Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘Table 1. Potential pitfalls of subgroup analyses.• Over-interpreting positive results as evidence of cause and effect• Not supporting the results of subgroup analyses with a strong biological rationale• Not increasing the significance threshold for multiple analyses• Having an inadequate number of subjects in the subgroups to be able to give a good estimate of the treatment effect• Selecting subgroups post hoc, which can be biased by the treatment effect itself• Not considering supporting evidence from other studiesWednesday or born only in the year 1940 are much less likely to have a rationalbiological association with a disease process, and so would usually forminappropriate subgroups.What are the uses of subgroup analyses?Subgroup analyses are used in many ways. The most common applications are:• to examine whether the treatment effect or side-effects of treatmentsare the same or greater in patients with a specific feature or risk factorso that more specific treatment decisions can be made• to generate hypotheses for future studies such as novel associations(eg, patients with asthma and rheumatoid arthritis had more jointpains in a trial of patients using a new formulation of salbutamol;might rheumatoid arthritis and asthma therapies be linked?)• in rare situations, to review whether the randomization process workedevenly (eg, in a large multinational trial, were the 100 patients fromcountry X equally distributed to new and control treatments? If not,did the imbalance change the size of the treatment effect for thatcountry’s patients?)What are the problems with subgroup analyses?A number of pitfalls of subgroup analyses are listed in Table 1. The immediateproblem with subgroup analyses is that the individual subgroups of interest areusually small compared with the trial population, which can therefore reduce thestatistical power for determining an estimate of the true treatment effect withinthe subgroup. Although the beneficial effect of the treatment might increase if thetreatment is restricted to subjects at higher risk of trial endpoints, the confidenceinterval for the size of the true treatment effect will widen [2].267