STATISTICS IN CLINICAL TRIALS: OUT OF CONDITION. SOME PROBLEMS OF UNCONDITIONAL INFERENCEAT THE CROSSROADS OF METHODOLOGY AND ETHICS

Randomized controlled trials are experiments for the evaluation of a new treatment option, currently representing the "gold standard" in health care assessment. Clinical trials fulfill a double role of evidence production and of regulatory oversight in sanctioning new drugs' approval into the drug market. For this reason trials are large and tightly regulated enterprises that have to comply with ethical requirements while at the same time maintaining high epistemic standards, in a balance that becomes increasingly difficult to strike as research questions become more and more sophisticated. The statistical framework adopted for designing and analysing trials represents a relevant part of this architecture. Statististical methodology influences such aspects as which inferences are licensed on the basis of data and what is the degree of support granted to an hypothesis. Thus, statistics plays a fundamental role as a gatekeeper both in warranting the ethical permissibility of a trial, and in licensing conclusions about the most effective treatment. Certain widely-accepted statistical principles have an impact on the way results from medical studies are evaluated. One such principle is conditioning, i.e. the possibility to incorporate an assessment of strength of evidence in inferential statements of confidence. Currently, conditioning is not part of the statistical method in use, although it is upheld by alternative statistical paradigms such as the Bayesian. In my thesis I analyze the impact of conditioning upon the ethical, epistemic and regulatory facets of trials and I suggest the possibility of incorporating conditioning within the current statistical paradigm of clinical research.