PurposePrediction models of postoperative outcomes of patients with hepatocellular carcinoma (HCC) after surgery based on the China liver cancer (CNLC) staging system are rare. This study aimed to compare the prognostic abilities of CNLC, Tumor-Node-Metastasis (TNM) 8th edition, and Barcelona Clinic Liver Cancer (BCLC) staging systems for HCC after curative resection. We developed two nomograms incorporating the CNLC staging system to predict the postoperative recurrence-free survival (RFS) and overall survival (OS) of HCC patients.Patients and methodsThe prognostic abilities of the CNLC, TNM and BCLC staging systems for HCC after curative resection were compared using receiver operating characteristic (ROC) curves. Two nomograms incorporating five selected risk factors were constructed based on multivariate Cox regression in the primary cohort of 312 HCC patients. It was validated with an independent validation cohort of 130 HCC patients. The predictive performance and discrimination ability of the two nomograms were further evaluated and compared with those of the TNM and BCLC staging systems.ResultsThe CNLC staging system had a higher area under the receiver operating characteristic curve (AUROC) value for both OS (AUC=0.692) and RFS (AUC=0.673) than the TNM (ROC=0.667 for OS and 0.652 for RFS) and BCLC (ROC=0.671 for OS and 0.670 for RFS) staging systems. The independent predictors of OS (cirrhosis, gamma-glutamyl transpeptidase (GGT), tumor differentiation and CNLC staging system) and RFS (α-fetoprotein (AFP) and CNLC staging system) were incorporated into the two nomograms. The OS and RFS nomograms consistently outperformed the TNM and BCLC staging systems in the primary cohort. These results were verified in the validation cohort. In the 442 patients with HCC, the RFS nomogram could predict early recurrence very well.ConclusionThe two proposed nomograms incorporating the CNLC staging system can predict the outcomes of patients with HCC after curative hepatectomy in clinical practice.
BackgroundProstate cancer (PCa) is the second most common malignant tumor in men worldwide. MiRNAs have been reported to play significant roles in prognosis prediction for patients with malignant tumors.MethodsThe survival-related miRNAs (sDMIRs) were identified by Cox regression analysis. A risk score model (RSM) was established based on three sDMIRs. The expression levels of sDMIRs in cell lines and clinical samples were detected via quantitative polymerase chain reaction. The correlations between sDMIRs and clinicopathological characteristics of PCa patients were evaluated using the chi-square test and Fisher's exact probability method.ResultsFour sDMIRs were remarkably related to the prognosis of PCa patients based on univariate Cox analysis, of which miR-10a-5p, miR-20a-5p, and miR-508-3p were used to establish the RSM. The OS in the low-risk group was better than that in the high-risk group. In the verification of various prostate cell lines and clinical samples from 162 PCa patients, the prominently higher expression of miR-10a-5p and miR-20a-5p and lower expression of miR-508-3p were detected in PCa cell lines and tumor tissues, especially the more advanced T-stage. Besides, the higher expression of miR-20a-5p and miR-10a-5p was significantly correlated to the higher level of PSA, Gleason score, more advanced T-stage, and distant metastasis status.ConclusionWe identify and validate the clinical significance of three sDMIRs and establish a verified RSM to evaluate the prognosis for PCa patients. The findings not only provide a reliable tool for clinical decision-makers to evaluate patients' prognosis but also offer a novel perspective into the field of biomarker identification.
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