作者
Laurène Fenwarth, Xavier Thomas, Stephane De Botton, Nicolas Duployez, Jean-Henri Bourhis, Auriane Lesieur, Gael Fortin, Paul-Arthur Meslin, Ibrahim Yakoub-Agha, Pierre Sujobert, Pierre-Yves Dumas, Christian Recher, Delphine Lebon, Céline Berthon, Mauricette Michallet, Arnaud Pigneux, Stephanie Nguyen, Sylvain Chantepie, Norbert Vey, Emmanuel Raffoux, Karine Celli-Lebras, Claude Gardin, Juliette Lambert, Jean-Valere Malfuson, Denis Caillot, Sebastien Maury, Benoit Ducourneau, Pascal Turlure, Emilie Lemasle, Cecile Pautas, Sylvie Chevret, Christine Terre, Nicolas Boissel, Gerard Socie, Herve Dombret, Claude Preudhomme, Raphael Itzykson
发表日期
2021/1/28
期刊
Blood, The Journal of the American Society of Hematology
卷号
137
期号
4
页码范围
524-532
出版商
American Society of Hematology
简介
A multistage model instructed by a large dataset (knowledge bank [KB] algorithm) has recently been developed to improve outcome predictions and tailor therapeutic decisions, including hematopoietic stem cell transplantation (HSCT) in acute myeloid leukemia (AML). We assessed the performance of the KB in guiding HSCT decisions in first complete remission (CR1) in 656 AML patients younger than 60 years from the ALFA-0702 trial (NCT00932412). KB predictions of overall survival (OS) were superior to those of European LeukemiaNet (ELN) 2017 risk stratification (C-index, 68.9 vs 63.0). Among patients reaching CR1, HSCT in CR1, as a time-dependent covariate, was detrimental in those with favorable ELN 2017 risk and those with negative NPM1 minimal residual disease (MRD; interaction tests, P = .01 and P = .02, respectively). Using KB simulations of survival at 5 years in a scenario without HSCT in …
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L Fenwarth, X Thomas, S De Botton, N Duployez… - Blood, The Journal of the American Society of …, 2021