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Purpose To improve early detection and risk prediction of prostate cancer, we incorporated the urine urothelial carcinoembryonic antigen 1 (UCA1) gene expression levels and the serum PSA level. Patients and Methods In 897 patients the urine UCA1 gene expression was normalized and the performance of UCA1 score was evaluated by receiver operating characteristic (ROC) curve analysis, the Mann–Whitney U test, or decision curve analysis (DCA). Results In the Shengli training cohort (n = 517), the area under ROC curve (AUC) was 0.880, 0.728, and 0.705 for detecting prostate cancer, D'Amico, and cancer of the prostate risk assessment (CAPRA), respectively. The UCA1 scores of benign patients were significantly lower than those of nonhigh‐risk prostate cancer patients (−2.63 vs. 0.16, p < 0.001; AUC 0.834). DCA yielded a better result with the UCA1 score compared to PSA. Combining PSA <4 with UCA1 score ≥−0.475, all nine of 62 patients were successfully diagnosed with prostate cancer and 70.97% of prostate biopsies were excluded. Using PSA ≥4 and UCA1 score ≥−3.47, 122 cancer patients were accurately diagnosed with a sensitivity of 0.992, while 102 prostate biopsies (22.42%) were excluded. Similar results were validated in the Fuzhou validation cohort (n = 380). In all patients of two cohort (n = 897), the UCA1 score was superior to PSA only for detection of clinically significant cancer (28% VS. 22%, p = 0.007) and detection of high‐risk cancer (25% VS. 19%, p = 0.009). Conclusion The performance of the UCA1 score is superior to that of the existing PSA only in the detection and risk prediction of prostate cancer. Combination of the PSA level and the UCA1 score may significantly reduce the burden of prostate biopsy.

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