IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v78y2014icp1-20.html
   My bibliography  Save this article

Center-within-trial versus trial-level evaluation of surrogate endpoints

Author

Listed:
  • Renfro, Lindsay A.
  • Shi, Qian
  • Xue, Yuan
  • Li, Junlong
  • Shang, Hongwei
  • Sargent, Daniel J.

Abstract

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:csdana:v:78:y:2014:i:c:p:1-20
    DOI: 10.1016/j.csda.2014.03.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947314000887
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2014.03.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Didier Renard & Helena Geys & Geert Molenberghs & Tomasz Burzykowski & Marc Buyse & Tony Vangeneugden & Luc Bijnens, 2003. "Validation of a longitudinally measured surrogate marker for a time-to-event endpoint," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(2), pages 235-247.
    3. Abrahantes, Jose Cortinas & Molenberghs, Geert & Burzykowski, Tomasz & Shkedy, Ziv & Abad, Ariel Alonso & Renard, Didier, 2004. "Choice of units of analysis and modeling strategies in multilevel hierarchical models," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 537-563, October.
    4. Ariel Alonso & Geert Molenberghs & Tomasz Burzykowski & Didier Renard & Helena Geys & Ziv Shkedy & Fabián Tibaldi & José Cortiñas Abrahantes & Marc Buyse, 2004. "Prentice's Approach and the Meta-Analytic Paradigm: A Reflection on the Role of Statistics in the Evaluation of Surrogate Endpoints," Biometrics, The International Biometric Society, vol. 60(3), pages 724-728, September.
    5. 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.
    6. Ariel Alonso & Geert Molenberghs, 2007. "Surrogate Marker Evaluation from an Information Theory Perspective," Biometrics, The International Biometric Society, vol. 63(1), pages 180-186, March.
    7. 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.
    8. Tilahun, Abel & Pryseley, Assam & Alonso, Ariel & Molenberghs, Geert, 2007. "Flexible surrogate marker evaluation from several randomized clinical trials with continuous endpoints, using R and SAS," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4152-4163, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Ariel Alonso & Geert Molenberghs, 2007. "Surrogate Marker Evaluation from an Information Theory Perspective," Biometrics, The International Biometric Society, vol. 63(1), pages 180-186, March.
    3. Emily K. Roberts & Michael R. Elliott & Jeremy M. G. Taylor, 2023. "Solutions for surrogacy validation with longitudinal outcomes for a gene therapy," Biometrics, The International Biometric Society, vol. 79(3), pages 1840-1852, September.
    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. Geert Molenberghs, 2012. "Discussion Contribution to 091037PR4 (Ghosh, Taylor, and Sargent)," Biometrics, The International Biometric Society, vol. 68(1), pages 233-235, March.
    6. Cortiñas Abrahantes, José & Burzykowski, Tomasz, 2010. "Simplified modeling strategies for surrogate validation with multivariate failure-time data," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1457-1466, June.
    7. Pryseley, Assam & Tilahun, Abel & Alonso, Ariel & Molenberghs, Geert, 2010. "Using earlier measures in a longitudinal sequence as a potential surrogate for a later one," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1342-1354, May.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Margaux Delporte & Steffen Fieuws & Geert Molenberghs & Geert Verbeke & Simeon Situma Wanyama & Elpis Hatziagorou & Christiane De Boeck, 2022. "A joint normal‐binary (probit) model," International Statistical Review, International Statistical Institute, vol. 90(S1), pages 37-51, December.
    14. 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.
    15. John O'Quigley & Philippe Flandre, 2006. "Quantification of the Prentice Criteria for Surrogate Endpoints," Biometrics, The International Biometric Society, vol. 62(1), pages 297-300, March.
    16. Yongming Qu & Michael Case, 2007. "Quantifying the Effect of the Surrogate Marker by Information Gain," Biometrics, The International Biometric Society, vol. 63(3), pages 958-960, September.
    17. 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.
    18. 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.
    19. Ariel Alonso & Wim Van der Elst & Geert Molenberghs & Marc Buyse & Tomasz Burzykowski, 2015. "On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpoints," Biometrics, The International Biometric Society, vol. 71(1), pages 15-24, 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:78:y:2014:i:c:p:1-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.