Title: Screening biomarkers associated with individual treatment effect
Authors: Shonosuke Sugasawa - University of Tokyo (Japan) [presenting]
Abstract: The development of molecular diagnostic tools to achieve precision medicine requires accurate screening biomarkers associated with individual treatment effect. Although several effective data analytic strategies have been proposed for this purpose, they have limitations when it comes to flexibly capturing the complex relationships between clinical outcome and possibly high-dimensional covariates. We employ semiparametric hierarchical mixture modeling and propose an effective method for screening biomarkers associated with individual treatment effect. We apply the proposed method together with some existing methods to simulated data set and real trial data.