BACKGROUND: We aimed to develop a clinicopathological model that would predict the risk of bone metastasis (BM) in hepatocellular carcinoma (HCC). METHODS: We first evaluated a training cohort of 201 HCC patients who had undergone hepatectomy and found that the following factors independently predicted BM development: vascular invasion, tumor-node-metastasis stage, CXCR4, connective tissue growth factor, and interleukin-11. These variables were used to construct a clinicopathological prediction model that may be scored from 0 to 19. The predictive value of the model was demonstrated in a validation cohort of 179 post-hepatectomy HCC patients. RESULTS: During a median follow-up of 54.3 months for the training cohort and 52.5 months for the validation cohort, 23 patients (11.4%) in the former and 19 patients (10.6%) in the latter developed BM. A cutoff value of 9.4 best discriminated BM risk and was able to exclude future BM development with high accuracy in the validation cohort. The sensitivity and specificity of the method were 73.7 and 78.7%, respectively, the positive predictive value was 29.2%, and the negative predictive value 96.2%. The 1- and 2-year cumulative BM rates were (respectively) 10.8% and 27.4% in the high-risk group and 2.4 and 4.3% in the low-risk group. The hazard ratio for BM of the high- versus low-risk group was 9.240 (95% CI: 3.319-25.722). CONCLUSION: The simple prediction model constructed from clinicopathological parameters is accurate in predicting BM development in HCC patients.
BACKGROUND: We aimed to develop a clinicopathological model that would predict the risk of bone metastasis (BM) in hepatocellular carcinoma (HCC). METHODS: We first evaluated a training cohort of 201 HCC patients who had undergone hepatectomy and found that the following factors independently predicted BM development: vascular invasion, tumor-node-metastasis stage, CXCR4, connective tissue growth factor, and interleukin-11. These variables were used to construct a clinicopathological prediction model that may be scored from 0 to 19. The predictive value of the model was demonstrated in a validation cohort of 179 post-hepatectomy HCC patients. RESULTS: During a median follow-up of 54.3 months for the training cohort and 52.5 months for the validation cohort, 23 patients (11.4%) in the former and 19 patients (10.6%) in the latter developed BM. A cutoff value of 9.4 best discriminated BM risk and was able to exclude future BM development with high accuracy in the validation cohort. The sensitivity and specificity of the method were 73.7 and 78.7%, respectively, the positive predictive value was 29.2%, and the negative predictive value 96.2%. The 1- and 2-year cumulative BM rates were (respectively) 10.8% and 27.4% in the high-risk group and 2.4 and 4.3% in the low-risk group. The hazard ratio for BM of the high- versus low-risk group was 9.240 (95% CI: 3.319-25.722). CONCLUSION: The simple prediction model constructed from clinicopathological parameters is accurate in predicting BM development in HCC patients.
Authors: Ismael Ghanem; Maria E Riveiro; Valerie Paradis; Sandrine Faivre; Paula M Vázquez de Parga; Eric Raymond Journal: Am J Transl Res Date: 2014-07-18 Impact factor: 4.060
Authors: Jiamin Zhou; Yi Xiang; Teizo Yoshimura; Keqiang Chen; Wanghua Gong; Jian Huang; Ye Zhou; Xiaohong Yao; Xiuwu Bian; Ji Ming Wang Journal: Biomed Res Int Date: 2014-07-10 Impact factor: 3.411