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Validation of surrogate end points in multiple randomized clinical trials with failure time end points

Author

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  • Tomasz Burzykowski
  • Geert Molenberghs
  • Marc Buyse
  • Helena Geys
  • Didier Renard

Abstract

Before a surrogate end point can replace a final (true) end point in the evaluation of an experimental treatment, it must be formally ‘validated’. The validation will typically require large numbers of observations. It is therefore useful to consider situations in which data are available from several randomized experiments. For two normally distributed end points Buyse and co‐workers suggested a new definition of validity in terms of the quality of both trial level and individual level associations between the surrogate and true end points. This paper extends this approach to the important case of two failure time end points, using bivariate survival modelling. The method is illustrated by using two actual sets of data from cancer clinical trials.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jorssc:v:50:y:2001:i:4:p:405-422
    DOI: 10.1111/1467-9876.00244
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    Cited by:

    1. Welz, Thilo & Viechtbauer, Wolfgang & Pauly, Markus, 2023. "Cluster-robust estimators for multivariate mixed-effects meta-regression," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    2. Hirofumi Michimae & Takeshi Emura, 2022. "Bayesian ridge estimators based on copula-based joint prior distributions for regression coefficients," Computational Statistics, Springer, vol. 37(5), pages 2741-2769, November.
    3. 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.
    4. Debashis Ghosh & Jeremy M. G. Taylor & Daniel J. Sargent, 2012. "Meta-analysis for Surrogacy: Accelerated Failure Time Models and Semicompeting Risks Modeling," Biometrics, The International Biometric Society, vol. 68(1), pages 226-232, March.
    5. 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.
    6. Layla Parast & Lu Tian & Tianxi Cai, 2020. "Assessing the value of a censored surrogate outcome," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 245-265, April.
    7. Ghosh Debashis, 2008. "On the Plackett Distribution with Bivariate Censored Data," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-24, May.
    8. Steffen Fieuws & Geert Verbeke, 2006. "Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles," Biometrics, The International Biometric Society, vol. 62(2), pages 424-431, June.
    9. Casimir Ledoux Sofeu & Virginie Rondeau, 2020. "How to use frailtypack for validating failure-time surrogate endpoints using individual patient data from meta-analyses of randomized controlled trials," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-25, January.
    10. Ariel Alonso & Helena Geys & Geert Molenberghs & Michael G. Kenward & Tony Vangeneugden, 2004. "Validation of Surrogate Markers in Multiple Randomized Clinical Trials with Repeated Measurements: Canonical Correlation Approach," Biometrics, The International Biometric Society, vol. 60(4), pages 845-853, December.
    11. Renfro, Lindsay A. & Shi, Qian & Xue, Yuan & Li, Junlong & Shang, Hongwei & Sargent, Daniel J., 2014. "Center-within-trial versus trial-level evaluation of surrogate endpoints," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 1-20.
    12. Layla Parast & Tianxi Cai & Lu Tian, 2023. "Testing for heterogeneity in the utility of a surrogate marker," Biometrics, The International Biometric Society, vol. 79(2), pages 799-810, June.
    13. Shi, Qian & Renfro, Lindsay A. & Bot, Brian M. & Burzykowski, Tomasz & Buyse, Marc & Sargent, Daniel J., 2011. "Comparative assessment of trial-level surrogacy measures for candidate time-to-event surrogate endpoints in clinical trials," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2748-2757, September.
    14. Lindsay A. Renfro & Bradley P. Carlin & Daniel J. Sargent, 2012. "Bayesian Adaptive Trial Design for a Newly Validated Surrogate Endpoint," Biometrics, The International Biometric Society, vol. 68(1), pages 258-267, March.
    15. Debashis Ghosh, 2009. "On Assessing Surrogacy in a Single Trial Setting Using a Semicompeting Risks Paradigm," Biometrics, The International Biometric Society, vol. 65(2), pages 521-529, June.
    16. Xiaoyun Li & Cong Chen & Wen Li, 2018. "Adaptive Biomarker Population Selection in Phase III Confirmatory Trials with Time-to-Event Endpoints," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(2), pages 324-341, August.
    17. Erin E. Gabriel & Michael J. Daniels & M. Elizabeth Halloran, 2016. "Comparing biomarkers as trial level general surrogates," Biometrics, The International Biometric Society, vol. 72(4), pages 1046-1054, December.
    18. Bo-Hong Wu & Hirofumi Michimae & Takeshi Emura, 2020. "Meta-analysis of individual patient data with semi-competing risks under the Weibull joint frailty–copula model," Computational Statistics, Springer, vol. 35(4), pages 1525-1552, December.
    19. Debashis Ghosh, 2008. "Semiparametric Inference for Surrogate Endpoints with Bivariate Censored Data," Biometrics, The International Biometric Society, vol. 64(1), pages 149-156, March.
    20. Lorna Wheaton & Anastasios Papanikos & Anne Thomas & Sylwia Bujkiewicz, 2023. "Using Bayesian Evidence Synthesis Methods to Incorporate Real-World Evidence in Surrogate Endpoint Evaluation," Medical Decision Making, , vol. 43(5), pages 539-552, July.
    21. 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.

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