The problem
Stroke trials answer yes or no at the 0.05 gate. Clinicians do not make yes-or-no decisions; they weigh graded probabilities for one patient at a time, and the gap between what the trials report and what the bedside needs is where much of the field's confusion lives.
A trial that "fails" at p = 0.06 and a trial that "succeeds" at p = 0.04 may carry nearly identical information about whether a treatment helps — and the binary reading of them drives treatment fashions, premature abandonments, and a decade of arguments that better questions would have dissolved.
What the method requires
Three disciplines make Bayesian synthesis worth trusting, and each is a practice rather than a slogan. Transparent priors: every analysis declares what was believed before the data arrived — enthusiastic, neutral and sceptical — and the declaration precedes the analysis, in writing. Reproducible engines: the same data and the same prior return the same posterior, byte for byte, on any machine, or the analysis does not ship. Pre-registration: the question, the priors and the analysis plan are registered before results exist, so that the answer cannot quietly become the question.
Proof the approach works, from the published literature
The approach is not speculative; the literature already carries its demonstrations, at both ends. DAWN (Nogueira RG, et al. N Engl J Med 2018; doi:10.1056/NEJMoa1706442; NCT02142283) showed a Bayesian design running a pivotal trial: adaptive enrichment, a posterior stopping rule, credible intervals — and a result the whole field acted on. The Bayesian reanalysis of EOLIA (Goligher EC, et al. JAMA 2018; PMID 30347031) showed the interpretive power of the same machinery pointed backwards: a trial the significance test called negative carried a posterior probability of mortality benefit (relative risk below 1) of 88% to 99% under stated priors, from strongly sceptical to enthusiastic. Design and interpretation are the two halves of this kind of work, and both already have their existence proofs in print.
Where our interest stands
We are studying these methods in depth — the same discipline this site applies to citations, applied to priors — and exploring collaborations with methodologists and trialists who work in them daily. Nothing of ours is published yet. When something is, it will have been pre-registered before it was anything else, and it will appear here.
Collaborate
If graded probability in cerebrovascular medicine is your problem too — as a trialist, a methodologist, or a clinician who has felt the 0.05 gate misdescribe a result you cared about — write: [email protected]