Work

The value of the prognostic nutritional index, sarcopenia index, and systemic immune-inflammatory index as auxiliary tools in the diagnosis of malnutrition in liver cancer patients according to the GLIM criteria

Year: 2026

Type: article

Abstract: To investigate the correlation of the Prognostic Nutritional Index (PNI), Sarcopenia Index (SI), and Systemic Immune-inflammatory Index (SII) with malnutrition defined by the Global Leadership Initiative on Malnutrition (GLIM) criteria, and to evaluate their value as auxiliary biomarkers for the GLIM criteria. This retrospective study included 210 patients diagnosed with hepatocellular carcinoma (HCC) who underwent surgery at the Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital of Ningbo University, between January 2021 and December 2024. Malnutrition was diagnosed in accordance with the GLIM criteria. Logistic regression analysis was used to examine the association between PNI, SI, SII and the presence of malnutrition. The diagnostic performance of PNI, SI, and SII was evaluated via the area under the receiver operating characteristic curve. Among the 210 patients, 68 cases (32.38%) were diagnosed with malnutrition. Compared with patients without malnutrition, those with malnutrition had significantly lower PNI and SI values, and significantly higher SII levels ( P < 0.05). Multivariate regression analysis revealed that low PNI, low SI, and high SII were independent risk factors for malnutrition under GLIM criteria ( P < 0.05). PNI is an effective tool for predicting malnutrition (sensitivity 0.683, specificity 0.765, area under the ROC curve 0.772, 95% CI: 0.708–0.836, P < 0.001), demonstrating superior diagnostic performance compared to SI (sensitivity 0.577, specificity 0.750, area under the ROC curve 0.688, 95% CI: 0.613–0.762, P < 0.05) and SII (sensitivity 0.882, specificity 0.606, area under the ROC curve 0.647, 95% CI: 0.569–0.725, P < 0.05). The combined PNI-SI model exhibited an area under the ROC curve of 0.779 (sensitivity 0.912, specificity 0.577, 95% CI: 0.716–0.843, P < 0.001). According to the DeLong test, the difference in AUC between the combined model and PNI alone was not statistically significant (95% CI: -0.030–0.016, Z = -0.629, P = 0.529). PNI, SI, and SII, particularly PNI, were effective auxiliary predictors for evaluating GLIM-standard malnutrition in patients with liver cancer. The combination of PNI and SI offered a high-sensitivity advantage in screening settings, serving as a simple and effective tool to complement clinical nutritional assessment.

Source: BMC Cancer

DOI: 10.1186/s12885-026-16877-4