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Validation by calibration of the UCLA integrated staging system prognostic model for nonmetastatic renal cell carcinoma after nephrectomy
Article first published online: 12 MAY 2008
Copyright © 2008 American Cancer Society
Volume 113, Issue 1, pages 65–71, 1 July 2008
How to Cite
Cindolo, L., Chiodini, P., Gallo, C., Ficarra, V., Schips, L., Tostain, J., de La Taille, A., Artibani, W. and Patard, J. J. (2008), Validation by calibration of the UCLA integrated staging system prognostic model for nonmetastatic renal cell carcinoma after nephrectomy. Cancer, 113: 65–71. doi: 10.1002/cncr.23517
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The first 2 authors contributed equally to this work.
- Issue published online: 20 JUN 2008
- Article first published online: 12 MAY 2008
- Manuscript Accepted: 22 FEB 2008
- Manuscript Revised: 15 FEB 2008
- Manuscript Received: 24 JAN 2008
- Italian Ministry of Education, University and Research
- renal cancer;
- University of California at Los Angeles (UCLA);
- Integrated Staging System (UISS);
- validation by calibration
To the authors' knowledge, calibration of the University of California at Los Angeles (UCLA) Integrated Staging System (UISS) prognostic score in patients nephrectomized for nonmetastatic renal cell carcinoma (RCC) has never been specifically addressed. The objective of the current study was to evaluate the calibration of the UISS prognostic score in a European multicenter retrospective study.
Six European centers participated in the study. According to the UISS, the endpoint was overall survival (OS). Survival curves were estimated by the Kaplan-Meier method. For calibration assessment, the approach of ‘validation by calibration’ first proposed by Van Houwelingen was used. The original prognostic score is embedded in a ‘calibration model’ that allows testing, in the validation cohort, the baseline hazards function as well the model linear predictor. Estimates of the ‘calibration model’ were used to recalibrate the UISS score.
Of the 2471 available subjects, 399 had died of any cause within the first 5 years. The observed OS curves were compared with the corresponding expected model-based curves. The UISS model did not adequately predict OS, particularly in the extreme categories (P < .0001). Patients in the validation sample, indeed, fared systematically better than patients in the developing cohort. There was no evidence, instead, of a change in the relative effect of the prognostic covariates. After recalibration, the UISS score worked well in the validation cohort.
The UISS score has good discrimination accuracy and is based on an adequately developed risk function. However, it systematically underestimates OS. At least in a European cohort of RCC patients, the use of the recalibrated UISS model could improve prediction accuracy. Cancer 2008. © 2008 American Cancer Society.