What question did this study set out to answer?

This study aims to connect trial design with the probabilities of clinical hypotheses, addressing the uncertainty in hypotheses evaluation.

Mind the gap: Bayesian equipoise calibration of clinical trial designs

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Randomized trial calibrates equipoise imbalance in clinical trial designs, suggesting improved decision-making.

This study aims to connect trial design with the probabilities of clinical hypotheses, addressing the uncertainty in hypotheses evaluation.
Quantified equipoise imbalance as the percentile of post-study odds reflecting pre-study equipoise.
Analyzed outcomes of trial designs with 90% evidence of equipoise imbalance using Bayesian methods.
Applied equipoise calibration to sequential clinical development plans in oncology.
Demonstrated that designs with 95% power and 5% false positive rate provided strong evidence against the alternative hypothesis.
Establishing equipoise imbalance required large sample sizes when outcomes were inconsistent between phase 2 and phase 3.

Fabio Rigat (2026) studied this question.

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