Efficient methods for signal detection from correlated adverse events in clinical trials.

ABSTRACT: It is an important and yet challenging task to identify true signals from many adverse events that may be reported during the course of a clinical trial. One unique feature of drug safety data from clinical trials, unlike data from post-marketing spontaneous reporting, is that many types of adverse events are reported by only very few patients leading to rare events. Due to the limited study size, the p-values of testing whether the rate is higher in the treatment group across all types of adverse events are in general not uniformly distributed under the null hypothesis that there is no difference between the treatment group and the placebo group. A consequence is that typically fewer than 100α percent of the hypotheses are rejected under the null at the nominal significance level of α . T

SUBMITTER: Diao G 

PROVIDER: S-EPMC6661211 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature