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.