Do nomograms predict aggressive recurrence after radical prostatectomy more accurately than biochemical recurrence alone?
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Updated: Jun 27, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Florian R Schroeck1, William J Aronson, Joseph C Presti
1Division of Urologic Surgery, Department of Surgery, and Duke Prostate Center, Duke University Medical Center, Durham, NC 27710, USA.
Objective:
To compare the predictive accuracy (PA) of existing models in estimating risk of biochemical recurrence (BCR) vs aggressive recurrence (BCR with a prostate-specific antigen, PSA, doubling time, DT, of <9 months).
Patients And Methods:
The study included 1550 men treated with radical prostatectomy (RP) between 1988 and 2007 within the Shared Equal Access Regional Cancer Hospital database. The PA of nine different risk stratification models for estimating risk of BCR and risk of aggressive recurrence after RP was assessed using the concordance index, c.
Results:
The 10-year risks of BCR and aggressive recurrence were 47% and 9%, respectively. Across all nine models tested, the PA was a mean (range) of 0.054 (0.024-0.074) points higher for predicting aggressive recurrence than for predicting BCR alone (c = 0.756 vs 0.702). Similar results were obtained in four sensitivity analyses: (i) defining patients with BCR but unavailable PSADT (220) as having aggressive recurrence; (ii) defining these patients as not having aggressive recurrence; (iii) defining aggressive recurrence as a PSADT of <6 months; or (iv) defining aggressive recurrence as a PSADT of <12 months. The improvement in PA was greater for preoperative than for postoperative models (0.053 vs 0.036, P = 0.03).
Conclusion:
Across nine different models the prediction of aggressive recurrence after RP was more accurate than the prediction of BCR alone. This is probably because current models mainly assess cancer biology, which correlates better with aggressive recurrence than with BCR alone. Overall, all models had relatively similar accuracy for predicting aggressive recurrence.
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