In clinical trials, it is common practice to follow up significant interactions between the factors under investigation with subgroup analyses. Such analyses pose at least two analytical and interpretational challenges. The first challenge is that performing multiple subgroup analyses increases the likelihood of obtaining spuriously significant results. This has been acknowledged and relevant guidance exists in the medical literature. The second challenge is that the effects that are obtained at the level of subgroup are composite. This has yet to be (...) fully acknowledged and discussed in the context of medical research. This paper aims to fill this lacuna. Using a simple additive model, we use recent findings from the CHARISMA trial on the efficacy of clopidogrel in addition to aspirin in the treatment of patients at risk for atherothrombotic events to demonstrate quantitatively the composition of effects at the level of subgroups. In the simplest case of a design involving an interaction (two crossed factors, with two levels each, i.e. a 2 x 2 design), effects at the level of subgroup consist of influences that stem (i) from the incidence of the measured outcome in the study population as a whole; (ii) from the factor of interest (e.g. treatment vs. placebo); (iii) from the second factor (e.g. patient group membership); (iv) from the interaction between the two factors; and (v) from random error in the measured outcome. The value of the approach illustrated here is that it is generalizable to any research design irrespective of its complexity and that it prompts clinicians to consider the multiple causality underlying medical research findings. (shrink)

This paper argues that there exists a collective epistemic state of ‘Broad Medical Uncertainty’ regarding the effectiveness of many medical interventions. We outline the features of BMU, and describe some of the main contributing factors. These include flaws in medical research methodologies, bias in publication practices, financial and other conflicts of interest, and features of how evidence is translated into practice. These result in a significant degree of uncertainty regarding the effectiveness of many medical treatments and unduly optimistic beliefs about (...) the benefit/harm profiles of such treatments. We argue for an ethical presumption in favour of openness regarding BMU as part of a ‘Corrective Response’. We then consider some objections to this position, including concerns that public honesty about flaws in medical research could undermine trust in healthcare institutions. We suggest that, as it stands, the Anti-Corrective Response is unconvincing. (shrink)