Selection of the optimal personalized treatment from multiple treatments with right-censored multivariate outcome measures.

ABSTRACT: We propose a novel personalized concept for the optimal treatment selection for a situation where the response is a multivariate vector that could contain right-censored variables such as survival time. The proposed method can be applied with any number of treatments and outcome variables, under a broad set of models. Following a working semiparametric Single Index Model that relates covariates and responses, we first define a patient-specific composite score, constructed from individual covariates. We then estimate conditional means of each response, given the patient score, correspond to each treatment, using a nonparametric smooth estimator. Next, a rank aggregation technique is applied to estimate an ordering of treatments based on ranked lists of treatment performance measures given b

SUBMITTER: Siriwardhana C 

PROVIDER: S-EPMC10956931 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature