Please use this identifier to cite or link to this item:
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.
BUYSE, Marc 
Issue Date: 2012
Source: 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.
Keywords: Principal stratification; Randomized trials; Reproducibility;Biology; Mathematical & Computational Biology; Statistics & Probability; Principal Stratification; Randomized trials; Reproducibility
Document URI:
ISSN: 0006-341X
e-ISSN: 1541-0420
DOI: 10.1111/j.1541-0420.2011.01646.x
ISI #: 000301924400035
Category: A1
Type: Journal Contribution
Validations: ecoom 2013
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
predicting treatment effect.pdf
  Restricted Access
published version593.8 kBAdobe PDFView/Open    Request a copy
Show full item record


checked on Sep 7, 2020


checked on May 21, 2022

Page view(s)

checked on May 23, 2022


checked on May 23, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.