Prognostic Value of the Advanced Lung Cancer Inflammation Index in Patients with Lung Cancer: A Meta-Analysis

Prognostic Value of Tertiary Lymphoid Structures in Stage I Nonsmall Cell Lung Cancer: Does Location Matter?

Background

Emerging evidence indicates the importance of tertiary lymphoid structures (TLSs) in predicting the outcomes of nonsmall cell lung cancer (NSCLC) patients; however, their prognostic value and correlations with peripheral inflammatory prognostic indices in stage I patients have been less well studied.

Methods

Stage I NSCLC patients were recruited retrospectively; the presence and location of TLSs (peritumoral [pTLSs] and intratumoral [iTLSs]) were determined via hematoxylin and eosin (H&E)-stained slides. Peripheral inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), prognostic nutritional index (PNI), and advanced lung cancer inflammation index (ALI), were obtained and compared among these subgroups. Disease-free survival (DFS) and overall survival (OS) were tested via Kaplan-Meier analysis, and risk factors for survival were determined via a Cox proportional hazards model.

Results

A total of 24.73% and 92.73% of patients were positive for pTLSs and iTLSs, respectively. The absolute number of iTLSs was significantly greater than that of pTLSs (P < .001). Low preoperative LMR and ALI were detected only in patients with pTLSs but not in those without. Only pTLS was found to be a risk factor for both DFS and OS, and it was independently associated with OS (HR = 3.93, 95% confidence interval [CI] = 1.16-13.37; P = .028). Accordingly, patients with pTLSs had relatively poor DFS (log rank = 5.46, P = .019) and OS (log rank = 10.48, P = .001) rates.

Conclusions

Among the heterogeneous results concerning the prognostic value of pTLSs and iTLSs in stage I NSCLC, our results for the first time indicated that the presence of pTLSs may predict poor outcomes in these patients and no correlation of iTLSs with the outcomes was validated; however, additional studies with large sample size are needed in future.

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.

Pre-Operative Measures of Systemic Inflammation Predict Survival After Surgery for Primary Lung Cancer

BACKGROUND

Measures of systemic inflammation (MSIs) have been developed and shown to help predict prognosis in patients with lung cancer. However, studies investigating the impact of MSIs on outcomes solely in cohorts of patients undergoing curative-intent resection of NSCLC are lacking. In the era of individualized therapies, targeting inflammatory pathways could represent a novel addition to the armamentarium of lung cancer treatment.

METHODS

A multicentre retrospective review of patients who underwent primary lung cancer resection between 2012 and 2018 was undertaken. MSIs assessed were neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune inflammation index (SII), advanced lung cancer inflammation index (ALI), prognostic nutritional index (PNI) and haemoglobin albumin lymphocyte platelet (HALP) score. Cox regression analysis was performed to assess the impact of MSIs on overall survival.

RESULTS

A total of 5029 patients were included in the study. Overall 90-day mortality was 3.7% (n = 185). All MSIs were significantly associated with overall survival on univariable analysis. After multivariable Cox regression analyses, lower ALI (expressed as a continuous variable) (HR 1.000, 95% CI 1.000-1.000, P = .049) and ALI <366.43 (expressed as a dichotomous variable) (HR 1.362, 95% CI 1.137-1.631, P < .001) remained independently associated with reduced overall survival.

CONCLUSIONS

MSIs have emerged in this study as potentially important factors associated with survival following lung resection for NSCLC with curative intent. In particular, ALI has emerged as independently associated with long-term outcomes. The role of MSIs in the clinical management of patients with primary lung cancer requires further investigation.

Association between advanced lung cancer inflammation index and in-hospital mortality in ICU patients with community-acquired pneumonia: A retrospective analysis of the MIMIC-IV database

Objective

The objective of the present study was to explore the correlation between the advanced lung cancer inflammation index (ALI) and in-hospital mortality among patients diagnosed with community-acquired pneumonia (CAP).

Methods

Data from the Medical Information Mart for Intensive Care-IV database were adopted to analyze the in-hospital mortality of ICU patients with CAP. Upon admission to the ICU, fundamental data including vital signs, critical illness scores, comorbidities, and laboratory results, were collected. The in-hospital mortality of all CAP patients was documented. Multivariate logistic regression (MLR) models and restricted cubic spline (RCS) analysis together with subgroup analyses were conducted.

Results

This study includes 311 CAP individuals, involving 218 survivors as well as 93 nonsurvivors. The participants had an average age of 63.57 years, and the females accounted for approximately 45.33%. The in-hospital mortality was documented to be 29.90%. MLR analysis found that ALI was identified as an independent predictor for in-hospital mortality among patients with CAP solely in the Q1 group with ALI ≤ 39.38 (HR: 2.227, 95% CI: 1.026-4.831, P = 0.043). RCS analysis showed a nonlinear relationship between the ALI and in-hospital mortality, with a turning point at 81, and on the left side of the inflection point, a negative correlation was observed between ALI and in-hospital mortality (HR: 0.984, 95% CI: 0.975-0.994, P = 0.002). The subgroup with high blood pressure showed significant interaction with the ALI.

Conclusion

The present study demonstrated a nonlinear correlation of the ALI with in-hospital mortality among individuals with CAP. Additional confirmation of these findings requires conducting larger prospective investigations.

Advanced Lung Cancer Inflammation Index for Predicting Prognostic Risk for Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Purpose

The decreased advanced lung cancer inflammation index (ALI), defined as body mass index (BMI) * albumin (Alb)/neutrophil-to-lymphocyte ratio (NLR), is an independent prognostic risk factor for overall survival in gastric, lung, and colorectal cancers. This study aimed to investigate the value of ALI in predicting the risk of major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS).

Patients and Methods

A total of 1624 patients with ACS undergoing percutaneous coronary intervention (PCI) were consecutively enrolled between January 2016 and December 2018. Follow-up data were collected at 1, 3, 6, and 12 months and annually thereafter. The primary endpoints were MACEs. All endpoints were defined as all-cause mortality, recurrent angina pectoris, restenosis/intra stent thrombosis, stroke, heart failure, and all-cause bleeding.

Results

The MACEs group and non-MACEs group showed significant differences in patients with age >65 years (28 [50.0%] vs 319 [23.7%]), history of heart failure (16 [28.6%] vs 127 [9.4%]), history of ischemic stroke (14 [25.0%] vs 186 [13.8%]), history of cardiogenic shock (6 [10.71%] vs 16 [1.19%]), left ventricular ejection fraction <40% (8 [14.29%] vs 33 [2.46%]), and ALI <343.96 (44 [78.65%] vs 680 [50.60%]) (all p<0.001). The optimal cut-off value for ALI was 334.96. The area under the curve (AUC) of the 1-, 2-, 3-, and 5-year was 0.560, 0.577, 0.665, and 0.749, respectively. The survival rate was significantly lower in the low ALI group than in the high ALI group (log-rank p<0.001). Low ALI was an independent risk factor for the long-term prognosis of patients with ACS after PCI, univariate HR: 3.671, 95% CI: 1.938-6.953, p<0.001; multivariate HR: 3.009, 95% CI: 1.57-5.769, p=0.001.

Conclusion

ALI score less than 334.96 is an independent prognostic risk factor for patients with ACS undergoing PCI and may be a novel marker for clinical practice.

Clinical significance of the advanced lung cancer inflammation index in gastrointestinal cancer patients: a systematic review and meta-analysis

Background

The advanced lung cancer inflammation index (ALI) has been identified as a scientific and clinical priority in multiple malignancies. The aim of this study is to investigate the value of the ALI before treatment in evaluating postoperative complications (POCs) and survival outcomes in patients with gastrointestinal (GI) cancer.

Methods

Electronic databases including PubMed, Embase and Web of Science were comprehensively reviewed up to June 2022. The endpoints were POCs and survival outcomes. Subgroup analyses and sensitivity analyses were also performed.

Results

Eleven studies including 4417 participants were included. A significant heterogeneity in the ALI cut-off value among studies was observed. Patients in the low ALI group showed increased incidence of POCs (OR=2.02; 95%CI:1.60-2.57; P<0.001; I² = 0%). In addition, a low ALI was also significantly associated with worse overall survival (HR=1.96; 95%CI: 1.58-2.43; P<0.001; I² = 64%), which remained consistent in all subgroups based on country, sample size, tumor site, tumor stage, selection method and Newcastle Ottawa Scale score. Moreover, patients in the low ALI group had an obviously decreased disease-free survival compared to these in the high ALI group (HR=1.47; 95%CI: 1.28-1.68; P<0.001; I² = 0%).

Conclusion

Based on existing evidence, the ALI could act as a valuable predictor of POCs and long-term outcomes in patients with GI cancer. However, the heterogeneity in the ALI cut-off value among studies should be considered when interpreting these findings.

The impact of the advanced lung cancer inflammation index on the outcomes of patients with metastatic colorectal cancer who receive chemotherapy

BACKGROUND

Advanced lung cancer inflammation index (ALI) is reported to be a prognosticator in various cancer patients with chemotherapy. However, the clinical impact of the ALI on treatment strategies in metastatic colorectal cancer (mCRC) patients remains unclear.

METHODS

A total of 356 patients, who received first-line chemotherapy for mCRC between April 2005 and November 2019 in a single institution, were retrospectively enrolled. The association of pretreatment ALI (calculated as follows: BMI × albumin value/neutrophil-to-lymphocyte ratio) status with clinicopathological factors and patient survival outcome was analyzed, using subgroup analysis.

RESULTS

The ALI-low cases were significantly associated with female sex, more synchronous metastasis, multiple metastatic sites, less primary tumor resection, less liver resection after chemotherapy, and poor overall survival (OS). A multivariate Cox proportional hazards analysis clarified that the ALI-low status was independently associated with poor OS (HR: 1.78, 95% CI 1.27-2.48, P = 0.001), in addition to right side tumor, multiple metastatic sites, and the non-performance of liver resection after chemotherapy. A subgroup analysis revealed that primary tumor resection and the resection of liver metastases after chemotherapy could not improve the prognosis of ALI-low cases in comparison with ALI-high cases, and the type of first-line chemotherapy did not significantly affect the association between the prognosis and the ALI status.

CONCLUSION

ALI comprehensively evaluates the prognostic host status and is a reliable prognosticator for the mCRC patients with chemotherapy. Calculating pretreatment ALI may serve as a cost-effective and easily available tool for constructing treatment strategies.

Nomograms Based on the Advanced Lung Cancer Inflammation Index for the Prediction of Coronary Artery Disease and Calcification

Aim

To develop and validate 3 nomograms incorporating the advanced lung cancer inflammation index (ALI) that can aid in predicting the risk of coronary artery disease (CAD) and coronary artery calcification (CAC).

Methods

The study enrolled 562 consecutive patients with suspected CAD who underwent coronary computed tomographic angiography between September 2015 and June 2017. Independent risk factors for CAD, CAC, and CAD with CAC were identified via univariate and multivariate analysis, and nomograms were established based on the independent predictors identified. The area under the curve (AUC), calibration curve, and decision curve analysis were used to evaluate the nomograms. Correlations between ALI and other clinical indicators were examined via Spearman correlation analysis.

Results

In total, 549 patients with suspected CAD who underwent coronary computed tomographic angiography were included. Male sex, hypertension, diabetes, dyslipidemia, ischemic stroke, and ALI were independent predictors of both CAD and CAC. Male sex, hypertension, diabetes, dyslipidemia, and ALI were also identified as independent predictors of CAD with CAC. The AUC values for the nomograms developed using these risk factors were 0.739 (95% confidence interval [CI], 0.693-0.785), 0.728 (95% CI, 0.684-0.772), and 0.717 (95% CI 0.673-0.761), respectively. ALI was negatively correlated with neutrophil-to-lymphocyte ratio and CAC score and positively correlated with serum albumin levels and body mass index (all P < .05).

Conclusions

ALI is an independent predictor of CAD, CAC, and CAD with CAC. Our ALI-based nomograms can provide accurate and individualized risk predictions for patients with suspected CAD.

Mediterranean Diet Implementation to Protect against Advanced Lung Cancer Index (ALI) Rise: Study Design and Preliminary Results of a Randomised Controlled Trial

The Mediterranean diet (MD) has been inversely associated with lung cancer (LC) risk. Hereby we show the preliminary results of our prospective randomised controlled trial in inflammatory and nutritional status of LC patients after 3-month implementation of MD. In total, 30 patients with small-cell or non-small-cell LC (stages III–IV) were enrolled. They were randomly assigned either to Control group, receiving general nutritional guidelines, or the MD group, in which a personalised MD plan was provided. Medical and dietary history, anthropometrics, blood biomarkers, and circulating antioxidant vitamins were assessed. The main outcome was a significantly higher advanced lung cancer inflammation index (ALI) in patients of the control arm than those following MD (p = 0.003). In the MD group, platelets were significantly reduced at the study endpoint (p = 0.044). BMI and body fat mass remained unchanged in both arms, but serum glucose was significantly higher in control compared to MD group (p = 0.017). In conclusion, we showed for the first time that implementing a personalised MD for 3 months is promising to regulate prognostic biomarkers in advanced LC. The final results of our on-going trial will shed a light on the inflammatory, antioxidant and nutritional status of LC patients following MD.

Prognostic Impact of the Advanced Lung Cancer Inflammation Index (ALI) in Metastatic Non-Small Cell Lung Cancer Treated with First Line Chemotherapy

Background:

The advanced lung cancer inflammation index (ALI) has been reported to predict the overall survival in patients with advanced non-small cell lung cancer (NSCLC). However, no previous studies have examined the prognostic significance of ALI in metastatic NSCLC treated with first line chemotherapy. The objective of this study was to explore the relationship between ALI and the prognosis of metastatic NSCLC treated with first line chemotherapy.

Materials and Methods:

Data of 109 metastatic NSCLC patients who had completed first line treatment with chemotherapy was collected. A multivariate flexible parametric proportional-hazards model with restricted cubic splines (RCS) was used to explore and identify the independent prognostic factors, including clinical potential factors and ALI for the overall survival. Multivariate regression analysis was used to evaluate the potential prognostic factors associated with short survival less than 6 months. The analysis of the restricted mean survival time (RMST) method was used to estimate the event-free time from zero to 18 months.

Results:

The median OS was 10.9 months (95%CI 9.57-13.18) and median PFS was 7.5 months (95%CI 6.85-8.00).The multivariate survival analyses revealed two prognostic factors for worse survival: Poor ECOG PS (HR46.90; 95%CI 2.90-758.73; p=0.007) and progressive disease after completing the first line chemotherapy treatment (HR 2.85; 95%CI1.18-6.88; p=0.02),whereas a low ALI <11 referred to a non-significant prognostic factor (HR 1.42; 95%CI 0.67-3.01; p=0.364).The results of the multivariate regression analysis revealed that the low ALI and progressive disease status were significantly associated with the short survival outcome (OR 5.12; 95%CI 1.11-23.65; p=0.037; OR 12.57; 95%CI 3.00-52.73; p=0.001).

Conclusions:

A low ALI was associated with the short survival in metastatic NSCLC treated with chemotherapy. However, using ALI as a prognostic factor only was still too limited. Other considerable clinical prognostic factors should also be used simultaneously, which would have strong significant prognostic impacts.

Links between Inflammation and Postoperative Cancer Recurrence

Despite complete resection, cancer recurrence frequently occurs in clinical practice. This indicates that cancer cells had already metastasized from their organ of origin at the time of resection or had circulated throughout the body via the lymphatic and vascular systems. To obtain this potential for metastasis, cancer cells must undergo essential and intrinsic processes that are supported by the tumor microenvironment. Cancer-associated inflammation may be engaged in cancer development, progression, and metastasis. Despite numerous reports detailing the interplays between cancer and its microenvironment via the inflammatory network, the status of cancer-associated inflammation remains difficult to recognize in clinical settings. In the current paper, we reviewed clinical reports on the relevance between inflammation and cancer recurrence after surgical resection, focusing on inflammatory indicators and cancer recurrence predictors according to cancer type and clinical indicators.

External validation of the prognostic relevance of the advanced lung cancer inflammation index (ALI) in pancreatic cancer patients

BACKGROUND

The advanced lung cancer inflammation index (ALI) was first introduced for prognosis prediction in lung cancer patients and since then evaluated in several other malignancies. However, in pancreatic cancer (PC) the ALI and its prognostic utility were only investigated in a comparably small and specific cohort of locally advanced PC patients treated with chemoradiotherapy.

METHODS

In our single-center cohort study, we included 429 patients with histologically verified PC who were treated between 2003 and 2015 at our academic institution. The ALI was defined as body mass index (BMI; kg/m2 ) × serum albumin levels (g/dL)/neutrophil-lymphocyte ratio (NLR) and we defined the optimal cutoff for biomarker dichotomization by ROC-analysis. Kaplan-Meier method as well as uni- and multivariate Cox regression Hazard proportional models were implemented to assess the prognostic potential of ALI in PC patients. We considered cancer-specific survival (CSS) as the primary endpoint of the study.

RESULTS

The ALI showed a significant negative correlation with CA19-9 levels and C-reactive protein levels whereas we found an association with localized tumor stage and better performance status (P < .05 for all mentioned variables). As opposed to patients with a high ALI, decreased ALI was significantly associated with shorter CSS (HR = 0.606, 95% CI: 0.471-0.779, P = .001). Multivariate analysis demonstrated tumor grade, tumor stage, chemotherapy, C-reactive protein levels, and CA19-9 levels to independently predict for CSS (all P < .05). In contrast the ALI failed to independently predict for CSS in the performed multivariate models (HR = 0.878, 95% CI: 0.643-1.198, P = .411).

CONCLUSION

In this large cohort of PC patients, the ALI did not complement existing clinicopathological factors for outcome determination.