Improving clinical trial interpretation with Acceptability Curve Estimation (ACE)

Effective decision making from randomised controlled clinical trials relies on robust interpretation of the numerical results. However, the language we use to describe clinical trials can cause confusion in both trial design and in comparing results across trials. Acceptability curve estimation (ACE) aids comparison between trials (even where of different designs) by harmonising reporting of results, acknowledging different interpretations of the results may be valid in different situations, and moving the focus from comparison to a pre-specified value to interpretation of the trial data. ACE can be applied to historical trials or incorporated into statistical analysis plans for future analyses. An online tool enables ACE on up to three trials simultaneously.