Evaluation of biomarkers for treatment selection using individual participant data from multiple clinical trials.

ABSTRACT: Biomarkers that predict treatment effects may be used to guide treatment decisions, thus improving patient outcomes. A meta-analysis of individual participant data (IPD) is potentially more powerful than a single-study data analysis in evaluating markers for treatment selection. Our study was motivated by the IPD that were collected from 2 randomized controlled trials of hypertension and preeclampsia among pregnant women to evaluate the effect of labor induction over expectant management of the pregnancy in preventing progression to severe maternal disease. The existing literature on statistical methods for biomarker evaluation in IPD meta-analysis have evaluated a marker's performance in terms of its ability to predict risk of disease outcome, which do not directly apply to the treatment

SUBMITTER: Kang C 

PROVIDER: S-EPMC5889758 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature