https://www.selleckchem.com/products/CI-1040-(PD184352).html 951, C-index = 0.788), which also validated in GSE29623. Prognosis prediction model incorporating multi-RNAs with pathologic distant metastasis (M) and pathologic primary tumor (T) (5-year AUC = 0.969, C-index = 0.812) had better efficiency than clinical prognosis prediction model (5-year AUC = 0.712, C-index = 0.680). In the constructed ceRNA regulatory network, lncRNA NCBP2-AS1 could interact with hsa-miR-34c and hsa-miR-363, and lncRNA LINC00115 could interact with hsa-miR-363 and hsa-miR-4709. SIX4, GRAP, NKAIN4, MMAA, and ERVMER34-1 are regulated by hsa-miR-4709. Prognosis prediction model incorporating multi-RNAs with pathologic M and pathologic T may have great value in COAD prognosis prediction. Prognosis prediction model incorporating multi-RNAs with pathologic M and pathologic T may have great value in COAD prognosis prediction. The current study aimed to compare the efficacy of transition zone PSA density (TZPSAD) with traditional PSA and PSA density (PSAD), for the diagnosis of prostate cancer (PCa) in Taiwanese males. Men with PSA between 4.0 and 20.0ng/ml who underwent a transrectal ultrasound (TRUS) guided prostate biopsy between the studied period were retrospectively identified. The demographic data, PSAD and TZPSAD were calculated in all patients. Receiver operating characteristic (ROC) curves were used to analyze the accuracy of a positive PCa diagnosis. The area under the ROC (AUC) was 0.615, 0.748 and 0.746 for PSA, PSAD and TZPSAD, respectively. The best cut-off of value for TZPSAD in predicting PCa in men with a PSA of 4.0-10.0ng/ml was 0.367ng/ml/ml with a sensitivity of 50% and a specificity of 77.5%. In men with a PSA of 10.1-20.0ng/ml, the best cut-off value was 0.454ng/ml, with a sensitivity of 74.8% and specificity of 70.9%. The use of TZPSAD can improve the efficiency and specificity of PSA for the diagnosis of PCa in Taiwanese men with PSA 4.0-20.0ng/ml. TZPSAD efficiency was