Meta-STEPP: Subpopulation Treatment Effect Pattern Plot for Meta-Analysis

• Activity Number: 606
• Type: Contributed
• Date/Time: Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Victoria Wang*+ and Bernard F. Cole and Marco Bonetti and Richard D. Gelber
• Companies: Dana-Farber Cancer Institute and University of Vermont and Bocconi University and Harvard School of Public Health/Dana-Farber Cancer Institute
• Keywords: treatment-covariate interaction ; clinical trials ; meta-analysis ; survival analysis

Abstract

STEPP (Subpopulation Treatment Effect Pattern Plot) is a method to explore possible treatment-by-covariate interaction in clinical trials where the covariate of interest is continuous. We extend STEPP to the meta-analysis setting where patterns of possible treatment effect heterogeneity can be examined in data from multiple trials. Simulation studies show that Meta-STEPP has adequate type-I error rate recovery as well as power when reasonable window sizes are chosen. When applied to eight breast cancer trials, Meta-STEPP suggests that chemotherapy is less effective for tumors with high estrogen receptor expression compared to those with low expression.