06 November 2019 : Clinical Research
Significant Diagnostic Value of Free-Serum PSA (FPSA)/Prostate-Specific Antigen Density (PSAD) and (F/T)/PSAD for Prostate Cancer of the Chinese Population in a Single Institution
Li-Bin Nan1AE, Xiao-Tao Yin1CF, Jiang-Ping Gao1G*DOI: 10.12659/MSM.916900
Med Sci Monit 2019; 25:8345-8351
Abstract
BACKGROUND: The aim of this study was to investigate the diagnostic value of (F/T)/PSAD for prostate cancer detection in the Chinese population.
MATERIAL AND METHODS: Data were collected retrospectively from patients with prostate cancer or benign prostatic hyperplasia from July 2009 to September 2014. SPSS 19.0 software was used for the receiver operating characteristic curve (ROC), and calculating sensitivity, specificity, and positive predictive values (PPV) and negative predictive values (NPV), respectively. Comparison of the area under ROC (AUC) was performed using the MedCalc v. 10.4.7.0 software.
RESULTS: A total of 660 patients (including 251 patients with prostate cancer and 409 patients with prostatic hyperplasia) were included. Prostate volume (PV), prostate-specific antigen density (PSAD), free-serum PSA (FPSA)/PSAD, and free-to-total PSA (F/T)/PSAD had similar AUC (P>0.05), and had significantly higher AUC (P<0.001) than F/T, total-serum PSA (TPSA), and free-serum PSA (FPSA). Based on the optimal cutoff value, the sensitivity of (F/T)/PSAD and FPSA/PSAD was similar (P>0.05), and significantly higher than the PV and PSAD (P<0.05). The logistic regression model using a combination of age, FPSA, PV, PSAD, FPSA/PSAD, and (F/T)/PSAD showed higher AUC than each one alone (P<0.001).
CONCLUSIONS: (F/T)/PSAD can be used as a predictor for prostate cancer in the Chinese population aged >50 years and has a significantly lower false negative rate than PSAD and PV with a cutoff value of ≤0.731. A new parameter, FPSA/PSAD, has similar diagnostic accuracy comparable to (F/T)/PSAD. The diagnostic value of a combination of age, FPSA, PV, PSAD, FPSA/PSAD, and (F/T)/PSAD needs further investigation.
Keywords: Diagnosis, Prostate-Specific Antigen, Prostatic Neoplasms, Area Under Curve, Asians, Biopsy, Kallikreins, Logistic Models, Prostate, Prostatic Hyperplasia, ROC Curve, Sensitivity and Specificity, serum
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