A microRNA-based prediction model for lymph node metastasis in hepatocellular carcinoma
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Li Zhang1,*, Zuo-Lin Xiang1,*, Zhao-Chong Zeng1, Jia Fan2, Zhao-You Tang2, Xiao-Mei Zhao1
1Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
2Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
*These authors have contributed equally to this work
Zuo-Lin Xiang, email: email@example.com
Zhao-Chong Zeng, email: firstname.lastname@example.org
Keywords: hepatocellular carcinoma, lymph node metastasis, microRNA, prediction model, in situ hybridization
Received: September 09, 2015 Accepted: November 22, 2015 Published: December 09, 2015
We developed an efficient microRNA (miRNA) model that could predict the risk of lymph node metastasis (LNM) in hepatocellular carcinoma (HCC). We first evaluated a training cohort of 192 HCC patients after hepatectomy and found five LNM associated predictive factors: vascular invasion, Barcelona Clinic Liver Cancer stage, miR-145, miR-31, and miR-92a. The five statistically independent factors were used to develop a predictive model. The predictive value of the miRNA-based model was confirmed in a validation cohort of 209 consecutive HCC patients. The prediction model was scored for LNM risk from 0 to 8. The cutoff value 4 was used to distinguish high-risk and low-risk groups. The model sensitivity and specificity was 69.6 and 80.2 %, respectively, during 5 years in the validation cohort. And the area under the curve (AUC) for the miRNA-based prognostic model was 0.860. The 5-year positive and negative predictive values of the model in the validation cohort were 30.3 and 95.5 %, respectively. Cox regression analysis revealed that the LNM hazard ratio of the high-risk versus low-risk groups was 11.751 (95 % CI, 5.110–27.021; P < 0.001) in the validation cohort. In conclusion, the miRNA-based model is reliable and accurate for the early prediction of LNM in patients with HCC.
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