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A revised prognostic model for patients with acute myeloid leukemia and first relapse

  • Niek G. van der Maas
  • , Dimitri Breems
  • , Clara P. W. Klerk
  • , Thomas Pabst
  • , Patrycja Gradowska
  • , Abin Thomas
  • , Bart J. Biemond
  • , Jurgen Kuball
  • , Catharina H. M. J. van Elssen
  • , Otto Visser
  • , Marie-Christiane Vekemans
  • , Carlos Graux
  • , Johan Maertens
  • , Steven Knapper
  • , Mike Dennis
  • , Sylvie Freeman
  • , Ian Thomas
  • , H. Berna Beverloo
  • , Gerwin Huls
  • , Charles Craddock
  • Peter J. M. Valk, Paresh Vyas, Nigel Russell, Gert Ossenkoppele, Bob löwenberg, Jan J. Cornelissen, Jurjen Versluis*
*Corresponding author for this work
  • Erasmus University Rotterdam
  • Cadix Hospital
  • Dijklander Hospital
  • University of Bern
  • Swiss Group for Clinical Cancer Research
  • HOVON Foundation
  • Cardiff University
  • Amsterdam UMC
  • Utrecht University
  • Maastricht University
  • Isala Clinics
  • Université catholique de Louvain
  • KU Leuven
  • The Christie NHS Foundation Trust
  • University of Birmingham
  • University of Groningen
  • University of Warwick
  • University of Oxford
  • Oxford University Hospital
  • Guy's and St Thomas' NHS Foundation Trust

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Most patients with acute myeloid leukemia (AML) may obtain remission upon induction chemotherapy, but relapse is frequent and associated with poor survival. Previous prognostic models for outcomes after relapse lacked analysis of comprehensive molecular data. A validated prognostic model integrating clinical, cytogenetic, and molecular variables may support treatment decisions. We studied 943 patients with AML who relapsed after intensive induction treatment in a development cohort (HOVON-SAKK). A random survival forest algorithm was used to evaluate the association of clinical parameters, cytogenetic abnormalities, and molecular variables at diagnosis with overall survival (OS). Relapsing patients (n = 377) who were enrolled in the NCRI-AML18 trial were used for validation. In the development cohort, the median age at relapse was 58 years, and patients were classified as 2022 European LeukemiaNet favorable (22%), intermediate (31%), and adverse risk (48%). One-third underwent allogeneic transplantation in the first complete remission. Variable selection yielded 9 variables associated with 1-year OS, including relapse-free interval, age, white blood cell count, mutated TP53, FLT3 internal tandem duplication, core-binding factor abnormalities, t(v;11q23)/KMT2A rearrangement, and complex/monosomal karyotype, which were assigned points according to their estimated hazard ratios. Three prognostic groups were defined with distinct 1-year OS in both development (favorable, 51% ± 3%; intermediate, 29% ± 3%; and poor, 14% ± 2%, respectively) and validation cohorts (51% ± 4%, 26% ± 5%, and 14% ± 3%, respectively). Validation confirmed the improved accuracy in predicting outcomes for patients with AML in first relapse. The revised AML relapse model improved on previous prognostic models for outcomes after first relapse. It provides stratification that might support tailoring second line treatment.
Original languageEnglish
Pages (from-to)3853-3864
Number of pages12
JournalBlood
Volume9
Issue number15
DOIs
Publication statusPublished - 12 Aug 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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