Prediction model for drug response of acute myeloid leukemia patients.
NPJ Precis Oncol
; 7(1): 32, 2023 Mar 24.
Article
em En
| MEDLINE
| ID: mdl-36964195
ABSTRACT
Despite some encouraging successes, predicting the therapy response of acute myeloid leukemia (AML) patients remains highly challenging due to tumor heterogeneity. Here we aim to develop and validate MDREAM, a robust ensemble-based prediction model for drug response in AML based on an integration of omics data, including mutations and gene expression, and large-scale drug testing. Briefly, MDREAM is first trained in the BeatAML cohort (n = 278), and then validated in the BeatAML (n = 183) and two external cohorts, including a Swedish AML cohort (n = 45) and a relapsed/refractory acute leukemia cohort (n = 12). The final prediction is based on 122 ensemble models, each corresponding to a drug. A confidence score metric is used to convey the uncertainty of predictions; among predictions with a confidence score >0.75, the validated proportion of good responders is 77%. The Spearman correlations between the predicted and the observed drug response are 0.68 (95% CI [0.64, 0.68]) in the BeatAML validation set, -0.49 (95% CI [-0.53, -0.44]) in the Swedish cohort and 0.59 (95% CI [0.51, 0.67]) in the relapsed/refractory cohort. A web-based implementation of MDREAM is publicly available at https//www.meb.ki.se/shiny/truvu/MDREAM/ .
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Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article