Prespecification of subgroup analyses and examination of treatment-subgroup interactions in cancer individual participant data meta-analyses are suboptimal

Objectives: This study aimed to explore the prespecification and conduct of subgroup analyses in cancer individual participant data meta-analyses (IPDMAs).

Study design and setting: We searched PubMed, Embase.com, Cochrane Library, and Web of Science to identify IPDMAs of randomized controlled trials evaluating intervention effects for cancer. We evaluated how often cancer IPDMAs prespecify subgroup analyses and statistical approaches for examining treatment-subgroup interactions and handling continuous subgroup variables.

Results: We included 89 IPDMAs, of which 41 (46.1%) reported a statistically significant treatment-subgroup interaction (P < 0.05) in at least one subgroup analysis. 47 (52.8%) IPDMAs prespecified methods for conducting subgroup analyses and the remaining 42 (47.2%) did not prespecify subgroup analyses. Of the 47 IPDMAs prespecified subgroup analyses, 19 performed the planned subgroup analyses, 21 added subgroup analyses, 7 reduced subgroup analyses. Eighty IPDMAs examined treatment-subgroup interactions, but 72 IPDMAs did not provide enough information to determine whether an appropriate approach that avoided aggregation bias was used. 85 IPDMAs that used continuous variables in subgroup analyses categorized continuous variables and only 1 IPDMA examined non-linear relationships.

Conclusion: Many cancer IPDMAs did not prespecify subgroup analyses, nor did they fully perform planned subgroup analyses. Lack of details for the test of treatment-subgroup interactions and examination of non-linear interactions was suboptimal.