Lifetime Data Analysis

, Volume 14, Issue 1, pp 54–64 | Cite as

Exploring and validating surrogate endpoints in colorectal cancer

  • Tomasz Burzykowski
  • Marc Buyse
  • Greg Yothers
  • Junichi Sakamoto
  • Dan Sargent


Sargent et al (J Clin Oncol 23: 8664–8670, 2005) concluded that 3-year disease-free survival (DFS) can be considered a valid surrogate (replacement) endpoint for 5-year overall survival (OS) in clinical trials of adjuvant chemotherapy for colorectal cancer. We address the question whether the conclusion holds for trials involving other classes of treatments than those considered by Sargent et al. Additionally, we assess if the 3-year cutpoint is an optimal one. To this aim, we investigate whether the results reported by Sargent et al. could have been used to predict treatment effects in three centrally randomized adjuvant colorectal cancer trials performed by the Japanese Foundation for Multidisciplinary Treatment for Cancer (JFMTC) (Sakamoto et al. J Clin Oncol 22:484–492, 2004). Our analysis supports the conclusion of Sargent et al. and shows that using DFS at 2 or 3 years would be the best option for the prediction of OS at 5 years.


Surrogate endpoint Colorectal cancer Surrogate threshold effect 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Biomarkers Definitions Working Group (2001). Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69: 89–95 CrossRefGoogle Scholar
  2. Burzykowski T and Buyse M (2006). Surrogate threshold effect: an alternative measure for meta-analytic surrogate endpoint validation. Pharm Stat 5: 173–186 CrossRefGoogle Scholar
  3. Burzykowski T and Cortiñas Abrahantes J (2005). Validation in case of two failure-time endpoints. In: Burzykowski, T, Molenberghs, G and Buyse, M (eds) Evaluation of Surrogate Endpoints, Springer, New York Google Scholar
  4. Burzykowski T, Molenberghs G, Buyse M, Geys H and Renard D (2001). Validation of surrogate endpoints in multiple randomised clinical trials with failure-time endpoints. J Roy Stat Society C (Appl Stat) 50: 405–422 MATHCrossRefMathSciNetGoogle Scholar
  5. Buyse M, Molenberghs G, Burzykowski T, Renard D and Geys H (2000). The validation of surrogate endpoints in meta-analyses of randomised experiments. Biostatistics 1: 49–68 MATHCrossRefGoogle Scholar
  6. Fuller WA (1987). Measurement error models. Wiley, New York MATHGoogle Scholar
  7. Plackett RL (1965). A class of bivariate distributions. J Am Stat Assoc 60: 516–522 CrossRefMathSciNetGoogle Scholar
  8. Sakamoto J, Ohashi Y, Hamada C, Buyse M, Burzykowski T, Piedbois P for the Meta-Analysis Group of the Japanese Society for Cancer of the Colon and Rectum and the Meta-Analysis Group in Cancer (2004) Efficacy of oral adjuvant therapy after resection of colorectal cancer: 5-year results from three randomized trials. J Clin Oncol 22:484–492Google Scholar
  9. Sargent D, Wieand S and Haller DG et al. (2005). Disease-free survival (DFS) vs. overall survival (OS) as a primary endpoint for adjuvant colon cancer studies: Individual patient data from 20,898 patients on 18 randomized trials. J Clin Oncol 23: 8664–8670 CrossRefGoogle Scholar
  10. Sargent DJ for the ACCENT Group (2007) Time-dependent patterns of failure and treatment benefit from adjuvant therapy for resectable colon cancer: lessons from the 20,800 patient ACCENT dataset. 2007 Gastrointestinal Cancers Symposium, Abstract #274Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Tomasz Burzykowski
    • 1
    • 2
  • Marc Buyse
    • 1
    • 3
  • Greg Yothers
    • 4
  • Junichi Sakamoto
    • 5
  • Dan Sargent
    • 6
  1. 1.Center for StatisticsHasselt UniversityDiepenbeekBelgium
  2. 2.MSOURCE Medical DevelopmentWarsawPoland
  3. 3.IDDI (International Drug Development Institute)Louvain-la-NeuveBelgium
  4. 4.NSABP (National Surgical Adjuvant Breast and Bowel Project) Biostatistical CenterPittsburghUSA
  5. 5.Nagoya University Graduate School of MedicineNagoyaJapan
  6. 6.Mayo Clinic College of MedicineRochesterUSA

Personalised recommendations