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Postoperative Nomogram Predicting the 10-Year Probability of Prostate Cancer Recurrence After Radical Prostatectomy

From the Department of Urology, Sidney Kimmel Center for Prostate and Urologic Cancers, Memorial Sloan-Kettering Cancer Center, New York, NY; Glickman Urological Institute, and the Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH

Address reprint requests to Michael W. Kattan, PhD, Chair, Department of Quantitative Health Sciences, The Cleveland Clinic Foundation, Wb4, 9500 Euclid Ave, Cleveland, OH 44195; e-mail: kattanm{at}ccf.org

PURPOSE: A postoperative nomogram for prostate cancer recurrence after radical prostatectomy (RP) has been independently validated as accurate and discriminating. We have updated the nomogram by extending the predictions to 10 years after RP and have enabled the nomogram predictions to be adjusted for the disease-free interval that a patient has maintained after RP.

METHODS: Cox regression analysis was used to model the clinical information for 1,881 patients who underwent RP for clinically-localized prostate cancer by two high-volume surgeons. The model was externally validated separately on two independent cohorts of 1,782 patients and 1,357 patients, respectively. Disease progression was defined as a rising prostate-specific antigen (PSA) level, clinical progression, radiotherapy more than 12 months postoperatively, or initiation of systemic therapy.

RESULTS: The 10-year progression-free probability for the modeling set was 79% (95% CI, 75% to 82%). Significant variables in the multivariable model included PSA (P = .002), primary (P < .0001) and secondary Gleason grade (P = .0006), extracapsular extension (P < .0001), positive surgical margins (P = .028), seminal vesicle invasion (P < .0001), lymph node involvement (P = .030), treatment year (P = .008), and adjuvant radiotherapy (P = .046). The concordance index of the nomogram when applied to the independent validation sets was 0.81 and 0.79.

CONCLUSION: We have developed and validated as a robust predictive model an enhanced postoperative nomogram for prostate cancer recurrence after RP. Unique to predictive models, the nomogram predictions can be adjusted for the disease-free interval that a patient has achieved after RP.

Supported in part by the National Cancer Institute Grant No. CA92629 SPORE in prostate cancer and by a gift from the Leon Lowenstein Foundation. A.J.S. and F.J.B. are supported in part by grants from the American Foundation for Urologic Disease, a T32 training Grant No. CA-82088 from the National Institutes of Health, and a gift from the Tina and Richard V. Carolan Foundation.

Presented in part at the 2004 Annual Meeting of the American Urological Association May 8-13, 2004, San Francisco, CA.

Authors’ disclosures of potential conflicts of interest are found at the end of this article.

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