Evaluating marker‐guided treatment selection strategies

摘要: A potential venue to improve healthcare efficiency is effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving rules (ITR) have become available in recent years. Prior adopting any ITR clinical practice, it crucial evaluate its value improving outcomes. Existing quantifying values mainly consider either a single or semi-parametric that are subject bias under model misspecification. In this paper, we general setting with multiple markers propose two-step robust method derive ITRs their values. We also procedures comparing different ITRs, which can be used quantify the incremental of new selection. While working models step I approximate optimal add layer calibration guard against misspecification further assess non-parametrically, ensures validity inference. To account sampling variability estimated corresponding values, resampling procedure provide valid confidence intervals functions well Our proposals examined through extensive simulation studies illustrated data from trial effects two drug combinations on HIV-1 infected patients.