A Karim Kader1, Michael A Liss2, Greg Trottier3, Seong-Tae Kim4, Jielin Sun4, S Lilly Zheng4, Karen Chadwick3, Gina Lockwood5, Jianfeng Xu4, Neil E Fleshner3. 1. Department of Urology, Moores Cancer Center, University of California San Diego, San Diego, CA. Electronic address: kkader@ucsd.edu. 2. Department of Urology, Moores Cancer Center, University of California San Diego, San Diego, CA. 3. Division of Urology, Department of Surgery, University Health Network, Toronto, Canada. 4. Departments of Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC. 5. Canadian Partnership Against Cancer, Toronto, Canada.
Abstract
OBJECTIVE: To determine to what extent prostate cancer (PCa) risk prediction is improved by adding prostate-specific antigen (PSA) to a baseline model including genetic risk. METHODS: Peripheral blood deoxyribonucleic acid was obtained from Caucasian men undergoing prostate biopsy at the University of Toronto (September 1, 2008 to January 31, 2010). Thirty-three PCa risk-associated single nucleotide polymorphisms were genotyped to generate the prostate cancer genetic score 33 (PGS-33). Primary outcome is PCa on study prostate biopsy. Logistic regression, area under the receiver-operating characteristic curves (AUC), and net reclassification improvement were used to compare models. RESULTS: Among 670 patients, 323 (48.2%) were diagnosed with PCa. The PGS-33 was highly associated with biopsy-detectable PCa (odds ratio, 1.66; P = 5.86E-05; AUC, 0.59) compared with PSA (odds ratio, 1.33; P = .01; AUC, 0.55). PSA did not improve risk prediction when added to a baseline model (age, family history, digital rectal examination, and PGS-33) for overall risk (AUC, 0.66 vs 0.66; P = .86) or Gleason score ≥7 PCa (AUC, 0.71 vs 0.73; P = .15). Net reclassification improvement analyses demonstrated no appropriate reclassifications with the addition of PSA to the baseline model for overall PCa but did show some benefit for reclassification of men thought to be at higher baseline risk in the high-grade PCa analysis. CONCLUSION: In a baseline model of PCa risk including the PGS-33, PSA does not add to risk prediction for overall PCa for men presenting for "for-cause" biopsy. These findings suggest that PSA screening may be minimized in men at low baseline risk.
OBJECTIVE: To determine to what extent prostate cancer (PCa) risk prediction is improved by adding prostate-specific antigen (PSA) to a baseline model including genetic risk. METHODS: Peripheral blood deoxyribonucleic acid was obtained from Caucasian men undergoing prostate biopsy at the University of Toronto (September 1, 2008 to January 31, 2010). Thirty-three PCa risk-associated single nucleotide polymorphisms were genotyped to generate the prostate cancer genetic score 33 (PGS-33). Primary outcome is PCa on study prostate biopsy. Logistic regression, area under the receiver-operating characteristic curves (AUC), and net reclassification improvement were used to compare models. RESULTS: Among 670 patients, 323 (48.2%) were diagnosed with PCa. The PGS-33 was highly associated with biopsy-detectable PCa (odds ratio, 1.66; P = 5.86E-05; AUC, 0.59) compared with PSA (odds ratio, 1.33; P = .01; AUC, 0.55). PSA did not improve risk prediction when added to a baseline model (age, family history, digital rectal examination, and PGS-33) for overall risk (AUC, 0.66 vs 0.66; P = .86) or Gleason score ≥7 PCa (AUC, 0.71 vs 0.73; P = .15). Net reclassification improvement analyses demonstrated no appropriate reclassifications with the addition of PSA to the baseline model for overall PCa but did show some benefit for reclassification of men thought to be at higher baseline risk in the high-grade PCa analysis. CONCLUSION: In a baseline model of PCa risk including the PGS-33, PSA does not add to risk prediction for overall PCa for men presenting for "for-cause" biopsy. These findings suggest that PSA screening may be minimized in men at low baseline risk.
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