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Cut-Off Estimation and Medical Decision Making Based on a Continuous Prognostic Factor: The Prediction of Kidney Graft Failure


  • Foucher Yohann

    (Nantes University)

  • Giral Magali

    (INSERM U643)

  • Soulillou Jean-Paul

    (INSERM U643)

  • Daurès Jean-Pierre

    (University Institut of Clinical Research)


The determination of a cut-off value for a continuous prognostic test is an important problem, which is statistically challenging and practically important for risk assessment. We propose in this paper a method to estimate the optimal cut-off from this type of longitudinal data with censored failure times. The principle is to combine the prognostic error rates of false positives and false negatives with a cost function, which has the advantages to be statistically convenient and to be directly associated with the decision-making. Simulations were performed and the results demonstrate the interest of our approach compared to a reference method. The method is also illustrated by predicting the long-term survival of kidney transplant recipients from the 1-year creatinine clearance.

Suggested Citation

  • Foucher Yohann & Giral Magali & Soulillou Jean-Paul & Daurès Jean-Pierre, 2012. "Cut-Off Estimation and Medical Decision Making Based on a Continuous Prognostic Factor: The Prediction of Kidney Graft Failure," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-13, January.
  • Handle: RePEc:bpj:ijbist:v:8:y:2012:i:1:n:1

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    References listed on IDEAS

    1. Patrick J. Heagerty & Yingye Zheng, 2005. "Survival Model Predictive Accuracy and ROC Curves," Biometrics, The International Biometric Society, vol. 61(1), pages 92-105, March.
    2. Contal, Cecile & O'Quigley, John, 1999. "An application of changepoint methods in studying the effect of age on survival in breast cancer," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 253-270, May.
    3. Patrick J. Heagerty & Thomas Lumley & Margaret S. Pepe, 2000. "Time-Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker," Biometrics, The International Biometric Society, vol. 56(2), pages 337-344, June.
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