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Updated: Jun 16, 2026
Retzius-Sparing Robot-Assisted Radical Prostatectomy
Published on: May 19, 2022
External validation of the SEARCH model for predicting aggressive recurrence after radical prostatectomy: results
Anna E Teeter1, Leon Sun, Judd W Moul
1Duke Prostate Center, Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA.
Objective:
To validate a model previously developed using the Shared Equal Access Regional Cancer Hospital (SEARCH) database to predict the risk of aggressive recurrence after surgery, defined as a prostate-specific antigen (PSA) doubling time (DT) of <9 months, incorporating pathological stage, preoperative PSA level and pathological Gleason sum, that had an area under the curve (AUC) of 0.79 using a cohort of men from the Duke Prostate Center (DPC).
Patients And Methods:
Data were included from 1989 men from the DPC database who underwent RP for node-negative prostate cancer between 1987 and 2003. Of these men, 100 had disease recurrence, with a PSADT of <9 months, while 1889 either did not have a recurrence but had > or =36 months of follow-up or had a recurrence with a PSADT of > or =9 months. We examined the ability of the SEARCH model to predict aggressive recurrence within the DPC cohort, and examined the correlation between the predicted risk of aggressive recurrence and the actual outcome within DPC.
Results:
The SEARCH model predicted aggressive recurrence within DPC with an AUC of 0.82. There was a strong and significant correlation between the predicted risk of aggressive recurrence based on the SEARCH tables and the actual outcomes within DPC (r= 0.68, P < 0.001), although the model predictions tended to be slightly higher than the actual risk.
Conclusions:
The SEARCH model to predict aggressive recurrence after RP predicted aggressive recurrence in an external dataset with a high degree of accuracy. These tables, now validated, can be used to help select men for adjuvant therapy and clinical trials.
