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Activity Number:
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145
- Leveraging External Data in Clinical Trials
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Type:
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Contributed
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Date/Time:
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Monday, August 8, 2022 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #323521
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Title:
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Leveraging Information from Historical Trials: A Case Study in Pediatric Multiple Sclerosis
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Author(s):
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Min Zhu* and David Stivers and Judy Li
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Companies:
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Bristol Myers Squibb and Bristol Myers Squibb and Bristol Myers Squibb
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Keywords:
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meta-analytic-predictive prior;
MAP;
non-inferiority study;
prior-data conflict;
effective sample size;
robust MAP prior
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Abstract:
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About 10% of multiple sclerosis (MS) patients are diagnosed with MS before age 18. Compared to adult-onset patients, these patients experience more frequent neurological symptoms and have a much earlier onset age of disability. Rarity of pediatric patients and risks of irreversible deficits from treatment of low-efficacy controls pose challenges for developing MS pediatric therapies. We propose a Bayesian non-inferiority (NI) study design to address these challenges in the Phase 3 trial of ozanimod in MS pediatric patients. The NI design replaces low-efficacy control with fingolimod whereas the Bayesian approach reduces sample size by leveraging information from historical studies. For each arm, information extrapolated from adult studies are synthesized with information from pediatric studies to form a meta-analytic-predictive (MAP) prior. This informative prior is then combined with a non-informative prior to protect against prior-data conflict. Effective sample sizes are computed to quantify the amount of information that are leveraged.
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Authors who are presenting talks have a * after their name.
