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The validation of surrogate end points by using data from randomized clinical trials: a case‐study in advanced colorectal cancer

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  • Tomasz Burzykowski
  • Geert Molenberghs
  • Marc Buyse

Abstract

Summary. In many therapeutic areas, the identification and validation of surrogate end points is of prime interest to reduce the duration and/or size of clinical trials. Buyse and co‐workers and Burzykowski and co‐workers have proposed a validation strategy for end points that are either normally distributed or (possibly censored) failure times. In this paper, we address the problem of validating an ordinal categorical or binary end point as a surrogate for a failure time true end point. In particular, we investigate the validity of tumour response as a surrogate for survival time in evaluating fluoropyrimidine‐based experimental therapies for advanced colorectal cancer. Our analysis is performed on data from 28 randomized trials in advanced colorectal cancer, which are available through the Meta‐Analysis Group in Cancer.

Suggested Citation

  • Tomasz Burzykowski & Geert Molenberghs & Marc Buyse, 2004. "The validation of surrogate end points by using data from randomized clinical trials: a case‐study in advanced colorectal cancer," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(1), pages 103-124, February.
    • Handle: RePEc:bla:jorssa:v:167:y:2004:i:1:p:103-124
    DOI: 10.1111/j.1467-985X.2004.00293.x
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    References listed on IDEAS

    as
    1. C. B. Begg & D. H. Y. Leung, 2000. "On the use of surrogate end points in randomized trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(1), pages 15-28.
    2. Ding, Cherng G., 1996. "On the computation of the distribution of the square of the sample multiple correlation coefficient," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 345-350, August.
    3. Tomasz Burzykowski & Geert Molenberghs & Marc Buyse & Helena Geys & Didier Renard, 2001. "Validation of surrogate end points in multiple randomized clinical trials with failure time end points," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(4), pages 405-422.
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    1. Goele Massonnet & Paul Janssen & Tomasz Burzykowski, 2008. "Fitting Conditional Survival Models to Meta‐Analytic Data by Using a Transformation Toward Mixed‐Effects Models," Biometrics, The International Biometric Society, vol. 64(3), pages 834-842, September.
    2. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    3. Arielle Anderer & Hamsa Bastani & John Silberholz, 2022. "Adaptive Clinical Trial Designs with Surrogates: When Should We Bother?," Management Science, INFORMS, vol. 68(3), pages 1982-2002, March.
    4. Rui Zhuang & Ying Qing Chen, 2020. "Measuring Surrogacy in Clinical Research," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 295-323, December.
    5. A. E. Ades & A. J. Sutton, 2006. "Multiparameter evidence synthesis in epidemiology and medical decision‐making: current approaches," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(1), pages 5-35, January.
    6. Stuart G. Baker & Daniel J. Sargent & Marc Buyse & Tomasz Burzykowski, 2012. "Predicting Treatment Effect from Surrogate Endpoints and Historical Trials: An Extrapolation Involving Probabilities of a Binary Outcome or Survival to a Specific Time," Biometrics, The International Biometric Society, vol. 68(1), pages 248-257, March.

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