Prediction of resistance to hydroxyurea therapy in patients with polycythemia vera: a machine learning study (PV-AIM) validated in a prospective interventional phase IV trial (HU-F-AIM).

ABSTRACT: Polycythemia vera (PV) is a myeloproliferative neoplasm associated with increased thromboembolic (TE) risk and hematologic complications. Hydroxyurea (HU) serves as the most frequently used first-line cytoreductive therapy worldwide; however, resistance to HU (HU-RES) develops in a significant subset of patients, leading to increased morbidity and necessitating alternative treatments. This study, part of the PV-AIM project, employed machine learning techniques on real-world evidence (RWE) from the Optum® EHR database containing 82.960 PV patients to identify baseline predictors of HU-RES within the first 6-9 months of therapy. Using a Random Forest model, the study analyzed data from 1850 patients, focusing on laboratory parameters and clinical characteristics. Key predictive markers inclu

SUBMITTER: Heidel FH 

PROVIDER: S-EPMC12208875 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature