Inflammation is closely associated with the development and prognosis of prostate cancer (PCa). The relationship between a novel systemic inflammatory marker – the neutrophil percentage-to-albumin ratio (NPAR) – and PCa remains unclear. This study aims to examine the association between NPAR and PCa using a large US population-based cohort, with the objective of providing new insights for the screening and diagnosis of PCa. We examined data from 9176 participants in the National Health and Nutrition Examination Survey spanning 2007 to 2018, extracted baseline characteristics of the population, and incorporated data from the National Death Index to acquire mortality statistics for the PCa population. Weighted multivariable logistic regression evaluated the NPAR–PCa risk association, while subgroup analyses assessed consistency across demographic strata. Kaplan–Meier survival analysis and weighted multivariate COX proportional hazards models examined survival disparities and mortality risk. Smooth curve fitting and sensitivity analysis were employed to further investigate the association. NPAR exhibited a robust positive association with PCa risk. Adjusted odds ratio for NPAR across 3 models were 1.18 (95% confidence interval CI: 1.13–1.24), 1.11 (95% CI: 1.06–1.17), and 1.12 (95% CI: 1.07–1.18), with quartile-stratified odds ratio showing incremental increases. Subgroup analyses confirmed stable associations without significant interactions. Kaplan–Meier curves revealed pronounced survival differences across NPAR quartiles. In progressively adjusted models, the adjusted hazard ratio for mortality comparing the highest versus lowest NPAR quartiles were 4.13 (95% CI: 2.43–7.01), 3.08 (95% CI: 1.78–5.33), and 2.48 (95% CI: 1.31–4.70), with statistically significant P -values for trend. Smooth curve fitting and sensitivity analysis supported a positive relationship. This study demonstrates for the first time that elevated NPAR levels are significantly associated with an increased risk of both incidence and mortality of PCa. This finding provides a robust new tool for screening high-risk populations and assessing prognosis in patients with PCa.
Jia et al. (2025) studied this question.
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