title: Meta-STEPP: subpopulation treatment effect pattern plot for individual patient data meta-analysis.
abstract: We have developed a method, called Meta-STEPP (subpopulation treatment effect pattern plot for meta-analysis), to explore treatment effect heterogeneity across covariate values in the meta-analysis setting for time-to-event data when the covariate of interest is continuous. Meta-STEPP forms overlapping subpopulations from individual patient data containing similar numbers of events with increasing covariate values, estimates subpopulation treatment effects using standard fixed-effects meta-analysis methodology, displays the estimated subpopulation treatment effect as a function of the covariate values, and provides a statistical test to detect possibly complex treatment-covariate interactions. Simulation studies show that this test 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 with those with low expression. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, U.S.A.|Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02215, U.S.A.
authors.forename: Xin Victoria
authors.initials: XV
authors.lastname: Wang
authors.affiliation: Department of Mathematics and Statistics, University of Vermont, 16 Colchester Avenue, Burlington, VT 05401, U.S.A.
authors.forename: Bernard
authors.initials: B
authors.lastname: Cole
authors.affiliation: Bocconi University and Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Via Röntgen 1, 20136 Milan, Italy.
authors.forename: Marco
authors.identifier: 0000-0003-2304-4180
authors.initials: M
authors.lastname: Bonetti
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, U.S.A.|Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02215, U.S.A.
authors.forename: Richard D
authors.initials: RD
authors.lastname: Gelber
mesh_terms: D001943:Breast Neoplasms / Q000628:therapy; D000068598:Data Accuracy; D006801:Humans; D015201:Meta-Analysis as Topic; D011960:Receptors, Estrogen; D016896:Treatment Outcome
chemical_list: D011960:Receptors, Estrogen
keywords: clinical trial; meta-analysis; survival analysis; treatment covariate interaction