Dijkman B, Kooistra B, Bhandari M et al. How to work with a subgroup analysis. Can J Surg. 2009;52(6):515-22. PMID:20011190.
Abstract
Surgical practice should principally be based on evidence originating from high-quality data such as randomized controlled trials (RCTs). Whereas these studies mostly investigate general and representative patient populations, clinical decisions most often depend on individual patient characteristics. To concede to the need of individually based guidelines, many RCTs report analyses on specific subgroups of patients. The main aim of a subgroup analysis is to identify either consistency of or large differences in the magnitude of treatment effect among different categories of patients. Determining whether the observed overall treatment effect is different across certain subgroups may justly provide some patients with its benefits and protect others from its harm.
Irrespective of its practical potentials, subgroup analysis must be conscientious in design, reporting and interpretation. Many stringent methodological criteria apply but are far from always fulfilled. Consequently, inferences drawn may wrongfully direct management of certain patient groups. In fact, the definition of a subgroup analysis is equivocal in that authors use the term to indicate tests that estimate dfifferences in treatment effect within subgroups (a subgroup effect) and between subgroups (an interaction).
The purpose of this article is to consider criteria for sound subgroup analyses in RCTs, assuming good underlying methodological quality of the main trial (i.e., randomization, assessor blinding, etc.). A clinical scenario, based on a recent RCT in orthopedic surgery, will practically support the theoretical statements throughout the text.
Last Updated on October 2, 2026
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