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Most pretreatment risk-assessment models to predict biochemical recurrence (BCR) after radical prostatectomy (RP) for prostate cancer rely on total prostate-specific antigen (PSA), clinical stage, and biopsy Gleason grade. We investigated whether free PSA (fPSA) and human glandular kallikrein-2 (hK2) would enhance the predictive accuracy of this standard model. Preoperative serum samples and complete clinical data were available for 1,356 patients who underwent RP for localized prostate cancer from 1993 to 2005. A case-control design was used, and conditional logistic regression models were used to evaluate the association between preoperative predictors and BCR after RP. We constructed multivariable models with fPSA and hK2 as additional preoperative predictors to the base model. Predictive accuracy was assessed with the area under the ROC curve (AUC). There were 146 BCR cases; the median follow up for patients without BCR was 3.2 years. Overall, 436 controls were matched to 146 BCR cases. The AUC of the base model was 0.786 in the entire cohort; adding fPSA and hK2 to this model enhanced the AUC to 0.798 (p=0.053), an effect largely driven by fPSA. In the subgroup of men with total PSA<or=10 ng/ml (48% of cases), adding fPSA and hK2 enhanced the AUC of the base model to a similar degree (from 0.720 to 0.726, p=0.2). fPSA is routinely measured during prostate cancer detection. We suggest that the role of fPSA in aiding preoperative prediction should be investigated in further cohorts.

Original publication

DOI

10.1002/ijc.23983

Type

Journal article

Journal

Int J Cancer

Publication Date

01/02/2009

Volume

124

Pages

659 - 663

Keywords

Area Under Curve, Biomarkers, Tumor, Case-Control Studies, Humans, Male, Neoplasm Recurrence, Local, Predictive Value of Tests, Prognosis, Prostate-Specific Antigen, Prostatectomy, Prostatic Neoplasms, Protein Isoforms, ROC Curve, Tissue Kallikreins