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Abstract
Background
Sarcopenia is a risk factor for poor cancer prognosis. Early identification and timely intervention of sarcopenia can improve patient prognosis.
Methods
A total of 91 patients with liver cirrhosis complicated with primary hepatocellular carcinoma were retrospectively analyzed. Based on the results of multivariable logistic regression analysis, a nomogram was developed. Moreover, 50 patients were enrolled for external validation. The predictive efficacy of the nomogram was evaluated using the receiver operating characteristic curve (ROC).
Results
According to the logistic regression analysis results, age, body mass index (BMI), creatinine-to-cystatin C ratio (Cre/CysC), and systemic immune inflammation index (SII) were independent risk factors of sarcopenia in patients with cirrhosis complicated with primary hepatocellular carcinoma (HCC) (all p < 0.05). The ABCS nomogram model was established, and the area under the ROC curve (AUC) was 0.896 (84.7% sensitivity, 81.2% specificity). The calibration curve of the nomogram was close to the ideal diagonal line. The predictive efficacy of the nomogram was verified through the external validation.
Conclusion
The ABCS model based on SII and Cre/CysC can be used to identify high-risk sarcopenia in patients with cirrhosis complicated with HCC in the early stage.
Disclosure Statement
No potential conflict of interest was reported by the authors.
Author Contributions
Xinhua Luo and Hong Peng took charge of designing the study and revising the paper. Siyi Lei drafted the manuscript, analyzed and interpreted the data. Qian Zhang and Qing Zhang made the figures and tables. Li long, Shanbi Sun, Huamin Yuan, Yan Luo, Nanhui Chen collected the clinical data. All authors agree to the final approval of the version to be published.