Advanced lung cancer inflammation index predicts in-hospital mortality and refines risk stratification in patients with cirrhosis
- 1Department of Gastroenterology, The First Affiliated Hospital of Shihezi University, Shihezi, Xinjiang 832008 China
Abstract
Background: Conventional prognostic scores for liver cirrhosis frequently overlook the nutritional and systemic inflammatory status of patients. The Advanced Lung Cancer Inflammation Index (ALI) is a novel biomarker that integrates these two dimensions. This study aimed to investigate the clinical value of the ALI in assessing disease severity and predicting short-term in-hospital mortality in patients with cirrhosis.
Methods: This retrospective study analyzed 904 patients hospitalized with cirrhosis at the First Affiliated Hospital of Shihezi University between 2015 and 2023. The optimal ALI cutoff value was determined using receiver operating characteristic (ROC) curve analysis. Spearman’s correlation and multivariate logistic regression analyses were used to evaluate the independent association of the ALI with disease severity and in-hospital mortality. Restricted cubic splines (RCS) were used to explore the non-linear relationships. The incremental predictive value of the ALI was assessed using the area under the ROC curve (AUC), continuous net reclassification improvement (cNRI), and integrated discrimination improvement (IDI).
Results: The overall in-hospital mortality rate was 11.6% (105/904). The ALI demonstrated a significant inverse correlation with the Child-Pugh (r = -0.805) and Model for End-Stage Liver Disease (MELD) (r = -0.621) classifications (P < 0.001). RCS analysis revealed an “L-shaped” non-linear relationship between the ALI and mortality risk (inflection point at 17.0). Multivariate logistic regression analysis confirmed that a low ALI (< 17.0) was a strong independent risk factor for in-hospital mortality (odds ratio: 7.35, 95% confidence interval: 3.12–17.30, P < 0.001), an effect that remained highly consistent across multiple sensitivity and subgroup analyses. Incorporating the ALI into conventional Child-Pugh and MELD scores yielded highly significant improvements in AUC, cNRI, and IDI values for the combined models (all P < 0.001).
Conclusion: The ALI objectively reflects the degree of decompensation in cirrhosis, with a low ALI serving as an indicator of high short-term mortality risk. As a highly cost-effective, non-invasive biomarker, the ALI significantly optimizes the predictive performance of conventional hepatic scores, facilitating rapid, early risk stratification and precision intervention for hospitalized patients with cirrhosis.
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BibTeX
@article{zhao2026advanced,
title = {{Advanced lung cancer inflammation index predicts in-hospital mortality and refines risk stratification in patients with cirrhosis}},
author = {Yihang Zhao and Xin Peng and Lixiu Song},
journal = {BMC Gastroenterology},
year = {2026},
month = aug,
doi = {10.1186/s12876-026-05218-1},
url = {https://doi.org/10.1186/s12876-026-05218-1},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Advanced lung cancer inflammation index predicts in-hospital mortality and refines risk stratification in patients with cirrhosis
AU - Yihang Zhao
AU - Xin Peng
AU - Lixiu Song
PY - 2026
DA - 2026/08/10
JO - BMC Gastroenterology
DO - 10.1186/s12876-026-05218-1
UR - https://doi.org/10.1186/s12876-026-05218-1
AB - Background: Conventional prognostic scores for liver cirrhosis frequently overlook the nutritional and systemic inflammatory status of patients. The Advanced Lung Cancer Inflammation Index (ALI) is a novel biomarker that integrates these two dimensions. This study aimed to investigate the clinical value of the ALI in assessing disease severity and predicting short-term in-hospital mortality in patients with cirrhosis. Methods: This retrospective study analyzed 904 patients hospitalized with cirrhosis at the First Affiliated Hospital of Shihezi University between 2015 and 2023. The optimal ALI cutoff value was determined using receiver operating characteristic (ROC) curve analysis. Spearman’s correlation and multivariate logistic regression analyses were used to evaluate the independent association of the ALI with disease severity and in-hospital mortality. Restricted cubic splines (RCS) were used to explore the non-linear relationships. The incremental predictive value of the ALI was assessed using the area under the ROC curve (AUC), continuous net reclassification improvement (cNRI), and integrated discrimination improvement (IDI). Results: The overall in-hospital mortality rate was 11.6% (105/904). The ALI demonstrated a significant inverse correlation with the Child-Pugh (r = -0.805) and Model for End-Stage Liver Disease (MELD) (r = -0.621) classifications (P < 0.001). RCS analysis revealed an “L-shaped” non-linear relationship between the ALI and mortality risk (inflection point at 17.0). Multivariate logistic regression analysis confirmed that a low ALI (< 17.0) was a strong independent risk factor for in-hospital mortality (odds ratio: 7.35, 95% confidence interval: 3.12–17.30, P < 0.001), an effect that remained highly consistent across multiple sensitivity and subgroup analyses. Incorporating the ALI into conventional Child-Pugh and MELD scores yielded highly significant improvements in AUC, cNRI, and IDI values for the combined models (all P < 0.001). Conclusion: The ALI objectively reflects the degree of decompensation in cirrhosis, with a low ALI serving as an indicator of high short-term mortality risk. As a highly cost-effective, non-invasive biomarker, the ALI significantly optimizes the predictive performance of conventional hepatic scores, facilitating rapid, early risk stratification and precision intervention for hospitalized patients with cirrhosis.
SN - 1471-230X
ER -