Abstract
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. Trial Registration: This study was registered on clinicaltrials.gov under NCT0491026 on 1 June 2021.
| Original language | English (US) |
|---|---|
| Article number | 101592 |
| Journal | Contemporary Clinical Trials Communications |
| Volume | 49 |
| DOIs | |
| State | Published - Feb 2026 |
Bibliographical note
Publisher Copyright:© 2026 The Authors
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This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Clinical trials
- Group sequential design
- Multiple testing
- Nested subgroups
- Type I error rate
PubMed: MeSH publication types
- Journal Article
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