The Predictive Role of Neutrophil-Percentage-to-Albumin Ratio (NPAR) in Cancer Mortality: Insights from National Health and Nutrition Examination Survey

Background: Neutrophils interact with tumor cells, potentially exacerbating cancer progression, Concurrently, diminished albumin levels are indicative of a poor cancer prognosis. The neutrophil-percentage-to-albumin ratio (NPAR) has been used in prognostic assessments of non-cancerous diseases, yet its relationship with cancer mortality remains unexplored. Therefore, we explored the correlation between NPAR and both cancer incidence and mortality, utilizing data from the National Health and Nutrition Survey (NHANES). Methods This study leveraged comprehensive NHANES data spanning 2005–2016. We analyzed the relationship between NPAR and cancer incidence and mortality using weighted Logistic and Cox regression models, alongside trend test. Restricted cubic spline analysis was employed to investigate NPAR’s nonlinear relationship with cancer mortality. Furthermore, Kaplan-Meier survival analysis was utilized on NHANES and institutional clinical data to assess patient prognoses across varying NPAR levels. Results Elevated NPAR was significantly correlated with increased cancer mortality risk in the adjusted model ( p  < 0.05), with higher NPAR values correlating with greater risk ( p -trend  0.05). Our analysis further identified a non-linear relationship between NPAR and cancer mortality ( p -nonlinear < 0.05). The relationship is characterized by an optimal NPAR value, correlating with the lowest hazard ratio (HR). Deviations from this optimal NPAR result in increased cancer mortality risk ( p  < 0.05). Kaplan-Meier analysis indicated superior survival rates in patients with lower NPAR values compared to those with higher NPAR values ( p  < 0.05). Conclusions Our findings indicate a positive correlation between NPAR and cancer mortality risk, independent of cancer incidence. NPAR emerges as a promising biomarker for predicting cancer mortality, warranting further validation through prospective studies.