Cut-Off Estimation and Medical Decision Making Based on a Continuous Prognostic Factor: The Prediction of Kidney Graft Failure
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.
Volume (Year): 8 (2012)
Issue (Month): 1 (January)
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- 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.
- 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.
- 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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