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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13715

Title: Predicting Treatment Effect from Surrogate Endpoints and Historical Trials: An Extrapolation Involving Probabilities of a Binary Outcome or Survival to a Specific Time
Authors: Baker, Stuart G.
Sargent, Daniel J.
Issue Date: 2012
Citation: BIOMETRICS, 68 (1), p. 248-257
Abstract: Using multiple historical trials with surrogate and true endpoints, we consider various models to predict the effect of treatment on a true endpoint in a target trial in which only a surrogate endpoint is observed. This predicted result is computed using (1) a prediction model (mixture, linear, or principal stratification) estimated from historical trials and the surrogate endpoint of the target trial and (2) a random extrapolation error estimated from successively leaving out each trial among the historical trials. The method applies to either binary outcomes or survival to a particular time that is computed from censored survival data. We compute a 95% confidence interval for the predicted result and validate its coverage using simulation. To summarize the additional uncertainty from using a predicted instead of true result for the estimated treatment effect, we compute its multiplier of standard error. Software is available for download.
Notes: [Baker, Stuart G.] NCI, Bethesda, MD 20892 USA. [Sargent, Daniel J.] Mayo Clin, Rochester, MN 55905 USA. [Buyse, Marc] IDDI, B-1340 Louvain, Belgium. [Burzykowski, Tomasz] Hasselt Univ, B-3590 Diepenbeek, Belgium. sb16i@nih.gov
URI: http://hdl.handle.net/1942/13715
DOI: 10.1111/j.1541-0420.2011.01646.x
ISI #: 000301924400035
ISSN: 0006-341X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2013
Appears in Collections: Research publications

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