External validation of the SEARCH model for predicting aggressive recurrence after radical prostatectomy: results from the Duke Prostate Center Database.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Teeter, AE; Sun, L; Moul, JW; Freedland, SJ

Published Date

  • September 2010

Published In

Volume / Issue

  • 106 / 6

Start / End Page

  • 796 - 800

PubMed ID

  • 20151967

Pubmed Central ID

  • PMC2891130

Electronic International Standard Serial Number (EISSN)

  • 1464-410X

Digital Object Identifier (DOI)

  • 10.1111/j.1464-410X.2010.09214.x


  • eng

Conference Location

  • England