Primer: the fallacy of subgroup analysis.
The identification of subgroups of patients from randomized clinical trials that are of specific interest for guiding clinical decisions can be an attractive idea; however, since such trials are designed for the comparison of groups of patients, performing subgroup analyses can result in misinterpretation of the data. Such analyses must, therefore, be performed and evaluated with caution: these should be pre-planned and included in the design of a suitably powered trial. Data obtained should be analyzed using formal statistical tests of interaction on proper subgroups rather than improper subgroups of patients, the results obtained should be delineated carefully, and details of how these analyses were performed, and how the data should be interpreted, should be reported in the trial paper. The caveats associated with this approach, such as the occurrence of false positive or false negative effects, chance differences in observed effects, lack of power to perform the analysis, floor or ceiling effects, issues relating to multiple statistical testing, and over-reporting and under-reporting are discussed in this review. Subgroup analyses can, however, provide valuable, albeit predominantly exploratory, information on which to base clinical decisions if they are performed in accordance with recommendations and guidelines, and do, therefore, have a legitimate place in rheumatology clinical trials.
Guillemin
Francis
F
School of Public Health, Nancy University, and Clinical Epidemiology Centre Inserm CIE6, Nancy-University Hospital, France. francis.guillemin@medecine.uhp-nancy.fr
D003627:Data Interpretation, Statistical; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012107:Research Design; D012219:Rheumatology / Q000379:methods*; D018401:Sample Size; D015983:Selection Bias; D012680:Sensitivity and Specificity; D016896:Treatment Outcome