Conditional Drug Approval with the Harmonic Mean Chi-Squared Test

Approval of treatments in areas of high medical need may not follow the two-trials paradigm, but might be granted under conditional approval. Under conditional approval, the evidence for a treatment effect from a pre-market clinical trial has to be substantiated in an independent post-market clinical trial or a longer follow-up duration. Several ways exist to quantify the overall evidence provided by the two trials. We study the applicability of the recently developed harmonic mean Chi-squared test to the conditional drug approval framework. The proposed approach can be used both for the design of the post-market trial and the analysis of the combined evidence provided by both trials. Other methods considered are the two-trials rule, Fisher's criterion and Stouffer's method. For illustration, we apply the harmonic mean Chi-squared test to a drug which received conditional (and eventually final) market licensing by the EMA. A simulation study is conducted to study the operating characteristics in more detail. We finally investigate the applicability of the harmonic mean Chi-squared test to compute the power at interim of an ongoing post-market trial. In contrast to some of the traditional methods, the harmonic mean Chi-squared test always requires a post-market clinical trial. In addition, if the p-value from the pre-market clinical trial is << 0.025, a smaller sample size for the post-market clinical trial is needed than with the two-trials rule.