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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.
Stephenson et al. (2005) studied this question.