Advanced lung cancer inflammation index as a predictor of all-cause and cardiovascular mortality among patients with hypertension in the US

美国高血压患者中晚期肺癌炎症指数作为全因死亡率和心血管死亡率的预测指标

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Abstract

BACKGROUND: Hypertension is a leading global cause of mortality, necessitating early identification of high-risk patients. The Advanced Lung Cancer Inflammation Index (ALI), integrating body mass index (BMI), serum albumin (Alb), and neutrophil-to-lymphocyte ratio (NLR), reflects systemic inflammation and nutritional status. While prior studies linked ALI to outcomes in chronic diseases, its prognostic utility for mortality in hypertension, particularly within nationally representative cohorts, remains underexplored. This study investigated ALI's association with all-cause and cardiovascular mortality in US patients with hypertension, addressing gaps in generalizability and clinical applicability. METHODS: Utilizing data from seven National Health and Nutrition Examination Survey (NHANES) cycles (2005-2018), we analyzed 2,805 hypertensive adults. ALI was calculated as BMI × Alb / NLR. Mortality outcomes were assessed via linkage to the National Death Index. Survey-weighted Cox proportional hazards models evaluated hazard ratios (HRs) for all-cause and cardiovascular mortality across ALI quartiles (Q1-Q4), adjusted sequentially for demographics, comorbidities, and laboratory parameters. Restricted cubic splines (RCS) tested for nonlinear associations. Predictive accuracy was assessed using time-dependent receiver operating characteristic (ROC) curves, and clinical utility was evaluated via decision curve analysis (DCA). Competing risk models addressed non-cardiovascular deaths. RESULTS: Over a median follow-up of 57.6 months, higher ALI quartiles were associated with progressively lower risks of mortality. In fully adjusted models, participants in the highest ALI quartile (Q4) had significantly reduced risks compared to the lowest quartile (Q1): a 53.8% reduction in all-cause mortality (HR: 0.46, 95% CI: 0.28-0.77) and an 83.5% reduction in cardiovascular mortality (HR: 0.17, 95% CI: 0.06-0.48). Time-dependent ROC demonstrated strong predictive accuracy for cardiovascular mortality over 1-5 years (AUC: 0.735-0.772). DCA confirmed ALI's superior net benefit across threshold probabilities. Subgroup analyses revealed consistent associations regardless of age, sex, or comorbidities. CONCLUSION: ALI robustly predicts mortality in patients with hypertension in the US by synthesizing inflammatory, nutritional, and metabolic pathways. Its clinical utility, simplicity, and cost-effectiveness support routine use for risk stratification. Future studies should validate ALI in diverse populations and explore targeted interventions for low-ALI patients. This study advances hypertension management by integrating multidimensional risk assessment into prognostic algorithms. TRIAL REGISTRATION: Clinical trial number: not applicable.

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