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Döhner, K.1; Thiede, C.2; Jahn, N.1; Ekaterina, P.1; Gambietz, A.3; Prior, T. W.4; Marcucci, G.5; Jones, D.6; Krauter, J.7; Michael, H.8; Lo-Coco, F.9; Ottone, T.10; Nomdedeu, J.11; Mandrekar, S. J.12; Huebner, L.12; Laumann, K. M.12; Geyer, S. M.13; Klisovic, R. B.14; Wei, A.15; Sierra, J.16; Sanz, M. A.17; Brandwein, J. M.18; de Witte, T. M.19; Jansen, J. H.20; Niederwieser, D.21; Appelbaum, F. R.22; Medeiros, B. C.23; Tallman, M. S.24; Schlenk, R. F.25; Ganser, A.8; Serve, H.26; Ehninger, G.2; Amadori, S.9; Gathmann, I.27; Axel, B.3; Pallaud, C.27; Larson, R. A.28; Stone, R. M.29; Döhner, H.1; Bloomfield, C. D.30

doi: 10.1097/01.HS9.0000559252.96061.3e
Poster Session I: Acute myeloid leukemia - Clinical

1Department of Internal Medicine III, University Hospital of Ulm, Ulm

2Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus der TU Dresden, Dresden

3Division of Biostatistics, German Cancer Research Center, Heidelberg, Germany

4The Ohio State University Comprehensive Cancer Center, Ohio State University, Columbus

5City of Hope Comprehensive Cancer, Duarte

6Department of Pathology, The Ohio State University and James Cancer Hospital, Columbus, OH, United States

7 Department Hematology and Oncology, Braunschweig Municipal Hospital, Braunschweig

8Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany

9Department of Biomedicine and Prevention, Università di Roma “Tor Vergata”

10Department of Biomedicine and Prevention, University of Tor Vergata, Rome, Italy

11Clinical Hematology Service, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain

12Alliance Statistics and Data Center, Mayo Clinic, Rochester

13Health Informatics Institute, University of South Florida, Tampa

14Department of Hematology and Medical Oncology, Emory University, Atlanta, United States

15Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, Australia

16Hematology Department, Hospital Santa Creu i Sant Pau, Barcelona

17Department of Hematology, Hospital Universitari i Politecnic La Fe, Department of Medicine, University of Valencia, Spain

18Department of Medical Oncology and Hematology, Princess Margaret Hospital, Toronto, Canada

19 Department of Tumor Immunology, Nijmegen Centre of Life Sciences,Radboud University Nijmegen

20 Department of Laboratory Medicine, Laboratory of Hematology, Radboud University, Nijmegen, Netherlands

21 Division of Hematology and Oncology, University Hospital Leipzig, Leipzig, Germany

22Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle

23Division of Hematology-Oncology, Stanford Comprehensive Cancer Center, Stanford University, Stanford

24Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, United States

25 National Center of Tumor Diseases, German Cancer Research Center, Heidelberg

26Department of Medicine II, Hematology/Oncology, Goethe University, Frankfurt/Main, Germany

27Novartis Pharmaceuticals, Basel, Switzerland

28Department of Medicine and Comprehensive Cancer Center, University of Chicago, Chicago, IL

29Department of Medical Oncology, Dana-Farber/Partners CancerCare, Boston, MA

30The Ohio State University Comprehensive Cancer Center, Columbus, OH, United States

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Patients (pts) with AML harboring FLT3 internal tandem duplications (ITD) have poor outcomes, in particular pts with a high ITD mutant to wild-type (wt) allelic ratio (AR; ≥0.5). The 2017 update of the European LeukemiaNet (ELN) recommendations addressed the importance of the ITD AR in the genetic risk stratification and defined distinct NPM1/FLT3-ITD genotypes.

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In this exploratory post-hoc analysis from randomized pts treated within the RATIFY trial evaluating the addition of midostaurin to standard chemotherapy, we investigated the prognostic impact of the NPM1/FLT3-ITD genotypes according to the 2017 ELN risk categories.

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In total, 319 of 717 pts with FLT3-ITD positive AML were included who gave informed consent for biomarker analyses and who could be categorized according to 2017 ELN genetic risk stratification. Median age was 47.9 years (range, 18-60); median follow-up time was 4.8 years.

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Pts were categorized as follows: (i) favorable-risk (n = 85), NPM1mut/FLT3-ITDlow, irrespective of secondary chromosome abnormalities and concurrent gene mutations; (ii) intermediate-risk (n = 111), NPM1mut/FLT3-ITDhigh and NPM1wt/FLT3-ITDlow, both subgroups without adverse cytogenetics and without concurrent RUNX1, ASXL1, TP53 mutations; (iii) adverse-risk (n = 123), NPM1wt/FLT3-ITDhigh; as well as NPM1mut/FLT3-ITDhigh and NPM1wt/FLT3-ITDlow with adverse-risk cytogenetic and/or molecular markers; frequencies of RUNX1, ASXL1, and TP53 mutations in adverse-risk AML were 29.2%, 19.8%, and 1.9%, respectively. Rates of allogeneic transplantation (alloSCT) in first complete remission (CR) were not different among the groups, with 29.4%, 35.1%, and 35.0% in pts. with favorable-, intermediate-, and adverse-risk AML, respectively. Rates of CR (including responses after induction 1 and 2) were negatively associated with adverse-risk genetics (51.2% vs 69.4% and 64.0% in favorable- and intermediate-risk, respectively; p = 0.02); multivariable logistic regression analysis revealed adverse-risk as significantly different compared to favorable-risk (odds ratio [OR] 0.534, 95% confidence interval [CI] 0.287-0.979; p = 0.044), whereas no difference was seen between the two other risk groups; treatment with midostaurin had no impact (p = 0.32). Overall survival (OS) differed among the 3 ELN-risk groups; 5-year survival rates were 63%, 43%, 33% for favorable, intermediate- and adverse-risk groups, respectively. The OS curves did not show differential effects of midostaurin among the 3 risk groups (Figure 1), with a benefical effect seen for midostaurin vs placebo in all 3 groups with hazard ratios (HR) estimated as HR = 0.52, HR = 0.51, and HR = 0.55 for favorable-, intermediate-, and adverse-risk groups, respectively. A multivariable Cox model adjusted for age, WBC, sex, and bone marrow blasts was used to test the effects of treatment and risk classification. The resulting model revealed an increasing HR with increasing risk category (p < 0.001; intermediate vs. favorable, HR = 1.70, 95% CI 1.08-2.68; adverse vs. favorable risk, HR = 2.48, 95% CI 1.59-3.86), while treatment with midostaurin significantly reduced risk compared to placebo (p < 0.001; HR = 0.53, 95% CI 0.38-0.72).



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Data from this post-hoc exploratory analysis confirm the prognostic value of the 2017 ELN risk categories also among AML pts with the distinct NPM1/FLT3-ITD genotypes. A Cox model revealed a significant effect for midostaurin compared to placebo independent of the ELN risk groups. Analysis with regard to potential confounding effects of allogenic transplantation are ongoing.

Copyright © 2019 The Authors. Published by Wolters Kluwer Health Inc., on behalf of the European Hematology Association.