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...

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Vydáno v:	Statistics in medicine Ročník 39; číslo 15; s. 2115 - 2137
Hlavní autoři:	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
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken, USA John Wiley & Sons, Inc 10.07.2020 Wiley Subscription Services, Inc
Témata:	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
On-line přístup:	Získat plný text
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