Prognosis and risk factor assessment of patients with advanced lung cancer with low socioeconomic status: model development and validation.

BACKGROUND: Lung cancer, a major global health concern, disproportionately impacts low socioeconomic status (SES) patients, who face suboptimal care and reduced survival. This study aimed to evaluate the prognostic performance of traditional Cox proportional hazards (CoxPH) regression and machine learning models, specifically Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), in patients with advanced lung cancer with low SES. DESIGN: A retrospective study. METHOD: The 949 patients with advanced lung cancer with low SES who entered the hospice ward of a tertiary hospital in Wuhan, China, from January 2012 to December 2021 were randomized into training and testing groups in a 3:1 ratio. CoxPH regression methods and four machine learning algorithms (DT, RF, SVM, and XGBoost) were used to construct prognostic risk prediction models. RESULTS: The CoxPH regression-based nomogram demonstrated reliable predictive accuracy for survival at 60, 90, and 120 days. Among the machine learning models, XGBoost showed the best performance, whereas RF had the lowest accuracy at 60 days, DT at 90 days, and SVM at 120 days. Key predictors across all models included Karnofsky Performance Status (KPS) score, quality of life (QOL) score, and cough symptoms. CONCLUSIONS: CoxPH, DT, RF, SVM, and XGBoost models are effective in predicting mortality risk over 60-120 days in patients with advanced lung cancer with low SES. Monitoring KPS, QOL, and cough symptoms is crucial for identifying high-risk patients who may require intensified care. Clinicians should select models tailored to individual patient needs and preferences due to varying prediction accuracies. REPORTING METHOD: This study was reported in strict compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

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.

Prognostic Value of the Advanced Lung Cancer Inflammation Index Ratio in Patients with Acute Myocardial Infarction Complicated by Cardiogenic Shock: A Cohort Study.

Background: Acute myocardial infarction (AMI) complicated by cardiogenic shock (CS) carries a high mortality risk. Inflammation and nutrition are involved in the pathogenesis and prognosis of both AMI and CS. The advanced lung cancer inflammation index ratio (ALI) combines the inflammatory and nutritional status. Our present study aimed to explore the prognostic value of ALI in patients with CS following AMI. Methods: In total, 217 consecutive patients with AMI complicated by CS were divided into two groups based on the ALI admissions cut-off: ≤ 12.69 and > 12.69. The primary endpoint of this study was 30-day all-cause mortality. The secondary endpoints were gastrointestinal hemorrhage and major adverse cardiovascular events (MACEs), including 30-day all-cause mortality, atrioventricular block, ventricular tachycardia/ventricular fibrillation, and nonfatal stroke. The association of ALI with the study endpoints was analyzed by Cox regression analysis. Results: During the 30-day follow-up period after admission, 104 (47.9%) patients died and 150 (69.1%) suffered MACEs. The Kaplan-Meier analysis revealed significantly higher cumulative mortality and lower MACE rates in the low-ALI group compared to the high-ALI group (both log-rank p < 0.001). The 30-day mortality rate was significantly higher in patients with ALI ≤ 12.69 compared to ALI > 12.69 (72.1% vs. 22.6%; p < 0.001). Furthermore, the incidence of MACEs was higher in patients with ALI ≤ 12.69 (85.6% vs. 51.9%; p < 0.001). The receiver operating curve showed that ALI had a modest predictive value (area under the curve [AUC]: 0.789, 95% confidence interval [CI]: 0.729, 0.850). After multivariable adjustment, ALI ≤ 12.69 was an independent predictor for both 30-day all-cause mortality (hazard ratio [HR]: 3.327; 95% CI: 2.053, 5.389; p < 0.001) and 30-day MACEs (HR: 2.250; 95% CI 1.553, 3.260; p < 0.001). Furthermore, the addition of ALI to a base model containing clinical and laboratory data statistically improved the predictive value. Conclusions: Assessing ALI levels upon admission can provide important information for the short-term prognostic assessment of patients with AMI complicated by CS. A lower ALI may serve as an independent predictor of increased 30-day all-cause mortality and MACEs.

A case of response to combination treatment with TSA-DC-CTL immunotherapy and osimertinib in EGFR mutated advanced lung adenocarcinoma.

BACKGROUND: This study details a case of a patient with advanced lung adenocarcinoma harboring an exon 19 deletion in the EGFR gene. METHOD: A 46-year-old female patient was diagnosed with stage IVb left lung adenocarcinoma, with multiple bone and lymph node metastases. Following the identification of tumor-specific antigen peptides, the patient received a combination treatment of immunotherapy (TSA-DC-CTL) and oral osimertinib. Peripheral blood circulating immune cells and circulating tumor cells (CTCs) were monitored before and after treatment. PET-CT and CT scans were used to assess the tumor response to treatment. RESULTS: A significant increase in total lymphocyte percentage and decrease in the number of CTCs in the patient was observed. Imaging studies showed a notable reduction in tumor metastases. CONCLUSION: This report demonstrates the safety and efficacy of TSA-DC-CTL cell immunotherapy combined with osimertinib in the treatment of a patient with advanced lung adenocarcinoma with an EGFR exon 19 deletions. This study describes a promising new treatment option for patients with advanced lung cancer with EGFR mutations.

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.

Molecular heterogeneity and treatment outcome of EGFR exon 20 insertion mutations in Chinese patients with advanced non-small cell lung cancer: insights from a large-scale real-world study.

INTRODUCTION: This retrospective study aimed to investigate treatment patterns and outcomes in patients with NSCLC harboring EGFR20ins in China. EGFR20ins mutations are associated with poor responses to EGFR-TKIs, and limited real-world data exist regarding the efficacy of various treatment modalities. METHODS: In this retrospective, single-center study, treatment outcomes, including PFS and ORR, were evaluated for different treatment regimens based on imaging assessments. The impact of mutation heterogeneity on treatment efficacy was also explored. RESULTS: Data from 302 patients diagnosed with NSCLC with EGFR20ins were analyzed. EGFR-TKI monotherapy demonstrated suboptimal PFS compared to platinum-based chemotherapy in the first-line setting (3.00 m vs. 6.83 m, HR = 3.674, 95%CI = 2.48-5.44, p < 0.001). Platinum plus pemetrexed plus bevacizumab combination therapy showed improved PFS and ORR compared to platinum plus pemetrexed (7.50m vs. 5.43 m, HR = 0.593, 95%CI = 0.383-0.918, p = 0.019). In later-line treatments, monotherapy with EGFR-TKIs or ICIs exhibited suboptimal efficacy. The specific EGFR20ins subtype, A763_Y764insFQEA, showed favorable responses to EGFR-TKIs in real-world settings. CONCLUSIONS: This large-scale real-world study provides valuable insights into the treatment patterns and outcomes of NSCLC patients with EGFR20ins mutations in China. These findings contribute to the understanding of EGFR20ins treatment and provide real-world benchmark for future clinical trials and drug development.

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.

Association between nutrition-related indicators with the risk of chronic obstructive pulmonary disease and all-cause mortality in the elderly population: evidence from NHANES.

Background: This study aims to use six nutrition-related indicators to assess the relationship between nutritional status and the risk of COPD as well as the all-cause mortality rate, and to determine the most reliable predictive indicators. Methods: Data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2013 to 2018 were extracted. Nutritional status was evaluated using Controlling nutritional status (CONUT) score, Geriatric Nutritional Risk Index (GNRI), Advanced Lung Cancer Inflammation Index (ALI), Prognostic Nutritional Index (PNI), Triglycerides (TG) × Total Cholesterol (TC) × Body Weight (BW) Index (TCBI), and Albumin-to-Globulin Ratio (AGR) nutritional-related indicators. Multivariate weighted logistic and Cox regression models were employed to assess the correlation between the six nutritional-related indicators and the risk of COPD and as all-cause mortality. The restricted cubic spline tests were applied to explore potential nonlinear relationships, and ROC curves and C-index analyses were conducted to compare the predictive capabilities of different indicators. Stratified analysis and propensity score matching (PSM) to assess the robustness of the results. Results: In this study, Lower ALI, lower GNRI, and higher CONUT scores were positively correlated with an increased risk of COPD (OR: 1.77, 95% CI: 1.10-2.84) (OR: 8.66, 95% CI: 2.95-25.5), and (OR: 5.11, 95% CI: 1.72-15.2), respectively. It was found that ALI and GNRI had a non-linear relationship with the risk of COPD. After propensity score matching (PSM), the associations between ALI, GNRI, CONUT scores, and COPD remained consistent. Lower ALI, PNI, and GNRI scores were positively associated with all-cause mortality in COPD patients (HR: 2.41, 95% CI: 1.10-5.27), (HR: 3.76, 95% CI: 1.89-7.48), and (HR: 4.55, 95% CI: 1.30-15.9), respectively, with GNRI displaying a non-linear relationship with all-cause mortality. ROC curve and C-index analyses indicated that ALI had the best predictive ability for both COPD risk and all-cause mortality. Conclusion: ALI, GNRI, and CONUT scores are correlated with the risk of COPD, while ALI, PNI, and GNRI scores are associated with all-cause mortality in COPD patients. Compared to other nutritional scores, ALI may provide more effective predictive value for both risk and all-cause mortality.

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.

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.

Candidate tumor-specific CD8+ T cell subsets identified in the malignant pleural effusion of advanced lung cancer patients by single-cell analysis.

Isolation of tumor-specific T cells and their antigen receptors (TCRs) from malignant pleural effusions (MPE) may facilitate the development of TCR-transduced adoptive cellular immunotherapy products for advanced lung cancer patients. However, the characteristics and markers of tumor-specific T-cells in MPE are largely undefined. To this end, to establish the phenotypes and antigen specificities of CD8+ T cells, we performed single-cell RNA and TCR sequencing of samples from three advanced lung cancer patients. Dimensionality reduction on a total of 4,983 CD8+ T cells revealed 10 clusters including naïve, memory, and exhausted phenotypes. We focused particularly on exhausted T cell clusters and tested their TCR reactivity against neoantigens predicted from autologous cancer cell lines. Four different TCRs specific for the same neoantigen and one orphan TCR specific for the autologous cell line were identified from one of the patients. Differential gene expression analysis in tumor-specific T cells relative to the other T cells identified CXCL13, as a candidate gene expressed by tumor-specific T cells. In addition to expressing CXCL13, tumor-specific T cells were present in a higher proportion of T cells co-expressing PDCD1(PD-1)/TNFRSF9(4-1BB). Furthermore, flow cytometric analyses in advanced lung cancer patients with MPE documented that those with high PD-1/4-1BB expression have a better prognosis in the subset of 57 adenocarcinoma patients (p = .039). These data suggest that PD-1/4-1BB co-expression might identify tumor-specific CD8+ T cells in MPE, which are associated with patients' prognosis. (233 words).

Association between the advanced lung cancer inflammation index and all-cause and cardiovascular mortality in patients with RA: Insights from NHANES data analysis.

Background: Rheumatoid arthritis (RA) is associated with significant mortality, which is primarily due to cardiovascular complications. Despite advancements in RA treatment, mortality rates remain high, highlighting the need for reliable prognostic markers. The advanced lung cancer inflammation index (ALI), which integrates inflammatory and nutritional biomarkers, has shown promise in predicting outcomes in various medical conditions. However, its role in RA prognosis remains unclear. Methods: This study aimed to investigate the associations between the ALI and all-cause mortality, as well as cardiovascular mortality, in RA patients using data from the National Health and Nutrition Examination Survey (NHANES). A total of 1568 RA patients were included, and the ALI was calculated using body mass index (BMI), serum ALB, and the neutrophil-to-lymphocyte ratio. Comprehensive demographic, lifestyle, and metabolic data from the NHANES enabled adjustments for potential confounders. Multivariate Cox regression and sensitivity analyses were conducted to assess the associations between the ALI and mortality outcomes. Results: Our findings demonstrate an inverse association between the ALI and both all-cause and cardiovascular mortality in RA patients. Furthermore, a nonlinear relationship was observed, with mortality risk increasing significantly below a certain ALI threshold. Stratified analyses revealed a protective effect of the ALI across various demographic and clinical subgroups, underscoring its potential as a prognostic marker in patients with RA. Conclusion: The ALI holds promise as a valuable prognostic marker for identifying high-risk individuals and guiding personalized management strategies for patients with RA. However, further validation in prospective studies is warranted to confirm its clinical utility. Nonetheless, the potential implications of the ALI for improving the prognosis of patients with RA underscore the importance of its continued investigation in clinical practice.

Association of advanced lung cancer inflammation index with all-cause and cardiovascular mortality in US patients with rheumatoid arthritis.

Introduction: As a systemic autoimmune disorder, the prognosis of rheumatoid arthritis (RA) is intricately linked to inflammation. This study aimed to investigate the association between the advanced lung cancer inflammation index (ALI), a comprehensive indicator of inflammation combined with nutritional status, and all-cause and cardiovascular mortality among patients diagnosed with RA. Methods: The 2,305 RA patients from NHANES (2001-2018) included in the analysis were categorized into three groups according to ALI tertiles. Weighted Kaplan-Meier and multivariate COX regression analyses evaluated the relationship between ALI and mortality. The time-dependent characteristic curve (ROC) was used to assess the prediction accuracy of ALI. Results: During a median follow-up of 7.92 years, 591 participants died from all causes, including 197 from cardiovascular diseases. Increased ALI was associated with a decreased probability of death. The full COX model revealed lower all-cause mortality hazard risks in the T2 (HR: 0.67, 95%CI: 0.54-0.83) and T3 (HR: 0.47 95%CI: 0.33-0.67, p for tend <0.001) groups compared to T1, and the risk of cardiovascular mortality was also lower in the groups of T2 (HR: 0.47, 95%CI: 0.31-0.70) and T3 (HR: 0.34, 95%CI: 0.19-0.62, p for trend <0.001). Furthermore, the ROC analysis underscored the strong predictive capability of ALI (AUC for 1-year all-cause and cardiovascular mortality were 0.73 and 0.79, respectively). Conclusion: This cohort study demonstrated the higher accuracy of ALI in predicting mortality in RA patients, highlighting the important clinical value of ALI in risk assessment and prognosis evaluation.

Sex differences in the combined influence of inflammation and nutrition status on depressive symptoms: insights from NHANES.

Background: Both nutrition and inflammation are associated with depression, but previous studies have focused on individual factors. Here, we assessed the association between composite indices of nutrition and inflammation and depression. Methods: Adult participants selected from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were chosen. The exposure variable was the Advanced Lung Cancer Inflammation Index (ALI) integrating nutrition and inflammation, categorized into low, medium, and high groups. The outcome variable was depression assessed using the Patient Health Questionnaire-9 (PHQ-9). A multivariable logistic regression model was employed to evaluate the relationship between ALI and the risk of depression. Results: After extensive adjustment for covariates, in the overall population, participants with moderate and high levels of ALI had a decreased prevalence of depression compared to those with low ALI levels, with reductions of 17% (OR, 0.83; 95% CI: 0.72-0.97) and 23% (OR, 0.77; 95% CI: 0.66-0.91), respectively. Among females, participants with moderate and high ALI levels had a decreased prevalence of depression by 27% (OR, 0.73; 95% CI: 0.60-0.88) and 21% (OR, 0.79; 95% CI: 0.64-0.98), respectively, compared to those with low ALI levels, whereas no significant association was observed among males. Subgroup analyses based on females and males yielded consistent results. Conclusion: In this study, we observed a negative correlation between moderate to high levels of ALI and the prevalence of depression, along with gender differences. Specifically, in females, greater attention should be given to the nutritional and inflammatory status.

The advanced lung cancer inflammation index is associated with mortality in peritoneal dialysis patients.

BACKGROUND: There is still a very high morbidity and mortality rate for patients undergoing peritoneal dialysis (PD). The advanced lung cancer inflammation index (ALI) has been demonstrated to be associated with the prognosis in multiple types of cancers. Like in cancer, systemic chronic low-grade inflammation is one of the distinguishing features of PD patients. Therefore, we aimed to investigate the relationships between the ALI and all-cause and cardiovascular disease (CVD) mortality in PD patients. METHODS: Patients who started PD at Shaoxing People's Hospital between 1 January 2013 and 31 December 2020 (n = 277) were recruited and followed up until 1 July 2023. They were divided into high-ALI group and low-ALI group according to the median of ALI. Kaplan-Meier curves and multivariate Cox regression analyses were used to assess the associations between the ALI and all-cause and CVD mortality. Receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) was calculated to determine the predictive power of the ALI for all- cause and CVD mortality. RESULTS: During the median follow-up of 40.50 months (interquartile range, 26.42-59.77 months), a total of 55 patients died, 31 of whom died due to CVD. Kaplan-Meier curves revealed that patients in the low-ALI group had significantly lower cumulative and cardiovascular cumulative survival rates than did those in the high-ALI group (all P < 0.001). After we corrected for confounders, the risk of all-cause and CVD mortality was significantly greater in the low-ALI group than in the high-ALI group [hazard ratio (HR) 1.944, 95% confidence interval (CI) 1.068-3.540, P = 0.030, and HR 2.672, 95% CI 1.188-6.009, P = 0.017, respectively]. The predictive value of ALI (AUC = 0.708, 95% CI 0.630-0.786, P < 0.001) for all-cause mortality was superior to albumin (AUC = 0.644, 95% CI 0.556-0.726, P < 0.001), body mass index (AUC = 0.581, 95% CI 0.496-0.659, P = 0.069) and neutrophil-to-lymphocyte ratio (AUC = 0.675, 95% CI 0.596-0.754, P < 0.001). CONCLUSION: A lower ALI is an independent risk factor for all-cause and cardiovascular mortality in PD patients. The ALI may be an effective indicator for predicting outcomes in PD patients.

The chain mediating effect of spiritual well-being and anticipatory grief between benefit finding and meaning in life of patients with advanced lung cancer: Empirical research quantitative.

AIM: This study aimed to explore the chain mediating effect of spiritual well-being and anticipatory grief between benefit finding and meaning in life of patients with advanced lung cancer. DESIGN: This was a cross-sectional study. METHODS: The research included 400 patients with advanced lung cancer who attended REDACTE from December 2022 to August 2023 as the research subjects. Data were collected using a questionnaire including socio-demographic and clinical characteristics, the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being scale (FACIT-Sp-12), the Benefit Finding Scale (BFS), the Preparatory Grief in Advanced Cancer Patients Scale (PGAC), and the Meaning of Life Questionnaire (MLQ). The structural equation model (SEM) was used to analyse the relationship between benefit finding, spiritual well-being, anticipatory grief and meaning in life. RESULTS: There was a significant correlation between benefit finding, spiritual well-being, anticipatory grief, and meaning in life. Benefit finding could have a direct positive impact on meaning in life of patients with advanced lung cancer, but it could also indirectly affect meaning in life of patients with advanced lung cancer through three pathways: the mediating effect of spiritual well-being, the mediating effect of anticipatory grief and the chain mediating effect of spiritual well-being and anticipatory grief. Nursing staff should develop an integrated program of interventions to enhance the meaning in life of patients with advanced lung cancer.

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

[This corrects the article DOI: 10.3389/fonc.2023.997314.].

The advanced lung cancer inflammation index (ALI) predicted the postoperative survival rate of patients with non-small cell lung cancer and the construction of a nomogram model.

OBJECTIVE: To investigate the prognostic significance of the advanced lung cancer inflammation index (ALI) in patients with operable non-small-cell lung carcinoma (NSCLC). By constructing the nomogram model, it can provide a reference for clinical work. METHODS: A total of 899 patients with non-small cell lung cancer who underwent surgery in our hospital between January 2017 and June 2021 were retrospectively included. ALI was calculated by body mass index (BMI) × serum albumin/neutrophil to lymphocyte ratio (NLR). The optimal truncation value of ALI was obtained using the receiver operating characteristic (ROC) curve and divided into two groups. Survival analysis was represented by the Kaplan-Meier curve. The predictors of Overall survival (OS) were evaluated by the Cox proportional risk model using single factor and stepwise regression multifactor analysis. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling 1 000 times) was used for internal verification of the nomogram model. The concordance index (C-index) was used to represent the prediction performance of the nomogram model, and the calibration graph method was used to visually represent its prediction conformity. The application value of the model was evaluated by decision curve analysis (DCA). RESULTS: The optimal cut-off value of ALI was 70.06, and the low ALI group (ALI < 70.06) showed a poor survival prognosis. In multivariate analyses, tumor location, pathological stage, neuroaggression, and ALI were independently associated with operable NSCLC-specific survival. The C index of OS predicted by the nomogram model was 0.928 (95% CI: 0.904-0.952). The bootstrap self-sampling method (B = 1000) was used for internal validation of the prediction model, and the calibration curve showed good agreement between the prediction and observation results of 1-year, 2-year, and 3-year OS. The ROC curves for 1-year, 2-year, and 3-year survival were plotted according to independent factors, and the AUC was 0.952 (95% CI: 0.925-0.979), 0.951 (95% CI: 0.916-0.985), and 0.939 (95% CI: 0.913-0.965), respectively. DCA shows that this model has good clinical application value. CONCLUSION: ALI can be used as a reliable indicator to evaluate the prognosis of patients with operable NSCLC, and through the construction of a nomogram model, it can facilitate better individualized treatment and prognosis assessment.

A propensity­matched analysis of the prognostic value of advanced lung cancer inflammation index in patients with gastric cancer after curative resection.

The prognostic significance of inflammation, immune response and nutritional status in patients with cancer is well-documented. The advanced lung cancer inflammation index (ALI) has emerged as a novel prognostic indicator, reflecting both inflammation and nutritional status. This study aimed to assess the prognostic relevance of preoperative ALI in patients with gastric cancer (GC). Data of 459 patients who underwent curative gastrectomy for GC between December 2013 and November 2017 at the Kanagawa Cancer Center (Yokohama, Japan) were retrospectively analyzed. Preoperative ALI was calculated from blood tests. Patients were divided into the high- and low-ALI groups. This study investigated the association between preoperative ALI, clinicopathological features, overall survival (OS) and relapse-free survival (RFS) after propensity-matched analysis. Comparative analysis revealed that patients in the low-ALI group tended to be older, were predominantly female, had lower body mass index and had a higher incidence of lymphatic invasion compared with those in the high-ALI group before propensity-matched analysis. Notably, the low-ALI group exhibited significantly reduced OS and RFS post-gastrectomy (85.5% vs. 93.8%, P=0.01; and 82.1% vs. 91.8%, P=0.02, respectively). Multivariate analysis identified low ALI as an independent prognostic factor for both OS and RFS. In conclusion, preoperative ALI could provide a valuable prognostic tool for patients with GC undergoing curative resection, offering insights into patient survival outcomes based on their inflammatory and nutritional status.