Individual participant data meta‐analysis to examine interactions between treatment effect and participant‐level covariates: Statistical recommendations for conduct and planning

Precision medicine research often searches for treatment‐covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference, odds ratio, hazard ratio) changes across values of a participant‐level covariate (eg, age, gender, biomarker). Single trials do not usually hav...

Full description

Saved in:

Bibliographic Details
Published in:	Statistics in medicine Vol. 39; no. 15; pp. 2115 - 2137
Main Authors:	Riley, Richard D., Debray, Thomas P.A., Fisher, David, Hattle, Miriam, Marlin, Nadine, Hoogland, Jeroen, Gueyffier, Francois, Staessen, Jan A., Wang, Jiguang, Moons, Karel G.M., Reitsma, Johannes B., Ensor, Joie
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 10.07.2020 Wiley Subscription Services, Inc
Subjects:	Clinical trials Data Analysis effect modifier Humans individual participant data (IPD) Medical statistics Meta-analysis Meta-Analysis as Topic Models, Statistical Precision medicine Proportional Hazards Models subgroup effect treatment‐covariate interaction Tutorial in Biostatistics individual participant data (IPD) meta-analysis treatment-covariate interaction subgroup effect effect modifier
ISSN:	0277-6715, 1097-0258, 1097-0258
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!