Is a Subgroup Claim Believable?

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Subgroup analyses are often reported in randomized controlled trials and meta-analyses. Apparent subgroup effects may, however, be misleading. Surgeons may therefore find it challenging to decide whether to believe a claim of subgroup effect (i.e., an apparent difference in treatment effect between subgroups of the study population). In the present study, we introduce seven widely used criteria to assess subgroup analyses in the surgical literature and include two examples of subgroup analyses from a large randomized trial to elaborate on the use of these criteria. Typically, inferences regarding subgroup effects are stronger if the comparison is made within rather than between studies, if the test for interaction suggests that chance is an unlikely explanation for apparent differences, if the subgroup hypothesis was specified a priori, if it was one of a small number of hypotheses tested, if the difference in effect between subgroup categories is large, if it is consistent across studies, and if there is indirect evidence supporting the difference (a biological rationale). When testing the impact of surgical interventions, investigators may examine whether the effects differ between subgroups of patients or ways of administering an intervention—so-called subgroup analysis. For instance, in a randomized trial of removable splinting compared with casting for wrist buckle fractures in children, children with moderate injury (but not those with mild or severe injury) in the splint group had a larger change in scores on the Activity Scales for Kids than did the casting group1. In another example, a meta-analysis of sutures compared with staples for skin closure in orthopaedic surgery, the risk of a wound infection developing in patients with hip surgery (but not in other groups) was four times greater after staple closure than after suture closure2. Typically, the primary hypothesis of a randomized trial is to investigate …