Advanced lung cancer inflammation index predicts survival outcomes of hepatocellular carcinoma patients receiving immunotherapy

Prognostic value of advanced lung cancer inflammation index in heart failure patients: A comprehensive analysis

AIMS

The prognosis of heart failure (HF) is closely linked to inflammation and nutritional status. The advanced lung cancer inflammation index (ALI) is a composite indicator consisting of several parameters used to assess inflammation and nutritional status. Our study aimed to investigate the prognostic value of ALI in HF patients.

METHODS

The data from Study 1, which included 1359 HF patients, were extracted from the National Health and Nutrition Examination Survey (NHANES) database spanning the years 1999 to 2018. Study 2 analysed data from patients with HF who underwent cardiac magnetic resonance imaging examinations from 2020 to 2023. Kaplan-Meier curve analysis, Cox proportional hazard model, time-dependent receiver operating characteristic (ROC) curve and restricted cubic spline (RCS) were used to evaluate the relationship between ALI and long-term prognosis of patients with HF in Study 1. Logistic regression analysis was used to evaluate the correlation between ALI and left ventricular reverse remodelling, and RCS was used to determine any dose-response relationship. Spearman correlation was used to evaluate the relationship between ALI and indicators of cardiac structural changes.

RESULTS

Study 1 found that the average age of the patients was 68 years [inter-quartile range (IQR) 58-76], the proportion of males was 54.3%, and there were 699 all-cause mortality and 293 cardiovascular mortality cases. After adjusted by multivariable Cox regression analysis, elevated ALI levels were significantly associated with increased risks of all-cause [hazard ratio (HR) = 0.58, 95% confidence interval (CI) = 0.42-0.79, P < 0.001] and cardiovascular mortality (HR = 0.61, 95% CI = 0.38-0.97, P = 0.036) in patients with HF. A linear negative correlation was observed between ALI and both all-cause (P = 0.0011 and P < 0.001, P for nonlinear = 0.3993) and cardiovascular mortality (P = 0.0011, P for nonlinear = 0.5198). Time-dependent ROC curves showed the predictive value of ALI for all-cause mortality [area under the curve (AUC) = 0.678 in 3 years, AUC = 0.674 in 5 years and AUC = 0.683 in 10 years] and cardiovascular mortality (AUC = 0.694 in 3 years, AUC = 0.685 in 5 years and AUC = 0.697 in 10 years). Study 2 included 79 patients; the average age of the patients was 44 years (IQR 35-55); and the proportion of males was 74.7%. Adjusted multivariable logistic regression analysis indicated that high ALI levels were associated with left ventricular reverse remodelling (LVRR) in patients with HF following discharge from the hospital [odds ratio (OR) = 3.16, 95% CI = 1.06-10.8, P = 0.049]. Spearman analysis revealed a correlation between ALI and extracellular volume (ECV) (r = -0.25, P = 0.023).

CONCLUSION

ALI is associated with all-cause and cardiovascular mortality risk and structural changes in the heart in patients with HF.

Predictive Value of Advanced Lung Cancer Inflammation Index and Development of a Nomogram for Prognosis in Patients with Cervical Cancer Treated with Radiotherapy

Purpose

As an assessment tool of nutritional status and inflammation, the advanced lung cancer inflammation index (ALI) is associated with survival in various cancers. We aimed to investigate the association between the ALI's prognostic value and survival time in patients with the stage IIB-III cervical cancer treated with radiotherapy.

Patients and Methods

We retrospectively screened patients diagnosed with cervical cancer and underwent radiotherapy in a single institution between September 2013 to September 2015. The ALI was calculated as body mass index * serum albumin/neutrophil-to-lymphocyte ratio. The cut-off value of ALI was determined by the receiver operating characteristic (ROC) curves. Overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan-Meier method and Cox proportional hazards models. A nomogram was developed using prognostic factors based on multivariate analyses.

Results

A total of 178 patients with cervical cancer were included. The cutoff value of ALI was set at 310.6 by ROC analyses. Kaplan Meier survival curves indicated that patients with low ALI had a significantly poorer OS (log-rank P<0.001) and PFS (log-rank P=0.0056) than those with high ALI. The association between ALI and OS was significant in the patients with obese/overweight and low/normal weight. The Cox regression analysis indicated that patients with low ALI were associated with a decreased OS (Hazard Ratio (HR) = 2.56, 95% Confidence Intervals (CI), 1.35-4.83; P= 0.004) and PFS (HR = 1.83; 95% CI, 1.06-3.17; P = 0.031). The nomogram on OS was created based on ALI with C-index of 0.81. Patients with high nomogram points had worse OS than those with low nomogram points (log rank P<0.0001).

Conclusion

Pretreatment ALI is an independent negative prognostic factor in patients with cervical cancer treated with radiotherapy. The ALI based nomogram can help to identify patients who may have unfavorable outcomes.

Advanced lung cancer inflammation index: a key predictor of hepatic steatosis and fibrosis severity

BACKGROUND

The Advanced Lung Cancer Inflammation Index (ALI) reflects levels of systemic inflammation and nutrient metabolism in patients. However, The connection between ALI and hepatic steatosis and fibrosis remains unclear. This study aims to explore the potential association between ALI, the Controlled Attenuation Parameter (CAP), and Liver Stiffness Measurement (LSM), offering new perspectives for the prevention of hepatic steatosis and fibrosis.

METHODS

Using data from the National Health and Nutrition Examination Survey database spanning from 2017 to 2020, a cross-sectional study of 6591 participants aged 20 years and older was performed to assess the relationship between ALI and hepatic steatosis and hepatic fibrosis. Smooth curve fitting and generalized additive models were used to further evaluate whether there was a nonlinear association between ALI, CAP, and LSM, and threshold effect analysis was used to find the inflection point. A two-part linear regression model was applied to estimate threshold effects. Subgroup analysis and interaction were used to evaluate the potential association between ALI, CAP, and LSM. Furthermore, to verify the efficacy of ALI, we used ROC curves to compare ALI with fibrosis and nutritional markers (FIB-4 index, GNRI) that have been reported to be associated with liver disease.

RESULTS

The ALI levels in the MASLD and fibrosis 4 groups were considerably elevated than the control group, with statistical significance (PMASLD<0.001, PAHF =0.013). Multiple linear regression analyses indicated significant positive associations between ALI and its quartiles with both CAP[b(95%CI) ALI=0.510(0.465,0.555), P<0.001] and LSM levels [b(95%CI) ALI=0.011(0.009,0.013), P<0.001). There was a positive smooth curve fitting relationship between ALI and the levels of CAP and LSM, with threshold effect inflection points at 88.287 and 98.420 (PLog likelihood ratio<0.001), respectively. ALI interacts with CAP in relation to gender [OR(95%CI)female=0.095(0.039-0.150), OR(95%CI)male=0.174(0.118-0.230), Pfor interaction=0.044] and smoking [OR(95% CI)<100cigarettes in life=0.086(0.035-0.137), OR(95% CI)>100cigarettes in life=0.177(0.115-0.240), Pfor interaction=0.023], and with LSM in patients with HL [OR(95% CI)HL=0.014(0.008-0.019), Pfor interaction<0.001].

CONCLUSION

The findings suggest a positive correlation between elevated ALI levels and the levels of CAP and LSM. Maintaining ALI within an appropriate range may help mitigate the prevalence of hepatic steatosis and hepatic fibrosis.

Predictive effects of advanced lung cancer inflammation index and serum vitamin D on mortality in patients with asthma

BACKGROUND

Changes in systemic inflammation, nutritional status and serum vitamin D level are important characteristics of asthma. However, role and importance of nutritional inflammatory indicators or serum vitamin D concentrations in predicting the prognosis of asthma remain unclear. The advanced lung cancer inflammation index (ALI), based on body mass index (BMI), serum albumin and neutrophil-lymphocyte ratio (NLR), is a comprehensive index to assess systemic inflammation and nutrition. This study aimed to evaluate their independent and combined predictive value of mortality in asthma patients.

METHODS

This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Cox regression analysis was used to assess the independent or joint effect of ALI and serum vitamin D on mortality risks of asthma. Receiver operator characteristic curve analysis was used to compare the prognostic ability of ALI with its component factors, including NLR, albumin, neutrophil, lymphocyte and BMI.

RESULTS

A total of 2870 eligible asthma patients were included. After adjustment, higher ALI correlated significantly with reduced all-cause and respiratory disease mortality (adjusted hazard ratio [aHR] = 0.64 and 0.34; P < 0.05). Meanwhile, vitamin D deficiency correlated significantly with increased all-cause and respiratory disease mortality (aHR = 2.06 and 2.73; P < 0.05). The area under the curve of ALI in predicting 1-year, 5-year or 10-year all-cause mortality surpassed that of its five component indices. Joint analyses showed that individuals with higher levels of ALI and vitamin D had the lowest risks of all-cause and respiratory disease mortality (aHR = 0.31 and 0.17; P < 0.05).

CONCLUSIONS

ALI and serum vitamin D are robust independent and combined predictors of mortality in asthma patients. ALI offers superior predictive capability over its components, and sufficient vitamin D levels are beneficial for survival outcomes. The synergistic effect of high ALI and adequate vitamin D highlights the benefit of integrating both metrics into clinical practice for enhanced prognostic accuracy.

Association between advanced lung cancer inflammation index and unstable asthma: a population-based study from the NHANES 2007-2018

Background

Asthma exacerbation is associated with obesity and systemic inflammatory diseases, and advanced lung cancer inflammation index (ALI) is a novel biomarker of nutritional inflammation. The purpose of this study was to investigate the potential relationship between ALI and unstable asthma.

Methods

This cross-sectional study utilized data from the 2007-2018 National Health and Nutrition Examination Survey (NHANES). Asthma was assessed through self-reported questionnaires. Multifactorial logistic regression, subgroup analyses, interaction assessments, smoothed curve fitting, and threshold effect analysis models were conducted to investigate the association between ALI and unstable asthma.

Results

The study included 1,822 subjects with current asthma, and we found a linear positive association between ALI and unstable asthma, with higher levels of ALI significantly associated with an increased risk of asthma exacerbations in fully corrected models. However, the associations were not entirely consistent across subgroups. In subgroup analyses by body mass index (BMI) and race, unstable asthma and ALI were independently significant in the BMI (25-29.9) range and the Non-Hispanic White group. Interaction analysis suggested that BMI moderated the relationship between ALI and unstable asthma. Furthermore, smoothed curve fitting showed an inverted U-shaped relationship between log ALI and unstable asthma in subjects with a BMI <25 and male individuals, with inflection points observed at 1.53 and 2.13, respectively.

Conclusion

We found a linear positive association between ALI and unstable asthma, which remained constant in the fully adjusted model. These findings suggest that higher levels of ALI were significantly associated with an increased risk of asthma exacerbation, particularly in asthmatic populations with BMI in the 25-29.9 range. However, more prospective studies are required to confirm our findings.

Combined influence of nutritional and inflammatory status and breast cancer: findings from the NHANES

BACKGROUND

Previous studies have hinted at the benefits of following an anti-inflammatory diet for potentially reducing breast cancer prevalence. However, the combined influence of diet and inflammation on breast cancer remains unclear.

METHODS

The advanced lung cancer inflammation index (ALI) was used to assess inflammation and nutritional status. Statistical methods, such as multivariable logistic regression, eXtreme Gradient Boosting (XGBoost) model, and subgroup analysis, were employed to analyze the impact of ALI on prevalence of BC. Additionally, a two-piece-wise logistic regression model with smoothing was used to determine the ALI threshold for BC prevalence. The study aimed to understand the mechanistic association between ALI levels and BC development.

RESULTS

The mean (SD) age of the study population was 50.0 (17.7) years, with 40.0% of individuals classified as obese. Comparing ALI tertiles to the lowest tertile, the odds ratios (95% CI) for breast cancer (BC) were 0.78 (0.62, 0.98) and 0.68 (0.52, 0.87) for T2-T3. The XGBoost machine learning model was employed to assess the importance of selected factors, revealing ALI as one of the top five variables influencing BC. Subgroup analysis identified a correlation between ALI, alcohol consumption, and menopausal status. Additionally, ALI levels were associated with decreased estradiol (E2) levels, increased total testosterone (TT)/E2 ratio, and TT/sex hormone-binding globulin (SHBG) ratio.

CONCLUSION

This study indicates a potential protective effect of ALI levels against breast cancer, possibly related to sex hormone disruption. The findings support the use of optimal therapeutic strategies for preventing breast cancer.

Predictive Efficacy of the Advanced Lung Cancer Inflammation Index in Hepatocellular Carcinoma After Hepatectomy

Background

Hepatocellular carcinoma (HCC) presents a significant global health challenge due to its poor prognosis and high recurrence rates post-surgery. This study examines the predictive efficacy of the Advanced Lung Cancer Inflammation Index (ALI) in assessing the post-hepatectomy prognosis of patients with HCC.

Methods

A cohort comprising 1654 HCC patients who underwent hepatectomy at Guangxi Medical University Cancer Hospital from 2013 to 2019 was enrolled. Patients were stratified into two groups according to the median ALI level, and then subjected to propensity score matching (PSM) in a 1:1 ratio. Kaplan-Meier survival curves, the traditional Cox proportional hazards (CPH) model, and machine learning (ML) models were employed to analyze and evaluate ALI's prognostic significance. Furthermore, ALI's prognostic value in digestive system tumors was validated via analysis of the National Health and Nutrition Examination Survey (NHANES) database.

Results

After applying PSM, a final cohort of 1284 patients, categorized into high and low ALI groups, revealed a significantly reduced survival time in the low ALI cohort. Univariate and multivariate Cox analyses identified ALI, BCLC stage, CK19, Hepatitis B virus (HBV) DNA, lymph node metastasis, and microvascular invasion (MVI) as independent predictors of prognosis. Both traditional CPH and ML models incorporating ALI demonstrated excellent predictive accuracy, validated through calibration curves, time-dependent ROC curves, and decision curve analysis. Furthermore, the prognostic value of ALI in digestive tumors was confirmed in the NHANES database.

Conclusion

The ALI exhibits potential as a prognostic predictor in patients with HCC following hepatectomy, providing valuable insights into postoperative survival.

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.

Prognostic value of the advanced lung cancer inflammation index in patients with gastric cancer after radical gastrectomy: a propensity-score matching cohort study and meta-analysis

BACKGROUND

Insufficient evidence existed about the prognostic role of the advanced lung cancer inflammation index (ALI) for gastric cancer patients who underwent curative resection. The aim of this study was to identify the predictive ability of ALI for survival after curative gastrectomy.

METHODS

We retrospectively analyzed 328 gastric cancer patients who received curative gastrectomy from the database of Chongqing University Cancer Hospital, and investigated the prognostic role of the preoperative ALI compared with clinicopathological variables and other serum biomarkers, such as preoperative neutrophil-to-lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and Lymphocyte-monocyte ratio (LMR). To minimize intergroup differences, propensity score matching (PSM) analysis was employed. Additionally, we performed a meta-analysis of four cohort studies published up to October 2023 following the PRISMA guidelines.

RESULTS

In the overall cohort, patients in the low ALI group had a significantly worse overall survival compared to those in the high ALI group (P < 0.0001). Subgroup analysis identified that ALI maintained its prognostic significance across different subgroups. In addition, ROC analysis showed that ALI had a higher AUC value for 3-year overall survival compared to NLR, PLR, and LMR (0.576 vs. 0.573 vs. 0.557 vs. 0.557). Multivariate analysis indicated that ALI, other than other serum biomarkers, was an independent risk factor for decreased overall survival in GC patients following curative surgery (HR = 1.449; 95%CI: 1.028-2.045; P = 0.034). Consistently, PSM analysis supported all of these findings. The meta-analysis including 4 studies evaluating 2542 patients, confirmed the association between the low ALI and poor survival outcomes.

CONCLUSION

The preoperative ALI was an independent prognostic factor for survival in gastric cancer patients who underwent curative gastrectomy.

Association of the Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) score with immune checkpoint inhibitor efficacy in patients with gastrointestinal and lung cancer

OBJECTIVE

This study aimed to conduct a comprehensive analysis, evaluating the prognostic significance of the baseline Advanced Lung Cancer Inflammation Index (ALI) and Gustave Roussy Immune (GRIm) Score in patients undergoing immune checkpoint inhibitor (ICI) therapy.

METHODS

A comprehensive search was performed across various databases, including PubMed, the Cochrane Library, EMBASE, and Google Scholar, until October 21, 2023, to compile relevant articles for analysis. The investigation encompassed diverse clinical outcomes, including overall survival (OS) and progression-free survival (PFS).

RESULTS

This analysis included a total of 15 articles, comprising 19 studies involving 3335 patients. Among the 19 studies, nine studies focused on NSCLC, and six studies were conducted on HCC. Pooled results revealed that patients with elevated ALI levels experienced prolonged OS (HR: 0.51, 95% CI: 0.37-0.70, p < 0.001) and extended PFS (HR: 0.61, 95% CI: 0.52-0.72, p < 0.001). Furthermore, a GRIm score > 1 was associated with reduced OS (HR: 2.07, 95% CI: 1.47-2.92, p < 0.001) and diminished PFS (HR: 1.78, 95% CI: 1.35-2.34, p < 0.001) in cancer patients receiving ICIs. Subgroup analysis indicated that ALI cutoff values of 18 exhibited enhanced predictive potential. Additionally, for HCC patients, those with HCC-GRIm score > 2 showed a substantially decreased risk of mortality compared to individuals with HCC-GRIm score ≤ 2 (HR: 2.63, 95% CI: 1.89-3.65, p < 0.001).

CONCLUSION

The ALI and GRIm score served as dependable prognostic indicators for patients undergoing ICI therapy in the context of cancer treatment.

Prognostic Nutritional Index Predicts Efficacy and Immune-Related Adverse Events of First-Line Chemoimmunotherapy in Patients with Extensive-Stage Small-Cell Lung Cancer

Background

Currently, there is a lack of well-established markers to predict the efficacy of chemoimmunotherapy in small-cell lung cancer (SCLC). Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), advanced lung cancer inflammation index (ALI) and prognostic nutritional index (PNI) are associated with prognosis in several tumors, whereas their predictive role in SCLC remains unclear.

Methods

A retrospective study was conducted at Sun Yat-sen University Cancer Center, involving extensive-stage SCLC (ES-SCLC) patients who received first-line chemoimmunotherapy between January 2020 and December 2021. Peripheral blood biomarkers were extracted from medical records and their correlation with prognosis and immune-related adverse events (IRAEs) was analyzed.

Results

A total of 114 patients were included. Patients with a low PLR, high ALI and high PNI had prolonged progression-free survival (PFS) compared to those with a high PLR, low ALI and low PNI. Patients with a low NLR, low PLR, high ALI and high PNI had prolonged overall survival (OS) compared to those with a high NLR, high PLR, low ALI and low PNI. Cox regression model showed that PNI was an independent risk factor for both PFS and OS. ROC curve showed that PNI outperforms NLR, PLR and ALI in predicting both PFS and OS. The PNI-based nomogram demonstrated strong predictive capability for both PFS and OS. In addition, there was a significant correlation between PNI and IRAEs.

Conclusion

A high baseline PNI might be associated with improved prognosis and the occurrence of IRAEs in ES-SCLC patients treated with first-line chemoimmunotherapy.

Advanced lung cancer inflammation index predicts overall survival of hepatocellular carcinoma after hepatectomy

Aim

Limited data are available regarding ALI's clinical relevance and prognostic value in patients with hepatocellular carcinoma (HCC) after hepatectomy.

Materials and methods

HCC patients who received hepatectomy at the Meizhou People's Hospital from May 2011 to February 2022 were enrolled in the study cohort. The ALI was calculated as follows: ALI = BMI (kg/m2) × ALB (g/dL)/(absolute neutrophil count/absolute lymphocyte count). The primary outcome was overall survival (OS). The secondary outcome was cancer-specific survival (CSS). Univariate and multivariate Cox regression analyses were performed, followed by nomogram construction and decision curve analysis (DCA).

Results

425 HCC patients were enrolled for analyses. Lower preoperative ALI was significantly correlated with incomplete tumor capsule and advanced tumor stage. Lower preoperative ALI was an adverse independent prognostic factor for OS (HR: 1.512, 95% CI: 1.122-2.039, P 0.007) and CSS (HR: 1.754, 95% CI: 1.262-2.438, P <0.001) in HCC patients. The nomogram plot was built based on three (including age, TNM stage, and ALI) and two (including TNM stage and ALI) independent prognostic factors for OS and CSS, respectively. Further analyses indicated that the nomogram had better predictive value and some net benefit than the traditional TNM stage alone, especially in long-term OS.

Conclusions

Our study further indicated that ALI could be a prognostic marker for OS and CSS in HCC patients after hepatectomy, especially in long-term OS.

Biomarkers predicting the efficacy of immune checkpoint inhibitors in hepatocellular carcinoma

In recent years, immune checkpoint inhibitors (ICIs) have emerged as a transformative approach in treating advanced hepatocellular carcinoma (HCC). Despite their success, challenges persist, including concerns about their effectiveness, treatment costs, frequent occurrence of treatment-related adverse events, and tumor hyperprogression. Therefore, it is imperative to identify indicators capable of predicting the efficacy of ICIs treatment, enabling optimal patient selection to maximize clinical benefits while minimizing unnecessary toxic side effects and economic losses. This review paper categorizes prognostic biomarkers of ICIs treatment into the following categories: biochemical and cytological indicators, tumor-related markers, imaging and personal features, etiology, gut microbiome, and immune-related adverse events (irAEs). By organizing these indicators systematically, we aim to guide biomarker exploration and inform clinical treatment decisions.