Type I error control and interim monitoring for co-primary hypotheses involving a subgroup in the Outpatient Treatment with Anti-Coronavirus Immunoglobulin (OTAC) trial.

The recent growth of immunoglobulin-based therapies has motivated clinical trials testing primary endpoints both in the overall cohort and in subgroups of patients, such as in patients without specific antibodies at baseline. Multiple testing methods in clinical trials often ignore the natural correlation between test statistics in such contexts, resulting in overly conservative type I error control. The Outpatient Treatment with Anti-Coronavirus Immunoglobulin (OTAC) trial, is an ongoing Phase III trial evaluating the effect of a single infusion of anti-COVID-19 hyperimmune intravenous immunoglobulin (hIVIG), in outpatient adults with recently diagnosed SARS-CoV-2 infection, in both the overall cohort and in the subgroup of participants who had not received monoclonal antibodies or antiviral treatments. We present the method used to control the type I error at a predetermined rate while taking the estimated correlation into account, thus increasing efficiency. We evaluated the operating characteristics of this method in both fixed and group-sequential scenarios through extensive simulation studies. Our findings indicate that this approach controls the type I error at the desired rate, improves power, and reduces the expected sample size compared to a Bonferroni correction.