• Ming Chen, Ting Ma, Jun Li, Hai-Jun Zhang, Qiang Li, Jia-Jia Wang, Tian Sang, Chun-Li Cao, and Xin-Wu Cui.
• Department of Ultrasound, The First Affiliated Hospital of The Medical College, Shihezi University, Shihezi, Xinjiang, China (mainland).
• Med. Sci. Monit. 2021 Feb 8; 27: e929913.

AbstractBACKGROUND Two diagnostic models of prostate cancer (PCa) and clinically significant prostate cancer (CS-PCa) were established using clinical data of among patients whose prostate-specific antigen (PSA) levels are in the gray area (4.0-10.0 ng/ml). MATERIAL AND METHODS Data from 181 patients whose PSA levels were in the gray area were retrospectively analyzed, and the following data were collected: age, digital rectal examination, total PSA, PSA density (PSAD), free/total PSA (f/t PSA), transrectal ultrasound, multiparametric magnetic resonance imaging (mpMRI), and pathological reports. Patients were diagnosed with benign prostatic hyperplasia (BPH) and PCa by pathology reports, and PCa patients were separated into non-clinically significant PCa (NCS-PCa) and CS-PCa by Gleason score. Afterward, predictor models constructed by above parameters were researched to diagnose PCa and CS-PCa, respectively. RESULTS According to the analysis of included clinical data, there were 109 patients with BPH, 44 patients with NCS-PCa, and 28 patients with CS-PCa. Regression analysis showed PCa was correlated with f/t PSA, PSAD, and mpMRI (P<0.01), and CS-PCa was correlated with PSAD and mpMRI (P<0.01). The area under the receiver operating characteristic curves of 2 models for PCa (sensitivity=73.64%, specificity=64.23%) and for CS-PCa (sensitivity=71.41%, specificity=81.82%) were 0.79 and 0.87, respectively. CONCLUSIONS The prediction models had satisfactory diagnostic value for PCa and CS-PCa among patients with PSA in the gray area, and use of these models may help reduce overdiagnosis.

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