| Literature DB >> 26620456 |
Jeremy Yc Teoh1, Steffi Kk Yuen1, James Hl Tsu1, Charles Kw Wong1, Brian Sh Ho1, Ada Tl Ng1, Wai-Kit Ma1, Kwan-Lun Ho1, Ming-Kwong Yiu1.
Abstract
We investigated the performance characteristics of prostate-specific antigen (PSA) and PSA density (PSAD) in Chinese men. All Chinese men who underwent transrectal ultrasound-guided prostate biopsy (TRUS-PB) from year 2000 to 2013 were included. The receiver operating characteristic (ROC) curves for both PSA and PSAD were analyzed. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at different cut-off levels were calculated. A total of 2606 Chinese men were included. For the ROC, the area under curve was 0.770 for PSA (P < 0.001) and 0.823 for PSAD (P < 0.001). PSA of 4.5 ng ml-1 had sensitivity of 94.4%, specificity of 14.1%, PPV of 29.5%, and NPV of 86.9%; PSAD of 0.12 ng ml-1 cc-1 had sensitivity of 94.5%, specificity of 26.6%, PPV of 32.8%, and NPV of 92.7%. On multivariate logistic regression analyses, PSA cut-off at 4.5 ng ml-1 (OR 1.61, 95% CI 1.05-2.45, P= 0.029) and PSAD cut-off at 0.12 ng ml-1 cc-1 (OR 6.22, 95% CI 4.20-9.22, P< 0.001) were significant predictors for prostate cancer detection on TRUS-PB. In conclusion, the performances of PSA and PSAD at different cut-off levels in Chinese men were very different from those in Caucasians. PSA of 4.5 ng ml-1 and PSAD of 0.12 ng ml-1 cc-1 had near 95% sensitivity and were significant predictors of prostate cancer detection in Chinese men.Entities:
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Year: 2017 PMID: 26620456 PMCID: PMC5227659 DOI: 10.4103/1008-682X.167103
Source DB: PubMed Journal: Asian J Androl ISSN: 1008-682X Impact factor: 3.285
Baseline characteristics of the cohort
Figure 1Receiver operating characteristic curves of PSA and PSAD for prostate cancer detection. PSA: prostate-specific antigen; PSAD: prostate-specific antigen density.
Sensitivity, specificity, PPV, and NPV at different PSA cut-off levels
Sensitivity, specificity, PPV, and NPV at different PSAD cut-off levels
Logistic regression analyses on prostate cancer detection upon TRUS-PB