INTRODUCTION: Prostate-specific antigen (PSA) and the digital rectal exam (DRE) have moderate sensitivity but low specificity for cancer diagnosis, potentially causing unnecessary treatment complications with prostate biopsy. Transrectal ultrasound (TRUS) to evaluate prostate size and calculate PSA density can improve the specificity of PSA in predicting cancer. We evaluated the sensitivity and specificity of different pre-biopsy tests to detect prostate cancer. MATERIALS AND METHODS: Pre-biopsy data were collected from 521 men referred for biopsy from January-December 2011 and cancer aggressiveness data from 96 men who had radical prostatectomy. Model predictors included total PSA, DRE, the ratio of free to total PSA (PSAf/t), and PSA density. We used logistic regression and ROC curve analyses to compare the accuracy of different models to predict positive biopsy. RESULTS: The area under the curve (AUC) for model A (PSA total, DRE, PSAf/t) was moderate, but significant (AUC = .59, p < .05); only PSAf/t was a significant independent predictor of positive biopsy (OR = .002, p < .05). In model B (PSAf/t and PSA density; AUC= .66, p < .05), PSA density was the only strong predictor (OR = 1067.93, p < .05). Both models had comparable sensitivity (74% versus 72%) but model B had greater specificity (44% versus 61%). PSA density was also a significant predictor of different indices of aggressive cancer. CONCLUSIONS: PSA density has discriminative predictive power for prostate cancer. It had similar sensitivity, but greater specificity compared to using PSA total, DRE and PSAf/t. These results support the value of using PSA density to improve prediction of prostate cancer and reduce unnecessary biopsies.
INTRODUCTION:Prostate-specific antigen (PSA) and the digital rectal exam (DRE) have moderate sensitivity but low specificity for cancer diagnosis, potentially causing unnecessary treatment complications with prostate biopsy. Transrectal ultrasound (TRUS) to evaluate prostate size and calculate PSA density can improve the specificity of PSA in predicting cancer. We evaluated the sensitivity and specificity of different pre-biopsy tests to detect prostate cancer. MATERIALS AND METHODS: Pre-biopsy data were collected from 521 men referred for biopsy from January-December 2011 and cancer aggressiveness data from 96 men who had radical prostatectomy. Model predictors included total PSA, DRE, the ratio of free to total PSA (PSAf/t), and PSA density. We used logistic regression and ROC curve analyses to compare the accuracy of different models to predict positive biopsy. RESULTS: The area under the curve (AUC) for model A (PSA total, DRE, PSAf/t) was moderate, but significant (AUC = .59, p < .05); only PSAf/t was a significant independent predictor of positive biopsy (OR = .002, p < .05). In model B (PSAf/t and PSA density; AUC= .66, p < .05), PSA density was the only strong predictor (OR = 1067.93, p < .05). Both models had comparable sensitivity (74% versus 72%) but model B had greater specificity (44% versus 61%). PSA density was also a significant predictor of different indices of aggressive cancer. CONCLUSIONS:PSA density has discriminative predictive power for prostate cancer. It had similar sensitivity, but greater specificity compared to using PSA total, DRE and PSAf/t. These results support the value of using PSA density to improve prediction of prostate cancer and reduce unnecessary biopsies.
Authors: David Turay; Salma Khan; Carlos J Diaz Osterman; Matthew P Curtis; Balreet Khaira; Jonathan W Neidigh; Saied Mirshahidi; Carlos A Casiano; Nathan R Wall Journal: Cancer Invest Date: 2015-11-04 Impact factor: 2.176
Authors: Kai Wang; Xinguang Chen; Ting-Yuan David Cheng; Peihua Qiu; Victoria Y Bird; Mattia Prosperi Journal: Horm Cancer Date: 2019-10-16 Impact factor: 3.869