen voor MRD-gebaseerde stratificatie in toekomstige Nederlandse AML behandelingsprotocollen.

8. Coördinatie Het flowcytometrisch MRD onderzoek van de Nederlandse kinderen zou moeten worden uitgevoerd door het SKION laboratorium in nauwe samenwerking met afdeling Immunologie van het Erasmus MC. De RT-PCR studies van de Nederlandse kinderen met AML zullen worden uitgevoerd door de afdeling Immunologie van het Erasmus MC.


39


LITTERATUUR 1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12. 13. 14.

15.

16.

17.

18.

19. 20.

Coustan-Smith E, Ribeiro RC, Rubnitz JE, Razzouk BI, Pui CH, Pounds S, Andreansky M, Behm FG, Raimondi SC, Shurtleff SA, Downing JR, Campana D. Clinical significance of residual disease during treatment in childhood acute myeloid leukaemia. Br J Haematol 2003; 123: 243-252. Langebrake C, Creutzig U, Dworzak M, Hrusak O, Mejstrikova E, Griesinger F, Zimmermann M, Reinhardt D. Residual disease monitoring in childhood acute myeloid leukemia by multiparameter flow cytometry: the MRD-AML-BFM Study Group. J Clin Oncol 2006; 24: 3686-3692. Sievers EL, Lange BJ, Buckley JD, Smith FO, Wells DA, Daigneault-Creech CA, Shults KE, Bernstein ID, Loken MR. Prediction of relapse of pediatric acute myeloid leukemia by use of multidimensional flow cytometry. J Natl Cancer Inst 1996; 88: 1483-1488. Sievers EL, Lange BJ, Alonzo TA, Gerbing RB, Bernstein ID, Smith FO, Arceci RJ, Woods WG, Loken MR. Immunophenotypic evidence of leukemia after induction therapy predicts relapse: results from a prospective Children's Cancer Group study of 252 patients with acute myeloid leukemia. Blood 2003; 101: 3398-3406. Kern W, Voskova D, Schoch C, Hiddemann W, Schnittger S, Haferlach T. Determination of relapse risk based on assessment of minimal residual disease during complete remission by multiparameter flow cytometry in unselected patients with acute myeloid leukemia. Blood 2004; 104: 3078-3085. San Miguel JF, Martinez A, Macedo A, Vidriales MB, Lopez-Berges C, Gonzalez M, Caballero D, Garcia-Marcos MA, Ramos F, Fernandez-Calvo J, Calmuntia MJ, Diaz-Mediavilla J, Orfao A. Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood 1997; 90: 24652470. San Miguel JF, Vidriales MB, Lopez-Berges C, Diaz-Mediavilla J, Gutierrez N, Canizo C, Ramos F, Calmuntia MJ, Perez JJ, Gonzalez M, Orfao A. Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification. Blood 2001; 98: 1746-1751. Venditti A, Buccisano F, Del Poeta G, Maurillo L, Tamburini A, Cox C, Battaglia A, Catalano G, Del Moro B, Cudillo L, Postorino M, Masi M, Amadori S. Level of minimal residual disease after consolidation therapy predicts outcome in acute myeloid leukemia. Blood 2000; 96: 3948-3952. Venditti A, Tamburini A, Buccisano F, Del Poeta G, Maurillo L, Panetta P, Scornajenghi KA, Cox C, Amadori S. Clinical relevance of minimal residual disease detection in adult acute myeloid leukemia. J Hematother Stem Cell Res 2002; 11: 349-357. Coustan-Smith E, Behm FG, Sanchez J, Boyett JM, Hancock ML, Raimondi SC, Rubnitz JE, Rivera GK, Sandlund JT, Pui CH, Campana D. Immunological detection of minimal residual disease in children with acute lymphoblastic leukaemia. Lancet 1998; 351: 550-554. Coustan-Smith E, Sancho J, Hancock ML, Boyett JM, Behm FG, Raimondi SC, Sandlund JT, Rivera GK, Rubnitz JE, Ribeiro RC, Pui CH, Campana D. Clinical importance of minimal residual disease in childhood acute lymphoblastic leukemia. Blood 2000; 96: 2691-2696. van Dongen JJM, Orfao A, van der Velden VHJ, et al. The future of clinical cell analysis for diagnosis, classification and monitoring of hematological malignancies. Cytometry B. 2008; 74B: 64-65. Pedreira CE, Costa ES, Barrena S, Lecrevisse Q, Almeida J, van Dongen JJ, Orfao A, on behalf of EuroFlow C. Generation of flow cytometry data files with a potentially infinite number of dimensions. Cytometry A 2008 Pedreira CE, Costa ES, Almeida J, Fernandez C, Quijano S, Flores J, Barrena S, Lecrevisse Q, Van Dongen JJ, Orfao A; EuroFlow Consortium. A probabilistic approach for the evaluation of minimal residual disease by multiparameter flow cytometry in leukemic B-cell chronic lymphoproliferative disorders. Cytometry A. 2008 Dec;73A(12):1141-50. San Miguel JF, Ciudad J, Vidriales MB, Orfao A, Lucio P, Porwit-MacDonald A, Gaipa G, van Wering E, van Dongen JJ. Immunophenotypical detection of minimal residual disease in acute leukemia. Crit Rev Oncol Hematol 1999; 32: 175185. de Haas V, Verhagen OJ, von dem Borne AE, Kroes W, van den Berg H, van der Schoot CE. Quantification of minimal residual disease in children with oligoclonal B-precursor acute lymphoblastic leukemia indicates that the clones that grow out during relapse already have the slowest rate of reduction during induction therapy. Leukemia 2001; 15: 134140. Konrad M, Metzler M, Panzer S, Ostreicher I, Peham M, Repp R, Haas OA, Gadner H, Panzer-Grumayer ER. Late relapses evolve from slow-responding subclones in t(12;21)-positive acute lymphoblastic leukemia: evidence for the persistence of a preleukemic clone. Blood 2003; 101: 3635-3640. Baer MR, Stewart CC, Dodge RK, Leget G, Sule N, Mrozek K, Schiffer CA, Powell BL, Kolitz JE, Moore JO, Stone RM, Davey FR, Carroll AJ, Larson RA, Bloomfield CD. High frequency of immunophenotype changes in acute myeloid leukemia at relapse: implications for residual disease detection (Cancer and Leukemia Group B Study 8361). Blood 2001; 97: 3574-3580. Bonnet D and Dick JE. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med 1997; 3: 730-737. Lapidot T, Sirard C, Vormoor J, Murdoch B, Hoang T, Caceres-Cortes J, Minden M, Paterson B, Caligiuri MA, Dick JE. A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 1994; 367: 645-648.


40

NOPHO-DBH AML 2012 protocol Nederlandse bijlagen 21. 22. 23. 24.

25. 26. 27.

28.

29.

30.

31.

32.

33.

34.

Wittebol S, Raymakers R, van de Locht L, Mensink E, de Witte T. In AML t(8;21) colony growth of both leukemic and residual normal progenitors is restricted to the CD34+, lineage-negative fraction. Leukemia 1998; 12: 1782-1788. Blair A, Hogge DE, Ailles LE, Lansdorp PM, Sutherland HJ. Lack of expression of Thy-1 (CD90) on acute myeloid leukemia cells with long-term proliferative ability in vitro and in vivo. Blood 1997; 89: 3104-3112. Blair A, Hogge DE, Sutherland HJ. Most acute myeloid leukemia progenitor cells with long-term proliferative ability in vitro and in vivo have the phenotype CD34(+)/CD71(-)/HLA-DR. Blood 1998; 92: 4325-4335. Jordan CT, Upchurch D, Szilvassy SJ, Guzman ML, Howard DS, Pettigrew AL, Meyerrose T, Rossi R, Grimes B, Rizzieri DA, Luger SM, Phillips GL. The interleukin-3 receptor alpha chain is a unique marker for human acute myelogenous leukemia stem cells. Leukemia 2000; 14: 1777-1784. Feuring-Buske M and Hogge DE. Hoechst 33342 efflux identifies a subpopulation of cytogenetically normal CD34(+)CD38(-) progenitor cells from patients with acute myeloid leukemia. Blood 2001; 97: 3882-3889. Baersch G, Baumann M, Ritter J, Jurgens H, Vormoor J. Expression of AC133 and CD117 on candidate normal stem cell populations in childhood B-cell precursor acute lymphoblastic leukaemia. Br J Haematol 1999; 107: 572-580. Hao QL, Barsky LW, Yao D, Bockstoce D, Payne KJ, Petersen D, Ertl D, Amis J, Nolta JA, Parkman R, Weinberg KI, Crooks GM. Functionally different subpopulations of CD34+CD38-hematopoietic progenitors are defined by differential common gamma chain (gamma c) expression. Blood 1999; 94: 1120 (part 1121 suppl.). van Rhenen A, Moshaver B, Kelder A, Feller N, Nieuwint AW, Zweegman S, Ossenkoppele GJ, Schuurhuis GJ. Aberrant marker expression patterns on the CD34+CD38- stem cell compartment in acute myeloid leukemia allows to distinguish the malignant from the normal stem cell compartment both at diagnosis and in remission. Leukemia 2007; 21: 1700-1707. van Rhenen A, van Dongen GA, Kelder A, Rombouts EJ, Feller N, Moshaver B, Stigter-van Walsum M, Zweegman S, Ossenkoppele GJ, Jan Schuurhuis G. The novel AML stem cell associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells. Blood 2007; 110: 2659-2666. van Dongen JJ, Macintyre EA, Gabert JA, Delabesse E, Rossi V, Saglio G, Gottardi E, Rambaldi A, Dotti G, Griesinger F, Parreira A, Gameiro P, Diaz MG, Malec M, Langerak AW, San Miguel JF, Biondi A. Standardized RT-PCR analysis of fusion gene transcripts from chromosome aberrations in acute leukemia for detection of minimal residual disease. Report of the BIOMED-1 Concerted Action: investigation of minimal residual disease in acute leukemia. Leukemia 1999; 13: 1901-1928. Gabert J, Beillard E, van der Velden VH, Bi W, Grimwade D, Pallisgaard N, Barbany G, Cazzaniga G, Cayuela JM, Cave H, Pane F, Aerts JL, De Micheli D, Thirion X, Pradel V, Gonzalez M, Viehmann S, Malec M, Saglio G, van Dongen JJ. Standardization and quality control studies of 'real-time' quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia - a Europe Against Cancer program. Leukemia 2003; 17: 2318-2357. Beillard E, Pallisgaard N, van der Velden VH, Bi W, Dee R, van der Schoot E, Delabesse E, Macintyre E, Gottardi E, Saglio G, Watzinger F, Lion T, van Dongen JJ, Hokland P, Gabert J. Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using 'real-time' quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR) - a Europe against cancer program. Leukemia. 2003 Dec;17(12):2474-86. Willasch AM, Gruhn B, Coliva T, Kalinova M, Schneider G, Kreyenberg H, Steinbach D, Weber G, Hollink IH, Zwaan CM, Biondi A, van der Velden VH, Reinhardt D, Cazzaniga G, Bader P, Trka J. Standardization of WT1 mRNA quantitation for minimal residual disease monitoring in childhood AML and implications of WT1 gene mutations: a European multicenter study. Leukemia. 2009 Mar 26. [Epub ahead of print] Daniela Cilloni, Aline Renneville, Fabienne Hermitte, Robert K Hills, Sarah Daly, Jelena V Jovanovic, Enrico Gottardi, Milena Fava, Susanne Schnittger, Tamara Weiss, Barbara Izzo, Josep Nomdedeu, Adrian van der Heijden, Bert van der Reijden, Joop H Jansen, Vincent H.J van der Velden, Hans Ommen, Claude Preudhomme, Giuseppe Saglio and David Grimwade. Real-Time Quantitative PCR Detection of Minimal Residual Disease by Standardized WT1 assay to Enhance Risk Stratification in Acute Myeloid Leukemia: A European LeukemiaNet Study. J Clin Oncol 2009; in press.


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5.4

Predictive value of post-transplant minimal residual disease and myeloid progenitor chimerism in children with high-risk acute myeloid leukemia: a prospective study Dr. A.C. Lankester (WAKZ/LUMC)* Dr. M. Bierings (WKZ/UMCU) Dr. W.J.W. Kollen (WAKZ/LUMC) Dr. V. de Haas (SKION) Dr. V. vd Velden (ErasmusMC/Immunology) * Corresponding author WAKZ/ LUMC Afdeling Stamcel transplantatie Postbus 9600 2300 RC Leiden [email protected]

1

INTRODUCTION

During the last decade the overall survival of children with acute myeloid leukemia following treatment with intensive chemotherapy has significantly improved. Therefore, the indication for allogeneic stem cell transplantation in pediatric AML has become restricted to patients with a poor biological response in first remission (i.e refractory disease) and relapse AML. In these high risk AML patients, and despite myeloablative conditioning, relapses frequently occur, usually within the first 6-12 months after SCT (see also preliminary results). Therefore, in order to prevent disease recurrence, additional therapeutic interventions should be exploited either prior to (i.e. improving the preSCT remission status) or in the early postSCT period. Allo-reactive and antileukemic immune responses (known as ‘graft versus leukemia’) have been shown to be potentially beneficial in the prevention of relapse of myeloid leukemia. This can be achieved by early tapering of CsA, donor lymphocyte infusions and immune adjuvants [1,2]. Early tapering of CsA and DLI has been reported to be effective in reversing mixed chimerism in pediatric AML patients and often occurs in the absence of GvHD. In addition to DLI, leukemia-antigen specific T cell therapies and NK cell-based therapies are promising tools [3,4], but still experimental and general applicability is currently not feasible. Irrespective the mode of treatment, early and more accurate detection of imminent relapse postSCT would allow for interventions aimed at modifying disease outcome. Several studies have reported that frequent monitoring of peripheral blood chimerism may allow prediction of relapse in a subgroup of patients [5]. Thus, chimerism analysis may not only identify imminent relapse but may as such also provide a parameter to initiate meaningful immunotherapeutic interventions to prevent these relapses [6]. However, chimerism analyses in unfractionated blood have only limited sensitivity. The time between the reappearance of autologous cells (i.e. mixed chimerism) and AML relapse is often limited and therefore the therapeutic window is relatively short. Therefore, different and more sensitive assays are required to allow earlier recognition of recurrent autologous myeloid progenitors and/or leukemic cells. In acute lymphoblastic leukemia (ALL), MRD monitoring by either leukemia-specific DNA detection (using RQ-PCR) or flowcytometric immunophenotyping (multicolour FACS) has already entered the clinical arena [7,8] and is currently integrated in clinical decision making in both upfront chemotherapy protocols as well as in alloSCT protocols (eg. DCOG ALL-10, UK ALL-R3). Similarly, several studies have shown that detection of minimal residual disease (MRD) in AML is an independent prognostic factor [9-17] (please see also related study OC2009-018 for more details, as well as more details upon previous studies and preliminary results). So far most studies focussed on de novo AML patients and showed the prognostic significance of MRD detection. Very limited data are available for relapsed AML patients, particularly in children, and for the clinical significance of MRD levels post-SCT [18]. However, nowadays detailed phenotypic information of reference material

Bijlage 5.4 Predictive value of post-transplant minimal residual disease and myeloid progenitor chimerism in children with high-risk acute myeloid leukemia: a prospective study 42


will be available for most of the AML patients that will undergo alloSCT which will thus allow monitoring posttransplant. Flowcytometric immunophenotyping has the advantage of analysis at the single cell level. This is particularly important because childhood AML may be heterogeneous [14,19] and different subpopulations may respond to therapy differently [15]. This heterogeneity may be due to the fact that an AML arises from a small population of ‘cancer stem cells’ that gives rise to phenotypically diverse cancer cells, with less proliferative potential. Several studies have shown that such ‘cancer stem cells’ can be found in AML [16,17] and that these leukemic stem cells possess extensive proliferative capacity and the potential for self-renewal. Identification of leukemic stem cells at diagnosis and flowcytometric monitoring of these cells during treatment should give more insight in true treatment efficacy, because it might well be that leukemic stem cells and the other (more mature) leukemic cells differ in treatment sensitivity. In addition to flowcytometric monitoring, research is ongoing to improve MRD detection by molecular approaches including leukemia-restricted genes (eg. WT-1) and leukemia-specific chromosomal aberrations (eg. MLL rearrangements) [20-22]. In recent studies, evidence has been provided that these approaches may be instrumental to predict outcome in AML patients that undergo alloSCT [23-25]. However, further exploitation of these techniques to detect residual disease and/or autologous myeloid progenitors after transplantation as well as their clinical validation to predict relapse post-transplant in pediatric AML is required. 2

AIM OF THE STUDY

Primary aims: a. Study whether frequent measurement of myeloid progenitor chimerism improves (compared to standard chimerism in unfractionated blood) prediction of relapse. b. Study whether multicolor flowcytometric immunophenotyping analyses will identify MRD and predict relapse c. Study whether molecular detection of WT-1, FLT3-ITD and fusion gene products by RQ-PCR analyses will predict relapse Secondary aims d. Study whether aforementioned techniques will be instrumental to monitor the response to the conventional chimerism-guided immune intervention (see above). e. Study the impact of the interventions on immune reconstitution

3

RELEVANCE OF THE STUDY

Relapse leukemia is the major cause of treatment failure after alloSCT and mostly occurs within the first 6-12 months. In this study we will investigate whether flowcytometric immunophenotyping and chimerism analysis of progenitor populations as well as molecular detection of AML cells in bone marrow will prove to be feasible and can be used as reliable MRD markers. Eventually, this may lead to earlier and accurate identification of patients with imminent relapse and thereby create a window phase in which therapeutic interventions may be administered with the aim to modify disease outcome.

4

PRELIMINARY RESULTS

During the last years we evaluated MRD in 98 pediatric AML patients treated within the AML12/ANLL97 protocol. Bone marrow samples were obtained at diagnosis, before the second course (TP2; n=61), before the third (MACE) course (TP3; n=31), before the second randomisation Bijlage 5.4 Predictive value of post-transplant minimal residual disease and myeloid progenitor chimerism in children with high-risk acute myeloid leukemia: a prospective study 43


(TP4; n=27), and at the end of treatment (TP5; n=31). A detailed description of the results is provided in OC2009-018. Briefly, using flowcytometric immunophenotyping a leukemia-associated immunophenotype allowing a sensitivity of at least 0.1% could be detected in 94% of pediatric AML patients. MRD levels after the first course of chemotherapy predicted for clinical outcome: 3-year relapse-free survival was 85%±8% (SE) for MRD-based low-risk patients (MRD<0.1%), 64%±10% for MRD-based medium-risk patients (0.1%MRD<0.5%) and only 14±9% for MRD-based high-risk patients (MRD0.5%; p<0.001). Multivariate analysis showed that MRD after the first course of chemotherapy was an independent prognostic factor. These data show that flowcytometric MRD detection is possible in children with AML and that the level of MRD after the first course of chemotherapy provides prognostic information that may be used to guide therapy. Within the EuroFlow network (coordinated by Immunology, Erasmus MC, and with participation of DCOG) 8-color immunostaining protocols have recently been designed for all hematological malignancies, including AML. These 8-color immunostaining protocol have been optimized for use with the new Infinicyt software, which allows true multiparameter analysis of flowcytometric data [26,27]. It is anticipated that, using 8-color immunostainings, AML cells will better be distinguishable from normal myeloid cells, while the new software will allow a more objective analysis of data, both at diagnosis (defining leukemia-associated immunophenotypes) and during follow-up (determining MRD). This certainly will further improve the applicability and sensitivity of MRD detection in childhood AML. Since 2003 n=33 pediatric AML patients have been transplanted in the LUMC. Of these, 73% were transplanted in second remission. As shown in fig 1. most relapses presented within the first 6-12 months post alloSCT. This indicates that frequent sampling in this period will be required to detect imminent relapses. Fig.1 Relapse free survival in AML patients (CR1/CR2) in LUMC (n=27)

5

DESCRIPTION OF STUDY METHODS

Bone marrow and blood samples will taken according to the scheme below. All flowcytometry samples will be send to the SKION laboratory and analyzed freshly for optimal phenotypic characterization and to avoid loss of antigenic determinants during cryopreservation/thawing procedures. RNA will be isolated and stored in the SKION lab for future RQ-PCR analyses. Unfractionated bone marrow and blood mononuclear cells as well as BM progenitor cell fractions will be freshly sorted and analyzed for chimerism in the SCT centers LUMC and WKZ/UMCU.



Sampling scheme Bone marrow aspirates and blood samples will be taken at: Day 30, 60, 90, 120, 180, 240, 300, 360 after alloSCT

MRD and progenitor cell chimerism analysis MRD will be analyzed in all patients by 8-color immunophenotyping. At diagnosis, the recently developed EuroFlow labelings will be used to establish the detailed immunophenotype of the AML. Subsequently, INFINICYT® software will be used to define what parameters best distinguishes the AML cells from normal myeloid cells. Based on this information, 8-color labelings for monitoring the patient will be designed and used during follow up. In addition, AML stem cells will be analysed both at diagnosis and during follow-up by an 8-color labeling. Although an RT-PCR target is available in only 25 to 50% of AML patients, this MRD technique can be relevant as an adjuvant for the flowcytometric MRD detection. We will use primer/probe sets developed within the ‘Europe Against Cancer Project’ for detection and monitoring of fusion gene transcripts. The presence and monitoring of FLT3-ITD will be performed using RQ-PCR as well, applying patient-specific primers. For evaluation of WT1, the RQ-PCR recently developed within the European LeukemiaNet will be used [17-19]. Chimerism will be determined using the Powerplex®16 system (Promega, Leiden, the Netherlands). The PCR fragments will be analyzed on an ABI 3130 (Applied Biosystems Inc., Foster City, USA). Data analysis will be performed using Genescan® and Genotyper® software.

Immune reconstitution analysis Immune reconstitution will be analyzed freshly in blood/BM samples at the time points indicated in the scheme below. This approach is part of the follow-up after alloSCT and is implemented in the participating SCT centers. Kinetics of T/B/NK-cell recovery will be monitored by 9-parameter, 7-color flow cytometry, using an LSR II instrument® (Becton Dickinson) equipped with 4 lasers and 13 filters. Data will be assembled and analyzed with Diva® software. Part of the samples will be cryopreserved which will allow further retrospective phenotypic and functional analysis.

6

RATIONAL FOR REQUESTED PATIENT MATERIAL

Since this will be a prospective study the material requested will be provided to the SKION laboratory by the participating SCT centers using the standard procedures (hemoblok). Participation of nonDutch centers will be possible when fresh blood/bone marrow samples can be send to the SKION lab within twenty-four hours. 7

FINANCIAL SUPPORT

The costs of this project will be covered by the participating laboratories. We will apply for additional support in a separate grant application to KIKA.



8

REFERENCES 1. Bader P et al. Increasing mixed chimerism defines a high-risk group of childhood acute myelogenous leukemia patients after allogeneic stem cell transplantation where preemptive immunotherapy may be effective. BMT 2004; 33: 815-821 2. Bonanomi S et al. Successful outcome of allo-SCT in high-risk pediatric AML using chemotherapy-only conditioning and post transplant immunotherapy. BMT 2008;42:253-257 3. Heemskerk et al. T-cell receptor gene transfer for treatment of leukemia. Cytotherapy. 2008;10:108-15. Review. 4. Moretta L et al. Alloreactive natural killer cells in targeting high-risk leukaemias. Ann Rheum Dis. 2008;67 Suppl 3:iii39-43. Review. 5. Bader P et al. How and when should we monitor chimerism after allogeneic stem cell transplantation? Bone Marrow Transplant. 2005;35:107-19. 6. Rettinger E et al. Preemptive immunotherapy in childhood acute myeloid leukemia for patients showing evidence of mixed chimerism after allogeneic stem cell transplantation. 2011, 118:5681-5688 7. Goulden N et al. Minimal residual disease prior to stem cell transplant for childhood acute lymphoblastic leukaemia. Br J Haematol. 2003;122:24-9. 8. Lankester et al. Preemptive allo-immune intervention in high-risk pediatric acute lymphoblastic leukemia patients guided by minimal residual disease level before stem cell transplantation. 2010 submitted 9. Coustan-Smith E et al. Clinical significance of residual disease during treatment in childhood acute myeloid leukaemia. Br J Haematol 2003; 123: 243-252. 10. Langebrake C et al. Residual disease monitoring in childhood acute myeloid leukemia by multiparameter flow cytometry: the MRD-AML-BFM Study Group. J Clin Oncol 2006; 24: 3686-3692. 11. Sievers EL et al. Prediction of relapse of pediatric acute myeloid leukemia by use of multidimensional flow cytometry. J Natl Cancer Inst 1996; 88: 1483-1488. 12. Sievers EL et al. Immunophenotypic evidence of leukemia after induction therapy predicts relapse: results from a prospective Children's Cancer Group study of 252 patients with acute myeloid leukemia. Blood 2003; 101: 3398-3406. 13. Kern W et al Determination of relapse risk based on assessment of minimal residual disease during complete remission by multiparameter flow cytometry in unselected patients with acute myeloid leukemia. Blood 2004; 104: 3078-3085. 14. San Miguel JF et al. Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood 1997; 90: 24652470. 15. San Miguel JF et al. Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification. Blood 2001; 98: 1746-1751. 16. Venditti A et al. Level of minimal residual disease after consolidation therapy predicts outcome in acute myeloid leukemia. Blood 2000; 96: 3948-3952. 17. Venditti A et al. Clinical relevance of minimal residual disease detection in adult acute myeloid leukemia. J Hematother Stem Cell Res 2002; 11: 349-357. 18. Miyazaki T et al. Clinical significance of minimal residual disease detected by multidimensional flow cytometry: serial monitoring after allogeneic stem cell transplantation for acute leukemia. Leukemia Res 2012, 36: 998-1003 19. Bachas C et al. The role of minor subpopulations within the leukemic blast compartment of AML patients at initial diagnosis in the development of relapse. Leukemia 2012, 26: 13131320.



20. Gabert J et al. Standardization and quality control studies of 'real-time' quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia - a Europe Against Cancer program. Leukemia 2003; 17: 2318-2357. 21. Beillard E et al. Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using 'real-time' quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR) - a Europe against cancer program. Leukemia. 2003; 17:2474-86. 22. Cilloni D et al. Real-Time Quantitative PCR Detection of Minimal Residual Disease by Standardized WT1 assay to Enhance Risk Stratification in Acute Myeloid Leukemia: A European LeukemiaNet Study. J Clin Oncol 2009; in press. 23. Jacobsohn DA et al. High WT1 gene expression before haematopoietic stem cell transplant in children with acute myeloid leukaemia predicts poor event-free survival. Br J Haematol 2009; 146: 669-74 24. Candoni A et al. Quantitative assessment of WT1 gene expression after allogeneic stem cell transplantation is a useful tool for monitoring minimal residual disease in acute myeloid leukemia. Eur J Haematol 2009; 82: 61-8 25. Kwon M et al. Evaluation of minimal residual disease by real-time quantitative PCR of Wilms’ tumor I expression in patients with acute myelogenous leukemia after allogeneic stem cell transplantation: correlation with flow cytometry and chimerism. Biol Blood Marrow Transplant 2012, Epub. 26. van Dongen JJM et al. The future of clinical cell analysis for diagnosis, classification and monitoring of hematological malignancies. Cytometry B. 2008; 74B: 64-65. 27. Pedreira CE et al. EuroFlow Consortium. A probabilistic approach for the evaluation of minimal residual disease by multiparameter flow cytometry in leukemic B-cell chronic lymphoproliferative disorders. Cytometry A. 2008; 73A:1141-50



5.5

Prognostic significance of early AML blast clearance during induction and of routine bone marrow and peripheral blood monitoring by simple morphology during and after chemotherapy in pediatric AML

K. Klein, MD (Pediatric Oncology, VUmc, Amsterdam, The Netherlands)* V. de Haas, MD, PhD (DCOG laboratory, The Hague, The Netherlands) Prof. E.S.J.M. de Bont, MD, PhD (Pediatric Oncology/Hematology, UMCG, Groningen, The Netherlands) Prof. G.J.L. Kaspers, MD, PhD (Pediatric Oncology/Hematology, VUmc, Amsterdam, The Netherlands) * Corresponding author: VU University Medical Center Department of Pediatric Oncology/Hematology De Boelelaan 1117 1081 HV Amsterdam, The Netherlands 003120 - 444 3148 [email protected] In collaboration with members of the Dutch Childhood Oncology Group (DCOG), members of the Belgian Society of Pediatric Haematology Oncology (BSPHO) and members of the Nordic Society of Paediatric Haematology and Oncology (NOPHO)

Background The cure rate of pediatric acute myeloid leukemia (AML) has improved significantly, however, relapses still occur in 30-40% of patients in high-income countries, and in an even higher percentage of patients in low-income countries.1 Well-known prognostic factors for relapse risk in (pediatric) AML are early treatment response, cytogenetics and minimal residual disease (MRD).1-6 Unfortunately, the latter is cumbersome, and not available in all countries. Moreover, MRD evaluation has not been shown to be as successful as in acute lymphoblastic leukemia (ALL) so far, and is not yet being used by all pediatric AML study groups for risk group adapted therapy.3 Early treatment response has usually been studied by bone marrow (BM) evaluation, including examination on “day 15” [depending on the applicable protocol, on day 14-16] and “day 30” [depending on the applicable protocol on day 28-32].1,3,4 To the best of our knowledge, studies on the prognostic significance of the dynamics of clearance of AML blasts from the peripheral blood (PB) have not been published in pediatric AML, while this is an important prognostic feature in pediatric ALL (“prednisone response” at day 8)7,8 and several adult studies suggest prognostic relevance of peripheral blast cell clearance in AML9-12 as well. In previous pediatric studies on ALL, just a few relapses were detected by routine examinations. Moreover, patients with relapses diagnosed by these routine examinations did not have superior outcome compared to patients with a relapse, which was detected after developing symptoms.13,14 Except for APL15 it has not convincingly been shown that early detection of AML relapse by routinely screening for it after achieving first complete remission (CR) is clinically relevant.16,17 In fact, a previous retrospective analysis on pediatric AML patients showed no survival benefit for the few patients with relapses detected by routine evaluation.18 However, BM and PB sampling is routinely being done in many pediatric AML protocols without solid evidence that such routine monitoring (including conventional examination by morphology) is able to detect a relapse in a patient in whom otherwise a relapse was not suspected and that this early detection results in a better salvage rate. Aims of the study 1. To prospectively study the prognostic significance of early clearance of the PB from AML blasts, in association with the prognostic significance of day 22 (and other days if sampled) BM morphology results and other outcome parameters. Bijlage 5.5 Prognostic significance of early AML blast clearance and of routine bone marrow and peripheral blood monitoring by simple morphology during and after chemotherapy in pediatric AML Versie 2

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2. To prospectively determine the usefulness of routine BM and PB examination by morphology during and after treatment in detecting AML relapse, that was not suspected otherwise (based on signs or symptoms already suggesting a relapse) This study was originally not aimed at MRD detection, however, correlations between morphology and MRD data seems to be of great interest and will be evaluated if available. Relevance of the study This study may provide a novel prognostic factor that will be available very early in therapy, which potentially will enable to adapt treatment strategies accordingly. In view of its simplicity these factors -early examination of BM and PB- will also be available to low-income countries, which cannot afford expensive techniques to detect MRD. The second part of this study may learn whether it is useful for relapse detection to routinely sample BM and PB in children that have no complaints or signs at physical examination suggesting a relapse. Such procedures should only be done if its usefulness has been demonstrated, and currently that evidence is lacking. Materials and Methods Descriptive, prospective study, in children with pediatric AML that will be treated according to protocol NOPHO-DBH AML 2012. 1. Study population: pediatric AML patients, 0-18 years, being treated according to protocol NOPHODBH AML 2012. 2. BM: on days 22 and other time-points as described in the protocol and other time-points if sampled - examined by simple morphology (see “labbijlage” in the Dutch appendix). 3. PB: daily in the first week, and in the following weeks -if leukemic blasts are still present- three times a week every other two days (at day 8, 10, 12, 14, 16, etcetera) until clearance of the PB from AML blasts as determined by simple morphology (see “labbijlage” in the Dutch appendix). 4. Routine BM and PB examination by morphology: at time points as described in the protocol and according to the local hospital after completion of therapy for 4 years (see appendix). Participating study groups: DCOG, the Netherlands NOPHO, Scandinavia BSPHO, Belgium Participating study groups will provide the requested data and will assign one of their members to be contact person and coauthor for this project. Study period Identical to the time of using the NOPHO-DBH 2012 treatment protocol. Follow-up till the age of 18 years. Statistics PB Blast clearance Statistical methods will be comparable to a previous adult study by Arellano et al.9 Correlations between time to clearance of peripheral blood blasts and marrow blast clearance on day 22 (CR after one course) and after 2 courses of chemotherapy will be analyzed using a logistic regression model. A multivariable regression model will be applied to estimate these correlations after adjusting for effects from other covariates, e.g. age, WBC count, and cytogenetic or molecular risk group. To evaluate the predictive power of days from initiation of chemotherapy to Bijlage 5.5 Prognostic significance of early AML blast clearance and of routine bone marrow and peripheral blood monitoring by simple morphology during and after chemotherapy in pediatric AML Versie 2

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disappearance of the peripheral blood blasts and on the clearance of bone marrow blasts at day 22, a receiver operating characteristic (ROC) analysis will be performed. Different areas under the ROC curve will be compared using the χ2-test. Survival estimates will be determined using the Kaplan-Meier method and compared with the log rank test. A multivariable Cox proportional hazard model will be applied to evaluate associations between blast clearance and outcome. Besides CR after 1 course and CR after 2 courses, evaluated outcome parameters will be: relapse free survival (RSF), event free survival (EFS) and overall survival (OS). Sample size Regarding power calculations, there is insufficient data available to do so at this stage. Therefore, this study must be considered to be explorative in nature, and will provide the information needed to decide on a confirmatory study including a power calculation. It should be emphasized that this study simply analyzes data that will become available as part of standard patient care.

Routine BM and PB monitoring Associations between clinical abnormalities and bone marrow evaluation will be evaluated using the χ2-test. Sensitivity, specificity, negative predictive value (NPV) and the positive predictive value (PPV) will be determined in order to evaluate the accuracy of the prediction of a relapse through abnormalities found in peripheral blood counts and/or routine clinical examination at the time of BM examination. Comparison between relapse free survival and overall survival for patients with a relapse detected by routinely performed bone marrow and patients with symptomatic relapses will be performed using the Kaplan-Meier method and compared using the log rank test.

References 1. Creutzig U, van den Heuvel-Eibrink MM, Gibson B, et al: Diagnosis and management of acute myeloid leukemia in children and adolescents: recommendations from an international expert panel. Blood 120:3187-205, 2012 2. Kaspers GJ: Pediatric acute myeloid leukemia. Expert Rev Anticancer Ther 12:405-13, 2012 3. Kaspers GJ, Zwaan CM: Pediatric acute myeloid leukemia: towards high-quality cure of all patients. Haematologica 92:1519-32, 2007 4. Kern W, Haferlach T, Schoch C, et al: Early blast clearance by remission induction therapy is a major independent prognostic factor for both achievement of complete remission and long-term outcome in acute myeloid leukemia: data from the German AML Cooperative Group (AMLCG) 1992 Trial. Blood 101:64-70, 2003 5. Grimwade D, Walker H, Oliver F, et al: The importance of diagnostic cytogenetics on outcome in AML: analysis of 1,612 patients entered into the MRC AML 10 trial. The Medical Research Council Adult and Children's Leukaemia Working Parties. Blood 92:2322-33, 1998 6. Sievers EL, Lange BJ, Buckley JD, et al: Prediction of relapse of pediatric acute myeloid leukemia by use of multidimensional flow cytometry. J Natl Cancer Inst 88:1483-8, 1996 7. Felice MS, Zubizarreta PA, Alfaro EM, et al: Childhood acute lymphoblastic leukemia: prognostic value of initial peripheral blast count in good responders to prednisone. J Pediatr Hematol Oncol 23:411-5, 2001 8. Manabe A, Ohara A, Hasegawa D, et al: Significance of the complete clearance of peripheral blasts after 7 days of prednisolone treatment in children with acute lymphoblastic leukemia: the Tokyo Children's Cancer Study Group Study L99-15. Haematologica 93:1155-60, 2008 Bijlage 5.5 Prognostic significance of early AML blast clearance and of routine bone marrow and peripheral blood monitoring by simple morphology during and after chemotherapy in pediatric AML Versie 2

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9. Arellano M, Pakkala S, Langston A, et al: Early clearance of peripheral blood blasts predicts response to induction chemotherapy in acute myeloid leukemia. Cancer 118:5278-82, 2012 10. Elliott MA, Litzow MR, Letendre LL, et al: Early peripheral blood blast clearance during induction chemotherapy for acute myeloid leukemia predicts superior relapse-free survival. Blood 110:4172-4, 2007 11. Lacombe F, Arnoulet C, Maynadie M, et al: Early clearance of peripheral blasts measured by flow cytometry during the first week of AML induction therapy as a new independent prognostic factor: a GOELAMS study. Leukemia 23:350-7, 2009 12. Gianfaldoni G, Mannelli F, Baccini M, et al: Clearance of leukaemic blasts from peripheral blood during standard induction treatment predicts the bone marrow response in acute myeloid leukaemia: a pilot study. Br J Haematol 134:54-7, 2006 13. Rubnitz JE, Hijiya N, Zhou Y, et al: Lack of benefit of early detection of relapse after completion of therapy for acute lymphoblastic leukemia. Pediatr Blood Cancer 44:138-41, 2005 14. Gandhi M, Rao K, Chua S, et al: Routine blood counts in children with acute lymphoblastic leukaemia after completion of therapy: are they necessary? Br J Haematol 122:451-3, 2003 15. Lo-Coco F, Breccia M, Diverio D: The importance of molecular monitoring in acute promyelocytic leukaemia. Best Pract Res Clin Haematol 16:503-20, 2003 16. Muller E, Sauter C: Routine bone marrow punctures during remission of acute myelogenous leukemia. Leukemia 6:419, 1992 17. Estey E, Pierce S: Routine bone marrow exam during first remission of acute myeloid leukemia. Blood 87:3899-902, 1996 18. Hageman IM, Peek AM, de Haas V, et al: Value of routine bone marrow examination in pediatric acute myeloid leukemia (AML): a study of the Dutch Childhood Oncology Group (DCOG). Pediatr Blood Cancer 59:1239-44, 2012

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5.6

Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia Running title: SLAAP studie (SLeep in children with Acute myeloid leukemia and Additional costs to the Parents: a study into the effects on quality of life)

Principal investigators

1. Prof. dr. Gertjan Kaspers

2. dr. Raphaële van Litsenburg

3. Prof. dr. Martha Grootenhuis Co-applicant

4. prof. dr. Carin Uyl-de Groot

Pediatric oncology-hematology VU University Medical Center Amsterdam Pediatric oncology-hematology VU University Medical Center Amsterdam Psychosocial department AMC Amsterdam Health technology assessment VU University Medisch Centrum Amsterdam Institute for Medical Technology Assessment, Erasmus University Rotterdam

1. INTRODUCTION AND RATIONALE Over the last decades there has been progress in the treatment of pediatric acute myeloid leukemia (AML). AML is a rare disease, about 20-25 new cases are diagnosed in the Netherlands each year. The majority of children achieve complete remission (85-90%), but overall survival is much lower (70%) due to a high rate of recurrences. Despite the increased attention to psychosocial outcomes in pediatric cancer and the improvement in AML survival, there have been few studies that focused on children during and after treatment of AML. This study proposal is an adjustment to the currently open DCOG DB-AML01 add-on study “Kwaliteit van leven, slaap en vermoeidheid tijdens en na behandeling voor acute myeloide leukemie op de kinderleeftijd”. It also incorporates new parts: the effect on parental psychosocial functioning and the effect of monetary costs to the family, comparable to the ALL11 add-on study, and collaboration with several other international childhood cancer groups. 1.1 Psychosocial outcomes As mentioned in the previous section, children with AML have not often been studied separately when it comes to psychosocial outcomes. For example, up to date we have identified only one paper on quality of life (QoL) outcomes in pediatric AML (1). An other paper by Jonhston et al. reported on reasons for non-completion of QoL assessments in AML patients. Response rate was good (83%), reasons for non-completion during therapy were: patient too ill; passive or active refusal by respondent; developmental delay; logistic challenges; and poor knowledge of the study process from both the respondent and institutional perspective. QoL outcomes were, however, not reported (2). Finally, self-reported health experience, educational achievement, employment, and marital status were comparable with a sibling control group in a cohort of AML survivors (3). AML is often analyzed as part of the group of acute leukemias, which inevitable leads to AML being underrepresented. Since treatment compared to acute lymphoblastic leukemia is very different, shorter and more intense, it is likely that psychosocial outcomes are different. Therefore, this patient group should be studied separately in order to rightly identify the course of psychosocial outcomes over time and risk factors for adverse outcomes. This will help to provide adequate and timely counseling in future (high-risk) patients. It will also help identify potential interventions for the improvement of QoL. Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 52 versie 2


Recently, the mediating effect of sleep and sleep problems on QoL has been the focus of research. In ALL, the prevalence of sleep problems is higher than in healthy peers and it has been associated with a lower QoL during (4) as well as after treatment (5). In this population, risk factors for impaired sleep, such as child age (4, 6), child gender (4, 7, 8), fatigue (5) and nocturnal awakening during hospital admissions (9) are starting to emerge. Treatment with glucocorticoids seems to have a negative effect on sleep (7). Of course, these results cannot simply be applied to AML patients since treatment is fundamentally different. Sleep does not only affect the child, impaired child sleep also negatively affects parental QoL (10) and parental sleep (11). Management of sleep problems in children with AML may therefore be an important tool to improve both child and parental QoL. There has been considerable success treating sleep problems in children with behavioral therapy, melatonin and benzodiazepines (12-17), which may be applicable to the AML population. Melatonin is a biomarker of circadian dysregulation (18), which can be measured in urine. It is used to treat sleep onset delay and the consequent (daytime) fatigue associated with this sleep disorder. It is however, still unclear if sleep onset delay is a problem in this group. Knowledge on the character and development of sleep (problems) in AML is therefore necessary in order to design intervention studies with the ultimate goal to improve QoL in the future. 1.2 Cost-effectiveness The future advancement in survival in childhood oncology will increasingly involve individual tailormade therapies, new –more expensive- technology and medication. This is illustrated in the NOPHODBH AML 2012 protocol that includes an intensified induction treatment and minimal residual disease measurements to evaluate the response to therapy, in order to improve outcomes. Further therapy is adjusted accordingly, with stem cell transplantation for patients with a poor response and three consolidation courses in patients with a good response. Good responders with inv[16], a good prognostic marker, will receive a less intensive treatment: two instead of three consolidation courses. It is to be expected that further improvement in treatment of childhood cancer will therefore come at higher monetary costs. Even though childhood cancer is rare and costs are low compared to the costs involved in adult cancer care (19, 20), cost-effectiveness analysis are important because they help in the decision-making process regarding future interventions. Data on cost-effectiveness in adult cancer care cannot be compared to pediatric situations since there are large differences in costs as well as effects (21). In economic evaluations, the monetary costs of treatments or interventions are evaluated with regards to the effect of the treatment or intervention. This can lead to relatively expensive therapies being regarded as cost-effective when the effect is positive. Cost-effectiveness analysis (CEA) and cost-utility analysis (CUA) are the designs most often used. In CEA the costs are expressed as costs per life year saved or life year gained. In CUA, the life years saved are discounted for the quality of the life years. For this purpose, preference-based QoL scores, also referred to as utility scores, have to be collected. Utility scores are based on patient and community preferences concerning health states. The more preferable an outcome, the more utility is associated with it. Utilities are subsequently used to calculate quality adjusted life years (QALY). In CUA, costs are expressed as costs QALY. In general CUA are considered superior (22) to CEA. The effect of costs is not only important on a macro level. Financial burden to the parents as a consequence of treatment may also influence family functioning and QoL. Research on this topic in childhood cancer is almost non-existent. Two Canadian studies dating from 1996 (23) and 2008 (24) reported considerable expenses to the parents (up to 25% of the families’ disposable income). Considering the Canadian healthcare system is similar to the Dutch situation, with mandatory healthcare plans, this may indicate that Dutch parents also experience a large financial burden. Since there are, however, important differences between the Canadian and the Dutch society, more information on the effect on Dutch families caring for a child with cancer is important. Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 53 versie 2


1.3 International collaboration Patient numbers are low in pediatric AML. (Inter)national collaboration is therefore mandatory in order to perform solid research. We will be collaborating with two international childhood oncology groups in order to achieve more power to describe (risk factors for poor) QoL. Longitudinal development of QoL will be assessed at approximately the same time points and using the same instruments in all Nordic countries, Estonia and North America. The Nordic countries and Estonia are participating in the NOPHO-DBH AML 2012 treatment protocol, while patients from North America will be treated according to Childhood Oncology Group (COG) treatment protocols. These collaborations will not only increase patient numbers, but will also enable us to evaluate crosscultural differences in QoL (within the NOPHO-DBH treatment protocol) and QoL across different treatment protocols (NOPHO-DBH versus COG protocols). The aforementioned groups will also be collaborating regarding cost-effectiveness of treatment. Across high-income western countries, survival rates for pediatric AML are similar. Treatment strategies and supportive care practices, however, differ. Comparison of health care resource usage, (in)direct non-medical costs and QoL outcomes (utilities) in a CUA will help future decision-making on the most cost-effective treatment and supportive care scenarios. 1.3 Conclusion This study aims at describing quality of life, sleep and financial burden during and after treatment for pediatric AML. Since evidence on these aspects of AML treatment is very scarce, results from this study will improve patient counseling and will be a starting point for future (intervention) studies. 2. Study aims The main study questions to be answered are: 1. What is the (development of) quality of life of children with AML, during and after treatment? 1a. Is quality of life associated with specific factors such as demographic variables, treatment variables, sleep, fatigue and financial burden? 2. What is the prevalence and development of sleep problems in children during and after treatment for AML? 2a. Is child sleep associated with specific factors such as fatigue, demographic or treatment variables? 3. What is the financial burden of having a child with AML to the family? 4. What is the cost-effectiveness and cost-utility of AML treatment according to the NOPHODBH AML 2012 protocol in the Netherlands? Secondary study questions are: 1. Is sleep and/or fatigue associated with urinary melatonin levels? 2. Are parental sleep and psychosocial outcomes associated with financial burden, child sleep and quality of life? Tertiary study questions are: 1. Are there differences in quality of life between children treated according to the NOPHODBH AML 2012 protocol and children treated according to COG protocols in the USA? 2. Are there cultural differences in quality of life between children treated according to the same NOPHO-DBH AML 2012 protocol but living in different countries? 3. What are the differences in resource utilization during treatment for AML in the Netherlands compared to the USA?

Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 54 versie 2


3. STUDY DESIGN This study is designed as a prospective, longitudinal, multicenter observational cohort study. Patients will be observed during treatment for AML according to the NOPHO-DBH AML protocol and will be followed up until a year after the end of treatment. The main outcomes of this study will subjectively be assessed with reliable and validated questionnaires and sleep will also be objectively assessed with actigraphy. Parent-proxy questionnaires will be collected for all patients and children over the age of eight will be invited to fill out self-reports. 3.1 Inclusion criteria All children and adolescents treated according to the NOPHO-DBH AML 2012 protocol. 3.2 Exclusion criteria  Insufficiently fluent in Dutch or English  Age under 2 years 3.3 Test schedule Patients will be included three months after diagnosis. Follow up will take place until one year after the end of treatment. All measurements will include actigraphy, questionnaires and urine sampling (see sections 3.4, 3.5 and 3.6). Additional information on child and respondent demographics, parental occupation, family structure, hospital admissions and sleep medication will be collected at each time point. Information on treatment toxicity will be available through SKION databases. All patients will be tested 3 months after diagnosis (T0), at the end of treatment (T1) and 1 year after diagnosis (T2). See table 1 for an overview of the test schedule. 3.4 Questionnaires Child QoL can be evaluated by several respondents; the child itself, the parents, or healthcare providers. In childhood cancer research children are often too young or too ill and respondents are typically the parent(s). However, perceptions can differ between assessors. Children often report a better QoL than parent-proxies (5, 25), although the opposite has been reported as well (26). More agreement is generally seen on observable domains like physical health than on less-observable domains like emotional functioning (27). Therefore the consensus is to also include self-reports whenever possible. We will include parent-proxy reports for all participants and self-reports in children aged 8 years and older. Sleep In this study, sleep will be subjectively explored using the Children’s Sleep Habits Questionnaire (CSHQ). The CSHQ is a reliable and valid sleep screening instrument, designed by Owens et al. (28), to identify both behaviorally based and medically based sleep problems. An overall score of 41 and higher on the CSHQ is indicative for experiencing sleep problems. The scales include child self-report and parent proxy-report versions. The child self-report format is designed for children aged 7-12 years, the adolescent format (ASHQ) for the ages 12-18 years. The parent proxy-report also includes the age range 4-7 years, although the questionnaire has been successfully used in younger children as well (29). Parents and children will be asked to recall the child’s sleep behaviors over a “typical” recent week. The 33 items are rated on a 3-point scale. Filling in the CSHQ takes approximately ten minutes. The Dutch translation of the CSHQ showed adequate reliability and validity (30). Dutch norm references of the CSHQ have been obtained (31). Child Quality of life Quality of life will be assessed using the Pediatric Quality of Life InventoryTM (PedsQL) 4.0 Generic Core Scales. This instrument, designed by Varni et al., is a modular approach to measuring QoL in Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 55 versie 2


healthy children and adolescents aged 2 to 18 and those with acute and chronic health conditions. The 23-item questionnaire was designed to measure the core dimensions of health as delineated by the World Health Organization, as well as role (school) functioning. The 4 Multidimensional Scales are: physical, emotional, social and school functioning. It takes less than 4 minutes to complete the questionnaire. The PedsQL 4.0 Generic Core Scales include child self-reports and parent proxyreports. Child self-reports are available for unassisted administration for children from the age of 8 years. The parent proxy-report versions are available from the age of 2 years. The original American version demonstrated adequate reliability and validity. (32) The Dutch version of the PedsQL 4.0 Generic Core Scales has adequate psychometric properties and Dutch reference data have been collected (33). In addition, the PedsQL Cancer Module parent and child reports will be used to measure cancer-specific QoL (34). This instrument comprises eight subscales: pain, nausea, procedural anxiety, treatment anxiety, physical attractiveness, worry, communication and cognitive function and has satisfactory psychometric properties. Utility scores will be measured with the Health Utilities Index Mark 3(HUI) (35). The HUI is a preference-based QoL instrument that was developed based on morbidity in cancer survivors as described in the literature. It has good validity and reliability, and has been shown to be sensitive to change (36). It is suitable for proxy-reports for children from the age of 5 years and self-reports in children from the age of 12 years. Utility scores can be calculated and are appropriate for calculating quality- adjusted life years (QALYs) in CEA. Fatigue Fatigue will be subjectively explored using the PedsQL Multidimensional Fatigue Scale (PedsQL MFS) (34). The PedsQL MFS is designed to measure child and parent perception of fatigue in pediatric patients. The scales are comprised of parallel child self-report and parent proxy-report formats, similar to the Generic Core Scales. The original American version (34) and the translated Dutch version (37) demonstrated adequate reliability and validity in pediatric cancer. The estimated time to complete the PedsQLTM is less than four minutes. Parental functioning  Psychosocial functioning will be measured with the Distress Thermometer (DT-P). The DT-P consists of a thermometer on which parents are asked to rate their overall distress (0=no distress; 10=extreme distress) and items in different problems domains (practical, social, emotional, physical, cognitive and parenting). On these items, parents can indicate whether they experience this item as problematic. The validity and internal consistency of the DT-P is good (38). It takes about 7 minutes to complete. 

QoL will be measured with the Short Form 12 (SF-12). The SF is a frequently employed generic QoL instrument for adults. The SF-12 is validated and comprises only 12 items, thereby minimizing parental burden. It takes 2 to 3 minutes to complete. It measures functional health and well being by means of two summary scores: the physical summary score and mental summary score. Dutch norm values are available (39).



Sleep will subjectively be measured using the MOS sleep scale. The scale is validated and reliable (40). It consists of 12 questions and assesses six sleep domains, including sleep initiation, maintenance, quantity, adequacy, somnolence and respiratory impairments. Estimated time of completion is 2 to 3 minutes. Dutch norm values are available (41).

Costs to the families



At each time point parents will be asked to complete a short cost-diary containing a few daily questions on extra expenses (e.g. missed work hours, mileage, costs for extra daycare for siblings). This diary will take about two minutes a day to complete.

3.5 Actigraphy In this study, we will investigate disturbances of the circadian rhythm objectively, by performing actigraphy. Actigraphy measures sleep-wake rhythm from the presence or absence of movement, by a nonintrusive device (actometer) that patients wear 24 hours a day (excluding taking a shower or a bath). Patients have to wear the actometer for seven days, since aggregation over at least seven nights is necessary to acquire measures that reflect stable individual differences. (42) This method yields typical sleep-pattern measures, such as latency to sleep, sleep efficiency and intermittent awakening. This method has been widely used; reliability and validity have been established in infants, children and adults. (43-46) It is a low-cost, ambulant, non-invasive and objective method. The American Academy of Sleep Medicine recognizes actigraphy as useful adjunct in the clinical assessment of sleep disorders. (47) Results of actigraphic recordings are useful to evaluation of circadian-rhythm disorders and correlate well with measurements of melatonin rhythms. The actigraph contains a biaxial piezoelectric sensor and a microprocessor with programmable epoch length. Minimotion logger actigraphs will be set for 1-min epochs and zero crossing mode. Accompanying standardized software of the actometer will be used to extract several quantitive activity/rest and sleep/wake variables. Parents (with help of patients aged 8 years and over) will be asked to keep a sleep log of the children’s sleep-wake schedule during actigraphy. Detailed documentation in daily logs of sleep-wake periods and artifact-related information is critical since the conditions in practice differ from controlled standardized conditions in validation studies that have been conducted in the laboratory. (48) This daily log includes questions regarding the estimated sleep time, daytime function, sleep onset latency, wake periods during the night, feeling rested during daytime and subjective sleep quality. The log also contains information about times when the actigraph is not on the wrist. It will take about five to ten minutes to fill in the daily sleep log. Patients will serve as their own control. 3.6 Melatonin Since melatonin can be a biomarker for circadian dysregulation and melatonin is available for medical interventions, we will determine morning urinary melatonin levels along with the questionnaire measurements. Melatonin levels in urine are reflected by the amount of the primary metabolite 6-sulfatoxymelatonin (aMT6s). Adjusted for urinary creatinine concentrations, aMT6s levels are significantly correlated with serum melatonin. A single morning sample is representative of circulating levels of melatonin in the blood. Also, urinary melatonin is stable over time, making it suitable for delayed laboratory processing, which is inevitable in a national study. (18) 3.7 Participant gratuity To show appreciation for the participants’ efforts in this project, they will receive a 10 Euro gift card (VVV-bon) after the first measurement and one after the final measurement. 3.8 Logistics At the appropriate time points, the researcher will provide the family with the necessary material: accelerometer, questionnaires, sleep log, cost diary, voiding bags (if applicable) and urinary vials. The researcher will collect the material after the measurement week. Depending on the participants preference, questionnaires will be available on paper or can be accessed via a webportal: www.hetklikt.nu.



This study overlaps with the ongoing KLIK and IMPROVE projects, which are currently running in several pediatric oncology centers. Time points and choice of questionnaires have been synchronized in order to minimize burden to the families. There will be a close collaboration between all projects. 3.9 Cost-effectiveness 3.9.1 Cost categories: All costs made during AML treatment will be included. They will be evaluated from a societal perspective, following Dutch guidelines (22): 1. Direct medical costs: costs directly associated with AML treatment (e.g. admissions, day care treatment, outpatient clinic visits, medication, laboratory tests, imaging, radiotherapy, blood products etc). Healthcare utilization in the pediatric oncology centre as well as in the shared care hospital will be included. 2. Direct non-medical costs: see “costs to families” in the section 3.4 Questionnaires. 3.8.2 Cost determination Information on healthcare utilization will be acquired through hospital databases and chart review in pediatric oncology centers and shared care hospitals. Direct non-medical costs will be collected through 7-day diaries (see 3.4 questionnaires) at each time point. Costs will be calculated using units and tariffs defined by the Dutch Healthcare Authority, the Dutch manual for costing research (22) and the Health care insurance board. Tariffs will only be used if costing units are not available. For the costs of admission and day care treatment, local costs will be employed. Prices for stem cell transplantation will be calculated through the sum of all individual units. All costs will be expressed in 2015 or 2016 euros, indexed according to Statistics Netherlands (Centraal Bureau voor de Statistiek). Following Dutch guidelines, a 4% cost-discount will be used (22). Effects: 1. Survival: Three and five-year event free and overall survival. 2. Utilities measured with the Health Utilities Index (35), section 3.4 Questionnaires. Following Dutch guidelines, a 1,5% cost-discount for effects will be used (22).

4. STATISTICAL ANALYSIS Sample size calculation: Since information on the primary outcome measures (QoL and sleep) is largely lacking, we performed a sample size calculation based on QoL outcomes in children with acute lymphoblastic leukemia (ALL). Longitudinal data on QoL during ALL treatment was collected during a national add-on study to the DCOG ALL10 treatment protocol. Based on the change in QoL between diagnosis and halfway treatment, 20 to 50 participants (depending on the QoL domain that is measured) are necessary to demonstrate a small effect of 0.3 with a beta of 0.2 (power 0.8). Even though patients have already been recruited to participate in the observational study on QoL and sleep during the previous AML treatment protocol, this study does not include objective sleep measurements, parental sleep, parental psychosocial functioning and uses a different generic QoL instrument that will not enable us to compare data with international groups. Therefore, to answer the research questions in this study we propose to include 50 patients treated according to the NOPHO-DBH AML protocol. Based on the ALL10 add-on study on QoL, a high response rate (>80%) is expected for this study as well. Assuming all pediatric oncology centers in the Netherlands will participate in the study, about 20 patients will be eligible each year. Inclusion should be feasible in about 3-4 years. Statistical analysis: 1. To assess (the development of) quality of life and associated factors: Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 58 versie 2


2.

3.

4.

5.

a. We will evaluate the differences between the patient and the healthy sample using independent or one-sided t-tests. Age-appropriate norm values will be used. Scores below -1SD of the norm will be considered to represent impaired QoL (49). The magnitude and meaning of the differences will be represented as Cohen’s effect sizes. Effect sizes are calculated as follows; [mean(a) – mean (b) / largest standard deviation score (SD)], this means that differences between groups are expressed in units of the largest within-group standard deviation. Effect sizes between 0.2 and 0.5 indicate a small effect, an effect size between 0.5 and 0.8 indicate a moderate effect and effect sizes ≥ 0.8 represent a large effect. (50, 51) b. Multivariate analysis will be performed to assess the potential risk factors (demographic variables, sleep, fatigue, treatment modality, cost to families) for lower QoL. c. Longitudinal change in QoL will be analyzed using generalized estimating equations. The risk factors mentioned above (1b) will be included in the analysis. To assess the prevalence and development of sleep problems and associated factors: a. To evaluate differences in sleep between the patients and healthy children, see 1a. Children with scores over the cut-off point of 41 on the CSHQ will be considered to have sleep problems. b. Multivariate analysis will be performed to assess the potential risk factors (demographic variables, fatigue, treatment modality, costs to families) on the different outcome measures. c. Longitudinal change in QoL will be analyzed using generalized estimating equations. The risk factors mentioned above (2b) will be included in the analysis. Parental sleep and psychosocial outcomes and their association with financial burden, child sleep and child quality of life: a. To evaluate differences in parental sleep and psychosocial outcomes between the patient group and norms, see 1a. b. Multivariate analysis will be performed to assess the associations between the parental outcomes and financial burden, child sleep and child QoL. c. Longitudinal change in QoL will be analyzed using generalized estimating equations. The risk factors mentioned above (3b) will be included in the analysis. Differences in QoL between the NOPHO-DBH AML 2012 and COG treatment protocols and cultural differences within the NOPHO-DBH AML 2012 protocol will be analyzed using independent t-tests at each time point, after correcting for child age and treatment modality (chemotherapy versus stem cell transplantation). The cost-effectiveness of AML treatment a. Will be represented as the incremental cost-effectiveness ratio (ICER) between the NOPHO-DBH 2012 protocol and the previous DCOG-DB01 protocol. The ICER is calculated by dividing the difference in direct medical costs of the two protocols by the difference in gained life years. The “net-benefit regression approach” will allow us to analyze the influence of several determinants (e.g. type of treatment) on the cost-effectiveness. 95% Confidence intervals will be determined with Fieller’s or bootstrapping methods. The intervals will be illustrated in cost-effectiveness planes that plot the difference in survival and the difference in costs. Cost-effectiveness acceptability curves will be constructed to illustrate the probability of an acceptable ICER. b. Cost-utility (euros per QALY) will only be analyzed for patient treated according to the present NOPHO-DBH AML 2012 protocol, since utility scores (necessary for the calculation of QALY) have not been collected during the previous DCOG-DB AML-01 protocol. c. A one-way sensitivity analysis with a variation in costs for the most important costelements (admissions, medication), gained life years, life-expectance, utility scores



and discount percentage will be performed. The impact of the changed element on overall cost-effectiveness will be evaluated. d. The differences in health care usage during between the Netherlands and the USA will be analyzed with t-tests/mann-whitney U tests.

AML sleep and costs study questionnaires Time point:

Child age: 2-8 years

5-8 years

8-12 years

12+ years

T0

T1

T2

3 months after diagnosis

End of treatment

1 year after diagnosis

Parents: - CSHQ - PedsQL generic, cancer, MFS - SF 12/MOS/DT-P

Parents: - CSHQ - PedsQL generic, cancer, MFS - SF 12/MOS/DT-P

Parents: - CSHQ - PedsQL generic, MFS - SF 12/MOS/DT-P

- Sleeplog 7 days - cost diary 7 days


Children: -

Children: -

Children: -

Parents: - CSHQ - PedsQL generic, cancer, MFS - HUI - SF 12/MOS/DT-P

Parents: - CSHQ - PedsQL generic, cancer, MFS - HUI - SF 12/MOS/DT-P

Parents: - CSHQ - PedsQL generic, MFS - HUI - SF 12/MOS/DT-P



Children: -

Children: -

Children: -

Parents: See 5-8 yrs*



Children: - SSR - PedsQL generic, cancer, MFS

Children: - SSR - PedsQL generic, cancer, MFS

Children: - SSR - PedsQL generic, MFS






Children: Children: Children: - PedsQL generic, cancer, - PedsQL generic, cancer, - PedsQL generic, MFS MFS MFS - HUI - HUI - HUI CSHQ: Children’s Sleep Habits Questionnaire, MFS: Multidimentional Fatigue Scale, SSR: sleep self report *The sleeplog will filled out by parents with help of children aged >8 years. Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 60 versie 2


References 1. Hinds PS, Billups CA, Cao X, Gattuso JS, Burghen E, West N, et al. Health-related quality of life in adolescents at the time of diagnosis with osteosarcoma or acute myeloid leukemia. Eur J Oncol Nurs 2009;13(3):156-63. 2. Johnston DL, Nagarajan R, Caparas M, Schulte F, Cullen P, Aplenc R, et al. Reasons for noncompletion of health related quality of life evaluations in pediatric acute myeloid leukemia: a report from the Children's Oncology Group. PLoS One 2013;8(9):e74549. 3. Molgaard-Hansen L, Glosli H, Jahnukainen K, Jarfelt M, Jonmundsson GK, MalmrosSvennilson J, et al. Quality of health in survivors of childhood acute myeloid leukemia treated with chemotherapy only: a NOPHO-AML study. Pediatr Blood Cancer 2011;57(7):1222-9. 4. van Litsenburg RR, Huisman J, Hoogerbrugge PM, Egeler RM, Kaspers GJ, Gemke RJ. Impaired sleep affects quality of life in children during maintenance treatment for acute lymphoblastic leukemia: an exploratory study. Health Qual Life Outcomes 2011;9(1):25. 5. Gordijn MS, van Litsenburg RR, Gemke RJ, Huisman J, Bierings MB, Hoogerbrugge PM, et al. Sleep, fatigue, depression, and quality of life in survivors of childhood acute lymphoblastic leukemia. Pediatr Blood Cancer 2013;60(3):479-85. 6. Sadeh A, Sivan Y. Clinical practice: sleep problems during infancy. Eur J Pediatr 2009;168(10):1159-64. 7. Hinds P, Hockenberry M, Gattuso J, Srivastava D, Tong X, Jones H, et al. Dexamethasone alters sleep and fatigue in pediatric patients with acute lymphoblastic leukemia. Cancer 2007;110(10):2321-30. 8. Sanford SD, Okuma JO, Pan J, Srivastava DK, West N, Farr L, et al. Gender differences in sleep, fatigue, and daytime activity in a pediatric oncology sample receiving dexamethasone. J Pediatr Psychol 2008;33(3):298-306. 9. Hinds PS, Hockenberry M, Rai SN, Zhang L, Razzouk BI, McCarthy K, et al. Nocturnal awakenings, sleep environment interruptions, and fatigue in hospitalized children with cancer. Oncol Nurs Forum 2007;34(2):393-402. 10. Gedaly-Duff V, Lee K, Nail L, Nicholson H, Johnson K. Pain, sleep disturbance, and fatigue in children with leukemia and their parents: a pilot study. Oncol Nurs Forum 2006;33(3):641-6. 11. Zupanec S, Jones H, Stremler R. Sleep habits and fatigue of children receiving maintenance chemotherapy for ALL and their parents. J Pediatr Oncol Nurs 2010;27(4):217-28. 12. Smits MG, Nagtegaal EE, van der Heijden J, Coenen AM, Kerkhof GA. Melatonin for chronic sleep onset insomnia in children: a randomized placebo-controlled trial. J Child Neurol 2001;16(2):8692. 13. Braam W, Didden R, Smits M, Curfs L. Melatonin treatment in individuals with intellectual disability and chronic insomnia: a randomized placebo-controlled study. J Intellect Disabil Res 2008;52(Pt 3):256-64. 14. Stojanovski SD, Rasu RS, Balkrishnan R, Nahata MC. Trends in medication prescribing for pediatric sleep difficulties in US outpatient settings. Sleep 2007;30(8):1013-7. 15. Mindell JA, Kuhn B, Lewin DS, Meltzer LJ, Sadeh A. Behavioral treatment of bedtime problems and night wakings in infants and young children. Sleep 2006;29(10):1263-76. 16. Zawilska JB, Skene DJ, Arendt J. Physiology and pharmacology of melatonin in relation to biological rhythms. Pharmacol Rep 2009;61(3):383-410. 17. Buscemi N, Witmans M. What is the role of melatonin in the management of sleep disorders in children? Paediatr Child Health 2006;11(8):517-9. 18. Mirick DK, Davis S. Melatonin as a biomarker of circadian dysregulation. Cancer Epidemiol Biomarkers Prev 2008;17(12):3306-13. 19. Poos M, Smit J, Groen J, Kommer G, Slobbe L. Kosten van Ziekten in Nederland 2005. In: RIVM; 2008.



20. van Litsenburg RR, Uyl-de Groot CA, Raat H, Kaspers GJ, Gemke RJ. Cost-effectiveness of treatment of childhood acute lymphoblastic leukemia with chemotherapy only: The influence of new medication and diagnostic technology. Pediatr Blood Cancer 2011 57(6):1005-10. 21. Bassan R, Hoelzer D. Modern therapy of acute lymphoblastic leukemia. J Clin Oncol 2011;29(5):532-43. 22. Hakkaart - van Roijen L, Tan SS, Bouwmans CAM. Manual for costing research. Methods and guideline prices for economic evaluations in health care. Rotterdam: Health Care Insurance Board; 2010 Updated edition [in Dutch]. 23. Barr R, Furlong W, Horsman J, Feeny D, Torrance G, Weitzman S. The monetary costs of childhood cancer to the families of patients. Int J Oncol 1996;8(5):933-40. 24. Limburg H, Shaw AK, McBride ML. Impact of childhood cancer on parental employment and sources of income: a Canadian pilot study. Pediatr Blood Cancer 2008;51(1):93-8. 25. Engelen V, Koopman HM, Detmar SB, Raat H, van de Wetering MD, Brons P, et al. Healthrelated quality of life after completion of successful treatment for childhood cancer. Pediatr Blood Cancer 2011;56(4):646-53. 26. Theunissen NC, Vogels TG, Koopman HM, Verrips GH, Zwinderman KA, Verloove-Vanhorick SP, et al. The proxy problem: child report versus parent report in health-related quality of life research. Qual Life Res 1998;7(5):387-97. 27. Janse AJ, Gemke RJBJ, Uiterwaal CS, Van der Tweel I, Kimpen JLL, Sinnema G. Quality of life; patients and doctors don't always agree: A meta analysis. J Clin Epidemiol 2004;57(653):661. 28. Owens JA, Spirito A, McGuinn M. The children's sleep habits questionnaire (CSHQ) psychometric properties of a survey instrument for school-aged children. Sleep 2000;23(8):1043-51. 29. Goodlin-Jones B, Sitnick S, Tang K, Liu J, Anders T. The Children's Sleep Habits Questionnaire in toddlers and preschool children. J Dev Behav Pediatr 2008;29(2):82-8. 30. Waumans RC, Terwee CB, Van den Berg G, Knol DL, Van Litsenburg RR, Gemke RJ. Sleep and sleep disturbance in children: Reliability and validity of the Dutch version of the Child Sleep Habits Questionnaire. Sleep 2010;33(6):841-5. 31. van Litsenburg RR, Waumans RC, van den Berg G, Gemke RJ. Sleep habits and sleep disturbances in Dutch children: a population-based study. Eur J Pediatr 2010;169(8):1009-15. 32. Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations. Med.Care 2001;39(8):800-12. 33. Engelen V, Haentjens MM, Detmar SB, Koopman HM, Grootenhuis MA. Health related quality of life of Dutch children: psychometric properties of the PedsQL in the Netherlands. BMC Pediatr 2009;9:68. 34. Varni JW, Burwinkle TM, Katz ER, Meeske K, Dickinson P. The PedsQL(trademark) in pediatric cancer: Reliability and validity of the Pediatric Quality of Life Inventory(trademark) Generic Core Scales, Multidimensional Fatigue Scale, and Cancer Module. Cancer 2002;94(7):2090-106. 35. Horsman J, Furlong W, Feeny D, Torrance G. The Health Utilities Index (HUI): concepts, measurement properties and applications. Health Qual Life Outcomes 2003;1:54. 36. Klaassen RJ, Krahn M, Gaboury I, Hughes J, Anderson R, Grundy P, et al. Evaluating the ability to detect change of health-related quality of life in children with Hodgkin disease. Cancer 2010;116(6):1608-14. 37. Gordijn M, Cremers EM, Kaspers GJ, Gemke RJ. Fatigue in children: reliability and validity of the Dutch PedsQL Multidimensional Fatigue Scale. Qual Life Res 2011;20(7):1103-8. 38. Haverman L, van Oers HA, Limperg PF, Houtzager BA, Huisman J, Darlington AS, et al. Development and validation of the distress thermometer for parents of a chronically ill child. J Pediatr 2013;163(4):1140-6 e2. 39. Mols F, Pelle AJ, Kupper N. Normative data of the SF-12 health survey with validation using postmyocardial infarction patients in the Dutch population. Qual Life Res 2009;18(4):403-14. 40. Hays RD, Martin SA, Sesti AM, Spritzer KL. Psychometric properties of the Medical Outcomes Study Sleep measure. Sleep Med 2005;6(1):41-4. Bijlage 5.6 Quality of life, sleep, cost effectiveness and financial burden to the family in pediatric acute myeloid leukemia 62 versie 2


41. de Weerd A, de Haas S, Otte A, Trenite DK, van Erp G, Cohen A, et al. Subjective sleep disturbance in patients with partial epilepsy: a questionnaire-based study on prevalence and impact on quality of life. Epilepsia 2004;45(11):1397-404. 42. Acebo C, Sadeh A, Seifer R, Tzischinsky O, Wolfson AR, Hafer A, et al. Estimating sleep patterns with activity monitoring in children and adolescents: how many nights are necessary for reliable measures? Sleep 1999;22(1):95-103. 43. Sadeh A. Evaluating night wakings in sleep-disturbed infants: a methodological study of parental reports and actigraphy. Sleep 1996;19(10):757-62. 44. Ancoli-Israel S, Cole R, Alessi C, Chambers M, Moorcroft W, Pollak CP. The role of actigraphy in the study of sleep and circadian rhythms. Sleep 2003;26(3):342-92. 45. Sadeh A, Hauri PJ, Kripke DF, Lavie P. The role of actigraphy in the evaluation of sleep disorders. Sleep 1995;18(4):288-302. 46. Van Cauwenberghe E, Gubbels J, De Bourdeaudhuij I, Cardon G. Feasibility and validity of accelerometer measurements to assess physical activity in toddlers. Int J Behav Nutr Phys Act 2011;8:67. 47. Morgenthaler T, Alessi C, Friedman L, Owens J, Kapur V, Boehlecke B, et al. Practice parameters for the use of actigraphy in the assessment of sleep and sleep disorders: an update for 2007. Sleep 2007;30(4):519-29. 48. Sadeh A, Gruber R, Raviv A. Sleep, neurobehavioral functioning, and behavior problems in school-age children. Child Dev. 2002;73(2):405-17. 49. Varni JW, Burwinkle TM, Seid M, Skarr D. The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity. Ambul Pediatr 2003;3(6):329-41. 50. Cohen J. Statistical power analysis for behavioral sciences. New York: Academic press; 1977. 51. Kazis LE, Anderson JJ, Meenan RF. Effect sizes for interpreting changes in health status. Medical care 1989;27(3 Suppl):S178-S89.


Bijlagen behorende bij NOPHO-DBH AML 2012 protocol

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