Controlling false discovery proportion in identification of drug-related adverse events from multiple system organ classes.

ABSTRACT: Analyzing safety data from clinical trials to detect safety signals worth further examination involves testing multiple hypotheses, one for each observed adverse event (AE) type. There exists certain hierarchical structure for these hypotheses due to the classification of the AEs into system organ classes, and these AEs are also likely correlated. Many approaches have been proposed to identify safety signals under the multiple testing framework and tried to achieve control of false discovery rate (FDR). The FDR control concerns the expectation of the false discovery proportion (FDP). In practice, the control of the actual random variable FDP could be more relevant and has recently drawn much attention. In this paper, we proposed a two-stage procedure for safety signal detection with direct

SUBMITTER: Tan X 

PROVIDER: S-EPMC6731544 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature