This is actually the second entry in this series;† the first was Part V of the Homeopathy and Evidence-Based Medicine series, which began the discussion of why Evidence-Based Medicine (EBM) is not up to the task of evaluating highly implausible claims. That discussion made the point that EBM favors equivocal clinical trial data over basic science, even if the latter is both firmly established and refutes the clinical claim. It suggested that this failure in calculus is not an indictment of EBM’s originators, but rather was an understandable lapse on their part: it never occurred to them, even as recently as 1990, that EBM would soon be asked to judge contests pitting low powered, bias-prone clinical investigations and reviews against facts of nature elucidated by voluminous and rigorous experimentation. Thus although EBM correctly recognizes that basic science is an insufficient basis for determining the safety and effectiveness of a new medical treatment, it overlooks its necessary place in that exercise.
This entry develops the argument in a more formal way. In so doing it advocates a solution to the problem that has been offered by several others, but so far without real success: the adoption of Bayesian inference for evaluating clinical trial data.