Friday, April 29, 2011

Simulating randomized withdrawal studies for prediction & management

Title of talk: Signs of the Timings: Predicting Time of Completion in Multiphase Survival Trials

Paper as published in the conference proceedings: Predicting Time of Completion in Multiphase Survival Trials


Studying maintenance of clinical effect typically requires clinical response for a minimum amount of time on treatment before randomization. If randomized, patients are then followed until treatment failure or withdrawal, and the trial halted after a pre-specified 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; Predictions are updated as information is accrued.

Presented to:
Joint Statistical Meeting of the American Statistical Association
Seattle, WA
August, 2006

Delaware Chapter of the American Statistical Association
Dinner Meeting: September 21, 2006

Speaker: Dennis E. Sweitzer


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  2. Hi Dennis,
    If you're consulting, please contact me​ as soon as possible.