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Activity Number:
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381
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Type:
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Contributed
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Date/Time:
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Wednesday, August 9, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #305589 |
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Title:
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Predicting Time of Completion in Multiphase Survival Trials
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Author(s):
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Dennis Sweitzer*+
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Companies:
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AstraZeneca Pharmaceuticals
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Address:
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438 Gum Tree Road, Coatesville, PA, 19320,
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Keywords:
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clinical trial ; survival ; maintenance of effect ; trial management ; simulation
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Abstract:
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Studying maintenance of clinical effect typically requires clinical response for a minimum amount of time on treatment before randomization. If randomized, patients are followed until treatment failure or withdrawal, and the trial is halted after a prespecified number of events. For ethical and cost reasons, it is desirable to minimize the number of patients enrolled and randomized and to predict the time of the last event under multiple scenarios. We describe a data-driven stochastic simulation for two such trials in which each phase is modeled as a competing event process; distributions of event times are derived from Kaplan-Meier survival curves from available data; parameter uncertainty is modeled based on K-M survival estimates; withdrawals and events occur at similar overall rates, though at different times; and predictions are updated as information is accrued.
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