Prognostic value of the modified advanced lung cancer inflammation index in overweight or obese patients with lung cancer: Results from a multicenter study

The role of the advanced lung cancer inflammation index (ALI) in the risk of liver fibrosis and mortality among US adult MAFLD patients: a cross-sectional study of NHANES 1999-2018

BACKGROUND

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a prevalent chronic liver disease globally, with inflammation and nutrition playing key roles in its progression. The Advanced Lung Cancer Inflammation Index (ALI) is a novel biomarker reflecting nutritional and inflammatory status. This study aims to explore the association between ALI and the risk of liver fibrosis and prognosis in MAFLD patients.

METHODS

This cross-sectional study analyzed NHANES data from the 1999-2018 on adult participants in the US. Weighted logistic regression assessed the association between ALI and liver fibrosis risk. Mortality outcomes, including all-cause, cardiovascular disease (CVD), and cancer mortality, analyzed using weighted Kaplan-Meier and Cox proportional hazards models. Restricted cubic splines (RCS) and threshold effect analyses were uesd to explore non-linear relationships. Receiver operating characteristic (ROC) curve evaluated the prognostic value of ALI, and stratified analyses examined subgroup differences.

RESULTS

A total of 6,858 MAFLD patients (mean age 51.38 ± 17.22 years, 54% male) were included. A non-linear relationship was found between ALI and liver fibrosis risk, with a threshold at 5.68, beyond which the risk increased significantly (OR = 2.35, 95% CI: 1.89-2.95). Stronger associations were observed in subgroups with central obesity and prediabetes (P for interaction < 0.05). ALI was inversely associated with all-cause mortality (HR = 0.64, 95% CI: 0.56-0.72) and CVD mortality (HR = 0.57, 95% CI: 0.46-0.65), but not cancer mortality. RCS analysis showed an L-shaped non-linear relationship with all-cause mortality (threshold at 5.36) and a linear relationship with CVD mortality. Low HDL cholesterol and excessive alcohol consumption influenced the association between ALI and all-cause mortality (P for interaction < 0.05). ALI demonstrated the highest predictive accuracy for CVD mortality.

CONCLUSION

ALI is associated with an increased risk of liver fibrosis and reduced all-cause and CVD mortality, highlighting its potential value in assessing MAFLD prognosis, particularly CVD-related mortality.

Advanced Lung Cancer Inflammation Index: A Novel Comprehensive Biomarker of Host Status for Patients with Metastatic Colorectal Cancer

Numerous biomarkers that reflect host status have been identified for patients with metastatic colorectal cancer (mCRC). However, there has been a paucity of biomarker studies that comprehensively indicate body composition, nutritional assessment, and systemic inflammation status. The advanced lung cancer inflammation index (ALI), initially introduced as a screening tool for patients with non-small-cell lung cancer in 2013, emerges as a holistic marker encompassing all body composition, nutritional status, and systemic inflammation status. The index is calculated by the simple formula: body mass index × albumin value / neutrophil-to-lymphocyte ratio. Given its accessibility in routine clinical practice, the ALI has exhibited promising clinical utility in prognosticating outcomes for patients with multiple types of cancer. In this review, we focus on the significance of host status and the clinical applicability of the ALI in the treatment and management of patients with malignancies, including mCRC. We also suggest its potential in guiding the formulation of treatment strategies against mCRC and outline future perspectives.

A novel nutritional inflammation index for predicting mortality in acute ischemic stroke patients: insights into advanced lung cancer inflammation index from the Medical Information Mart for Intensive Care-IV database

Objective

This investigation aimed to delineate the association between the advanced lung cancer inflammation index (ALI) and all-cause mortality (ACM) in individuals experiencing acute ischemic stroke (AIS).

Methods

Drawing on information from the Medical Information Mart for Intensive Care (MIMIC)-IV database, release 2.2, covering the years 2012 to 2019, this research assessed the advanced lung cancer inflammation index (ALI) by factoring in body mass index (BMI), serum albumin levels (ALB), and the neutrophil-to-lymphocyte ratio (NLR). Patients with AIS were identified using codes from the International Classification of Diseases (ICD). To address potential confounding factors, a 1:1 propensity score matching (PSM) method was utilized. The investigation identified the pivotal ALI level impacting patient survival using maximally selected rank statistics. It then examined the effects on short- and long-term ACM through multivariate Cox proportional hazards regression models and Kaplan-Meier (K-M) survival analysis. Additionally, restricted cubic spline (RCS) methods were applied to delve into the linear or nonlinear nature of the relationship between ALI and ACM, with further insights gained from interaction and subgroup analyses.

Results

The cohort comprised 838 AIS patients. Post-PSM, analysis involved 199 matched patient pairs. Adjusted Cox proportional hazard models indicated a significant association of low ALI (<10.38) with increased in-hospital ACM, both before (HR: 1.98; 95% CI: 1.36-2.88; p < 0.001) and after PSM (HR: 2.16; 95% CI: 1.32-3.52; p = 0.002). Associations of low ALI with elevated risk were consistent across ICU, 30 days, 90 days, and 1 year ACM pre- and post-PSM. Subsequent RCS analysis post-PSM underscored a negative nonlinear relationship between ALI and ACM over both short and long terms, without significant interaction effects across different subgroups for ACM.

Conclusion

In this retrospective cohort study, by utilizing a nationally representative sample of United States patients with AIS, our analysis elucidates a negative correlation between the ALI and ACM in individuals with AIS, underscoring the utility of ALI as a novel, efficacious, and accessible inflammatory biomarker for prognosticating ACM. These results carry profound implications for public health policy and practice. A deeper comprehension of these associations can empower public health practitioners and researchers to devise more targeted interventions and policies, aimed specifically at catering to the distinct needs of the AIS patient population, thereby enhancing their health outcomes. The further research in other races/ethnicity is urgent, particularly before applying these findings in clinical practice.

Prognostic significance of sarcopenia diagnosed based on the anthropometric equation for progression-free survival and overall survival in patients with colorectal cancer

Background

The purpose of this study was to investigate the prognostic significance of sarcopenia diagnosed based on anthropometric equations for progression-free survival (PFS) and overall survival (OS) in patients with colorectal cancer (CRC).

Methods

A total of 1,441 CRC patients who underwent surgical treatment between January 2012 and December 2016 were enrolled in this study. Sarcopenia was diagnosed according to validated anthropometric equations. The Kaplan-Meier method with the log-rank test was used to estimate the survival curve. Cox proportional hazards regression models with forward selection were used to evaluate risk factors affecting the prognosis of CRC patients. R package "survival" was used to build the prognostic nomograms to predict 1-5 years of PFS and OS in CRC patients. The concordance index (C-index) and calibration curve were used to evaluate the prognostic accuracy of the prognostic nomogram.

Results

Two hundred and seventy-one patients (18.8%) were diagnosed with sarcopenia. Sarcopenia was significantly associated with advanced age, large tumor size, and high mortality. Compared with the non-sarcopenia patients, the PFS of sarcopenia patients was worse (5-year PFS, 48.34 vs. 58.80%, p = 0.003). Multivariate survival analysis showed that patients with sarcopenia had a higher risk (23.9%) of adverse PFS (HR, 1.239; 95%CI: 1.019-1.505, p = 0.031) than patients without sarcopenia. The OS of patients with sarcopenia was significantly worse than that of patients without sarcopenia (5-year OS: 50.92 vs. 61.62%, p = 0.001). In CRC patients, sarcopenia was independently associated with poor OS (HR: 1.273, 95%CI: 1.042-1.556, p < 0.001). Moreover, sarcopenia effectively differentiated the OS of CRC patients in the normal carcinoembryonic antigen (CEA) subgroup but not in the high CEA subgroup. Notably, sarcopenia can provide effective prognostic stratification in CRC patients at different pathological stages. Nomograms that integrated prognostic features were built to predict the risk of adverse outcomes in CRC patients. The C-index and calibration curves showed that these nomograms had good prediction accuracy. Internal validation confirmed that our nomogram has wide application potential.

Conclusion

Sarcopenia diagnosed based on anthropometric equations is an independent risk factor for PFS and OS in CRC patients.