PURPOSE: The online Prostate Cancer Prevention Trial risk calculator combines prostate specific antigen, digital rectal examination, family and biopsy history, age and race to determine the risk of prostate cancer. In this report we incorporate the biomarker prostate cancer gene 3 into the Prostate Cancer Prevention Trial risk calculator. MATERIALS AND METHODS: Methodology was developed to incorporate new markers for prostate cancer into the Prostate Cancer Prevention Trial risk calculator based on likelihood ratios calculated from separate case control or cohort studies. The methodology was applied to incorporate the marker prostate cancer gene 3 into the risk calculator based on a cohort of 521 men who underwent prostate biopsy with measurements of urinary prostate cancer gene 3, serum prostate specific antigen, digital rectal examination and biopsy history. External validation of the updated risk calculator was performed on a cohort of 443 European patients, and compared to Prostate Cancer Prevention Trial risks, prostate specific antigen and prostate cancer gene 3 by area underneath the receiver operating characteristic curve, sensitivity and specificity. RESULTS: The AUC of posterior risks (AUC 0.696, 95% CI 0.641-0.750) was higher than that of prostate specific antigen (AUC 0.607, 95% CI 0.546-0.668, p = 0.001) and Prostate Cancer Prevention Trial risks (AUC 0.653, 95% CI 0.593-0.714, p <0.05). Although it was higher it was not statistically significantly different from that of prostate cancer gene 3 (AUC 0.665, 95% CI 0.610-0.721, p >0.05). Sensitivities of posterior risks were higher than those of prostate cancer gene 3, prostate specific antigen and Prostate Cancer Prevention Trial risks. CONCLUSIONS: New markers for prostate cancer can be incorporated into the Prostate Cancer Prevention Trial risk calculator by a novel approach. Incorporation of prostate cancer gene 3 improved the diagnostic accuracy of the Prostate Cancer Prevention Trial risk calculator.
PURPOSE: The online Prostate Cancer Prevention Trial risk calculator combines prostate specific antigen, digital rectal examination, family and biopsy history, age and race to determine the risk of prostate cancer. In this report we incorporate the biomarker prostate cancer gene 3 into the Prostate Cancer Prevention Trial risk calculator. MATERIALS AND METHODS: Methodology was developed to incorporate new markers for prostate cancer into the Prostate Cancer Prevention Trial risk calculator based on likelihood ratios calculated from separate case control or cohort studies. The methodology was applied to incorporate the marker prostate cancer gene 3 into the risk calculator based on a cohort of 521 men who underwent prostate biopsy with measurements of urinary prostate cancer gene 3, serum prostate specific antigen, digital rectal examination and biopsy history. External validation of the updated risk calculator was performed on a cohort of 443 European patients, and compared to Prostate Cancer Prevention Trial risks, prostate specific antigen and prostate cancer gene 3 by area underneath the receiver operating characteristic curve, sensitivity and specificity. RESULTS: The AUC of posterior risks (AUC 0.696, 95% CI 0.641-0.750) was higher than that of prostate specific antigen (AUC 0.607, 95% CI 0.546-0.668, p = 0.001) and Prostate Cancer Prevention Trial risks (AUC 0.653, 95% CI 0.593-0.714, p <0.05). Although it was higher it was not statistically significantly different from that of prostate cancer gene 3 (AUC 0.665, 95% CI 0.610-0.721, p >0.05). Sensitivities of posterior risks were higher than those of prostate cancer gene 3, prostate specific antigen and Prostate Cancer Prevention Trial risks. CONCLUSIONS: New markers for prostate cancer can be incorporated into the Prostate Cancer Prevention Trial risk calculator by a novel approach. Incorporation of prostate cancer gene 3 improved the diagnostic accuracy of the Prostate Cancer Prevention Trial risk calculator.
Authors: Yuanyuan Liang; Jamie C Messer; Christopher Louden; Miguel A Jimenez-Rios; Ian M Thompson; Hector R Camarena-Reynoso Journal: Urol Oncol Date: 2012-02-03 Impact factor: 3.498
Authors: Donna P Ankerst; Josef Hoefler; Sebastian Bock; Phyllis J Goodman; Andrew Vickers; Javier Hernandez; Lori J Sokoll; Martin G Sanda; John T Wei; Robin J Leach; Ian M Thompson Journal: Urology Date: 2014-06 Impact factor: 2.649
Authors: David J Kaplan; Stephen A Boorjian; Karen Ruth; Brian L Egleston; David Y T Chen; Rosalia Viterbo; Robert G Uzzo; Mark K Buyyounouski; Susan Raysor; Veda N Giri Journal: BJU Int Date: 2009-08-25 Impact factor: 5.588