OBJECTIVE: •To compare the Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC) and European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSPC-RC) in a single-institution Canadian cohort. PATIENTS AND METHODS: •At Princess Margaret Hospital, 982 consecutive patients with PCPT-RC and ERSPC-RC covariables were prospectively catalogued before prostate biopsy for suspicion of prostate cancer (PCa). •Receiver-operating characteristic (ROC) curves were generated for each calculator and prostate-specific antigen (PSA). •Comparisons by area under the curve (AUC) and calibration plots were performed. •Predictors of PCa were identified by univariable and multivariable logistic regression. RESULTS: •PCa was detected in 46% and high-grade (HG) PCa (Gleason ≥4) in 23% of subjects with a median PSA level of 6.02 ng/mL. • Multivariable analysis identified transrectal ultrasonography nodule, prostate volume and PSA as the most important predictors of PCa and HG PCa. •ROC curve analysis showed that the ERSPC-RC (AUC = 0.71) outperformed the PCPT-RC (AUC = 0.63) and PSA (AUC = 0.55), for PCa prediction, P < 0.001. •The PCPT-RC was better calibrated in the higher prediction range (40-100%) than the ERSPC-RC, whereas the ERSPC-RC had better calibration and avoided more biopsies in the lower risk range (0-30%). •Discrimination of the ERSPC-RC continued to be superior to the PCPT-RC when the cohort was stratified by different clinical variables. CONCLUSIONS: •The ERSPC-RC had better discrimination for predicting PCa compared to the PCPT-RC in this Canadian cohort. •Calibration would need to be improved to allow routine use of the ERSPC-RC in Canadian practice.
OBJECTIVE: •To compare the Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC) and European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSPC-RC) in a single-institution Canadian cohort. PATIENTS AND METHODS: •At Princess Margaret Hospital, 982 consecutive patients with PCPT-RC and ERSPC-RC covariables were prospectively catalogued before prostate biopsy for suspicion of prostate cancer (PCa). •Receiver-operating characteristic (ROC) curves were generated for each calculator and prostate-specific antigen (PSA). •Comparisons by area under the curve (AUC) and calibration plots were performed. •Predictors of PCa were identified by univariable and multivariable logistic regression. RESULTS: •PCa was detected in 46% and high-grade (HG) PCa (Gleason ≥4) in 23% of subjects with a median PSA level of 6.02 ng/mL. • Multivariable analysis identified transrectal ultrasonography nodule, prostate volume and PSA as the most important predictors of PCa and HG PCa. •ROC curve analysis showed that the ERSPC-RC (AUC = 0.71) outperformed the PCPT-RC (AUC = 0.63) and PSA (AUC = 0.55), for PCa prediction, P < 0.001. •The PCPT-RC was better calibrated in the higher prediction range (40-100%) than the ERSPC-RC, whereas the ERSPC-RC had better calibration and avoided more biopsies in the lower risk range (0-30%). •Discrimination of the ERSPC-RC continued to be superior to the PCPT-RC when the cohort was stratified by different clinical variables. CONCLUSIONS: •The ERSPC-RC had better discrimination for predicting PCa compared to the PCPT-RC in this Canadian cohort. •Calibration would need to be improved to allow routine use of the ERSPC-RC in Canadian practice.
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