학술논문
Borrowing information across patient subgroups in clinical trials, with application to a paediatric trial
Document Type
article
Author
Rebecca M. Turner; Anna Turkova; Cecilia L. Moore; Alasdair Bamford; Moherndran Archary; Linda N. Barlow-Mosha; Mark F. Cotton; Tim R. Cressey; Elizabeth Kaudha; Abbas Lugemwa; Hermione Lyall; Hilda A. Mujuru; Veronica Mulenga; Victor Musiime; Pablo Rojo; Gareth Tudor-Williams; Steven B. Welch; Diana M. Gibb; Deborah Ford; Ian R. White; and the ODYSSEY Trial Team
Source
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-11 (2022)
Subject
Language
English
ISSN
1471-2288
Abstract
Abstract Background Clinical trial investigators may need to evaluate treatment effects in a specific subgroup (or subgroups) of participants in addition to reporting results of the entire study population. Such subgroups lack power to detect a treatment effect, but there may be strong justification for borrowing information from a larger patient group within the same trial, while allowing for differences between populations. Our aim was to develop methods for eliciting expert opinions about differences in treatment effect between patient populations, and to incorporate these opinions into a Bayesian analysis. Methods We used an interaction parameter to model the relationship between underlying treatment effects in two subgroups. Elicitation was used to obtain clinical opinions on the likely values of the interaction parameter, since this parameter is poorly informed by the data. Feedback was provided to experts to communicate how uncertainty about the interaction parameter corresponds with relative weights allocated to subgroups in the Bayesian analysis. The impact on the planned analysis was then determined. Results The methods were applied to an ongoing non-inferiority trial designed to compare antiretroviral therapy regimens in 707 children living with HIV and weighing ≥ 14 kg, with an additional group of 85 younger children weighing