A Critical Review of Graphics for Subgroup Analyses in Clinical Trials

Ballarini, N.M. and Chiu, Yi-Da and Koenig, Franz and Posch, Martin and Jaki, Thomas (2020) A Critical Review of Graphics for Subgroup Analyses in Clinical Trials. Pharmaceutical Statistics, 19 (5). pp. 541-560. ISSN 1539-1604

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Abstract

Subgroup analyses are a routine part of clinical trials to investigate whether treatment effects are homogeneous across the study population. Graphical approaches play a key role in subgroup analyses to visualise effect sizes of subgroups, to aid the identification of groups that respond differentially, and to communicate the results to a wider audience. Many existing approaches do not capture the core information and are prone to lead to a misinterpretation of the subgroup effects. In this work, we critically appraise existing visualisation techniques, propose useful extensions to increase their utility and attempt to develop an effective visualisation approach. We focus on forest plots, UpSet plots, Galbraith plots, subpopulation treatment effect pattern plot, and contour plots, and comment on other approaches whose utility is more limited. We illustrate the methods using data from a prostate cancer study.

Item Type:
Journal Article
Journal or Publication Title:
Pharmaceutical Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? statistics and probabilitypharmacologypharmacology (medical) ??
ID Code:
142041
Deposited By:
Deposited On:
03 Mar 2020 08:50
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Oct 2024 00:37