A personalized stepwise dynamic predictive algorithm of the time to first treatment in chronic lymphocytic leukemia.

ABSTRACT: Personalized prediction is ideal in chronic lymphocytic leukemia (CLL). Although refined models have been developed, stratifying patients in risk groups, it is required to accommodate time-dependent information of patients, to address the clinical heterogeneity observed within these groups. In this direction, this study proposes a personalized stepwise dynamic predictive algorithm (PSDPA) for the time-to-first-treatment of the individual patient. The PSDPA introduces a personalized Score, reflecting the evolution in the patient's follow-up, employed to develop a reference pool of patients. Score evolution's similarity is used to predict, at a selected time point, the time-to-first-treatment for a new patient. Additional patient's biological information may be utilized. The algorithm was ap

SUBMITTER: Moysiadis T 

PROVIDER: S-EPMC10470317 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature