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We represent a community with a shared interest in data analysis using the population approach.

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Sub-group Nonsense. Problems In Interpreting And Considering Covariates In Evaluation

Charles Warlow

Dept. of Clinical Neurosciences, Western General Hospital, Edinburgh, UK

Sub-group analysis is driven by our desire as doctors to treat individuals as individuals not as groups – in which sorts of people does the treatment work best, or worst? At the same time, the reliability of the results of sub-group analysis dpends on a number of things which are uncomfortable – a priori and not data-driven hypotheses about what should work and what might not, very large sample size of the overall trial and so in each relevant sub-group, and proper analysis to explore the heterogeneity of treatment effects across all sub-groups under consideration. Furthermore, the results of sub-group analysis should not be suppressed, and ideally they should be replicated in a different trial. So having more than one trial running in parallel has a lot to commend it. But even sub-group analysis is not enough, at least not unless the patients are divided not just into the obvious young or old, male or female etc, but also on the basis of overall baseline risk of a poor outcome. After all, even very risky treatments might be worthwhile in patients with a poor prognosis.