Multiplicity-adjusted semiparametric benefiting subgroup identification in clinical trials.

ABSTRACT: Background A recent focus in the health sciences has been the development of personalized medicine, which includes determining the population for which a given treatment is effective. Due to limited data, identifying the true benefiting population is a challenging task. To tackle this difficulty, the credible subgroups approach provides a pair of bounding subgroups for the true benefiting subgroup, constructed so that one is contained by the benefiting subgroup while the other contains the benefiting subgroup with high probability. However, the method has so far only been developed for parametric linear models. Methods In this article, we develop the details required to follow the credible subgroups approach in more realistic settings by considering nonlinear and semiparametric regression

SUBMITTER: Schnell PM 

PROVIDER: S-EPMC8796253 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature