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Activity Number:
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154
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #308203 |
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Title:
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Predicting Accrual in Clinical Trials: Bayesian Posterior Predictive Distribution
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Author(s):
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Stephen D. Simon*+ and Byron Gajewski
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Companies:
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Children's Mercy Hospital and The University of Kansas Medical Center
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Address:
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2401 Gillham Road, Kansas City, MO, 64108,
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Keywords:
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prior elicitation ; exponential ; inverse gamma ; Bayesian ; sample size
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Abstract:
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Investigators need good statistical tools for the initial planning and the ongoing monitoring of clinical trials. In particular, they need to carefully consider the accrual rate-how rapidly patients are being recruited into the clinical trial. A slow accrual decreases the likelihood that the research will provide results at the end of the trial with sufficient precision to make meaningful scientific inferences. In this paper we present a method for predicting accrual across a fixed period of time. Using a Bayesian framework we combine prior information with the information known up to a monitoring point to obtain a prediction. We provide posterior predictive distributions of the accrual. The approach is attractive since it accounts for both epistemic and aleatory uncertainties. We illustrate the approach using actual accrual data.
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