Effective Subgroup Analysis Approaches for Assessing Heterogeneity in Systematic Reviews of Complex Interventions

Identifying heterogeneity in systematic reviews of complex interventions is crucial for understanding differential treatment effects across subpopulations. Effective subgroup analysis approaches are essential for this purpose, as they help uncover variations in treatment efficacy that may be obscured when considering the population as a whole. Several methods have been proposed and evaluated in the literature, each with its strengths and limitations. The following sections outline some of the most effective approaches for subgroup analysis in systematic reviews.

While these methods offer robust frameworks for identifying heterogeneity, it is important to consider potential pitfalls such as post hoc data generation, multiple testing, and selective reporting, which can lead to erroneous interpretations. Properly prespecified subgroup analyses and carefully considering confounding factors are essential to avoid these issues and ensure valid conclusions. Additionally, the choice of method may depend on the specific context and characteristics of the data, highlighting the need for tailored approaches in different systematic reviews.