Risk factors for vascular invasion of primary liver cancer

Chang XiuJuan; Lu YinYing; Rong GuangHua; Liu Ze; Chen Yan; Xu GuiLin; Gao XuDong; Lou Min; Wang ChunPing; Yang YongPing; Ceng Zhen

doi:10.3969/j.issn.1001-5256.2018.05.022

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May 2018

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Article Navigation > Journal of Clinical Hepatology > 2018 > 34(5): 1038-1041

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Risk factors for vascular invasion of primary liver cancer

DOI: 10.3969/j.issn.1001-5256.2018.05.022

Liver Cancer Treatment and Research Center, 302 Hospital of PLA

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Received Date: 2017-11-16
Published Date: 2018-05-20

Abstract

Abstract

Objective To investigate the risk factors for vascular invasion of primary liver cancer ( PLC) . Methods A retrospective analysis was performed for the clinical data of 211 patients with liver cancer who were hospitalized in 302 Hospital of PLA from January 2013 to June 2014. The logistic regression model fitting was used for the data of 133 patients, and the data of the other 78 patients was used for the verification of this model. Univariate and multivariate logistic regression analyses were used to identify the influencing factors for vascular invasion of PLC; the logistic regression model was established and the receiver operating characteristic ( ROC) curve was plotted to determine the optimal cut-off value of this model. Results The univariate logistic regression analysis showed that tumor diameter ( odds ratio [OR]= 1. 594, 95% confidence interval [CI]: 1. 376-1. 846, P = 0) , neutrophil-lymphocyte ratio ( NLR) ( OR = 2. 783, 95% CI: 1. 847-4. 195, P = 0) , platelet-to-lymphocyte ratio ( PLR) ( OR = 1. 016, 95% CI: 1. 008-1. 024, P = 0) , fibrinogen ( Fb) ( OR = 2. 295, 95% CI: 1. 608-3. 274, P = 0) , and lymph node metastasis ( OR = 11. 664, 95% CI: 3. 744-36. 338, P = 0) were risk factors for vascular invasion of PLC; the multivariate logistic regression analysis showed that tumor diameter ( OR = 1. 506, 95% CI: 1. 250-1. 815, P =0) , PLR ( OR = 1. 499, 95% CI: 0. 173-0. 998, P = 0. 022) , NLR ( OR = 2. 491, 95% CI: 1. 411-4. 397, P = 0. 002) , and Fb ( OR = 1. 486, 95% CI: 1. 008-2. 193, P = 0. 046) were used for regression model fitting. The area under the ROC curve was 0. 927 ( 95% CI: 0. 881-0. 973) , and the ROC curve showed that the model had the highest sensitivity of 92. 9%, the highest specificity of86. 5%, and a prediction accuracy rate of 82. 79%. Conclusion The regression equation containing tumor diameter, PLR, NLR, and Fb established in this study has a high prediction accuracy of vascular invasion of PLC and provides a reference for early warning of vascular invasion of PLC.
- liver neoplasms,
- vascular invasion,
- risk factors,
- logistic models

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References

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沈阳化工大学材料科学与工程学院沈阳 110142

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Risk factors for vascular invasion of primary liver cancer

DOI: 10.3969/j.issn.1001-5256.2018.05.022

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Risk factors for vascular invasion of primary liver cancer

DOI: 10.3969/j.issn.1001-5256.2018.05.022

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