High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2026
Association Between Naples Prognostic Score and All-Cause Mortality in Individuals with Cardio-Renal-Metabolic Multimorbidity: A Cohort Study.
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Wen Song, Shi Wei, Huang Xingjie, Deng Zhexuan, Yang Hua, Chen Nan, Meng Lingbing
Аннотация
INTRODUCTION: The Naples Prognostic Score (NPS) has demonstrated prognostic value in oncology and certain chronic diseases. Its utility in cardio-renal-metabolic multimorbidity (CRMM) remains unexplored.
AIM: This study aims to evaluate the association between NPS and all-cause mortality in individuals with CRMM.
METHODS: We analyzed data from the National Health and Nutrition Examination Survey (1999-2018) comprising 3,602 adults with CRMM. The NPS was derived from serum albumin, total cholesterol (TC), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). Weighted Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to evaluate associations between NPS and all-cause mortality.
RESULTS: Over a median follow-up of 79 months, 1,621 (41.4%) deaths occurred. After comprehensive adjustment for potential confounders, each 1-point increase in NPS was associated with a 24.6% higher risk of all-cause mortality (HR 1.246, 95% CI 1.150-1.350, P < 0.0001). The HRs for all-cause mortality was 1.133 (95 % CI: 0.846-1.518, P = 0.401) in the medium NPS group and 1.721 (95 % CI: 1.248-2.375, P = 0.0009) in the high NPS group, as compared with the low NPS group. RCS analysis indicated a nonlinear relationship between NPS and all-cause mortality among participants with CRMM (Pnonlinear=0.014). Weighted quantile sum regression analysis identified NLR as the primary contributor to mortality risk (weight: 0.612 at 2 years, 0.580 at 5 years), followed by TC.
CONCLUSION: This study identified a positive, nonlinear association between NPS and all-cause mortality in CRMM individuals. The NPS integrates inflammatory, metabolic, and nutritional biomarkers into a practical prognostic tool that may enhance risk stratification and guide personalized management in multimorbidity.
AIM: This study aims to evaluate the association between NPS and all-cause mortality in individuals with CRMM.
METHODS: We analyzed data from the National Health and Nutrition Examination Survey (1999-2018) comprising 3,602 adults with CRMM. The NPS was derived from serum albumin, total cholesterol (TC), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). Weighted Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to evaluate associations between NPS and all-cause mortality.
RESULTS: Over a median follow-up of 79 months, 1,621 (41.4%) deaths occurred. After comprehensive adjustment for potential confounders, each 1-point increase in NPS was associated with a 24.6% higher risk of all-cause mortality (HR 1.246, 95% CI 1.150-1.350, P < 0.0001). The HRs for all-cause mortality was 1.133 (95 % CI: 0.846-1.518, P = 0.401) in the medium NPS group and 1.721 (95 % CI: 1.248-2.375, P = 0.0009) in the high NPS group, as compared with the low NPS group. RCS analysis indicated a nonlinear relationship between NPS and all-cause mortality among participants with CRMM (Pnonlinear=0.014). Weighted quantile sum regression analysis identified NLR as the primary contributor to mortality risk (weight: 0.612 at 2 years, 0.580 at 5 years), followed by TC.
CONCLUSION: This study identified a positive, nonlinear association between NPS and all-cause mortality in CRMM individuals. The NPS integrates inflammatory, metabolic, and nutritional biomarkers into a practical prognostic tool that may enhance risk stratification and guide personalized management in multimorbidity.
Предметные рубрики MeSH
HumansRisk FactorsFemaleMalePrognosisBiomarkersCause of DeathTime FactorsMiddle AgedRisk AssessmentPredictive Value of TestsMultimorbidityAgedNutrition SurveysUnited StatesCholesterolKidney DiseasesSerum Albumin, HumanNeutrophilsAdultMonocytesLymphocyte CountLymphocytesDecision Support TechniquesCardiovascular Diseases