Clinical trials in Crohn’s Disease face additional complexity as biologics provide additional treatment options but may require combination treatments to reach optimal efficacy. A Phase 4 prospective open-label study of a triple-combination therapy in participants with moderate to severe Crohn’s disease did not have comparison arms of participants treated with placebo or the associated monotherapies, precluding the ability to perform traditional head-to-head treatment comparisons. 

Alimentiv Statistics provided innovative insight into post hoc Bayesian analyses of the study data against literature-supported remission rate benchmarks for comparison treatments to support the combination treatment efficacy. 

These Bayesian analyses not only provided comparisons of the probability of subject response for the triple combination therapy against response rates for placebo and the associated monotherapies but also integrated prior information about the efficacy of the monotherapies to increase the accuracy of estimates of remission for the combination therapy of interest.

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