Objective Inflammation plays an important role in psoriasis. The neutrophil‐to‐albumin ratio (NPAR) is a low‐cost and easily accessible novel inflammatory biomarker. It has been validated for assessing the prognosis of multiple diseases, such as cancer and rheumatoid arthritis. However, the association between NPAR and psoriasis remains undefined. Therefore, this study aimed to investigate the association between NPAR and psoriasis. Methods This study adopted a cross‐sectional design. Data were extracted from the National Health and Nutrition Examination Survey (NHANES), covering five consecutive survey cycles between 2003 to 2006 and 2009 to 2014. Relevant clinical indicator data of adult participants with psoriasis were retrieved from the database. Participants with incomplete data were strictly excluded to ensure the reliability of subsequent analyses. Considering that the values of NPAR showed a skewed distribution, and to meet the data distribution requirements of statistical models, we performed a natural logarithmic transformation (ln transformation) on NPAR before analyzing its relationship with psoriasis. Weighted logistic regression, restricted cubic spline (RCS) regression, and subgroup analyses were used to systematically evaluate the potential association and interaction between NPAR and psoriasis. Meanwhile, sensitivity analyses were performed by comparing differences in baseline characteristics between preinclusion and excluded populations, as well as between the final included and excluded populations, and by using random forest imputation to handle missing values so as to verify the robustness of the study findings. Results A total of 16,651 participants were enrolled in the study, of whom 468 were identified as having psoriasis. In contrast to the nonpsoriasis group, the psoriasis group demonstrated markedly elevated NPAR levels. After adjusting for potential confounders, elevated NPAR was significantly associated with psoriasis ( p = 0.009, OR = 3.14, and 95% CI: 1.34–7.37). RCS revealed a nonlinear association with an inflection point at Ln NPAR = 6.77, above which the positive association became more evident (nonlinear p 0.05). Sensitivity analyses confirmed the stability of our core findings. Although minor differences were observed in individual indicators (e.g., Scr and SUA) between the preinclusion/exclusion population and the final study population, and partial indicators showed slight variations after missing data imputation (via the random forest method), repeated logistic regression analyses consistently demonstrated a significant association between NPAR and psoriasis. Specifically, the odds ratios across Models 1–3 ranged from 3.15 (95% CI: 2.02–4.92) to 2.66 (95% CI: 1.70–4.19), all of which were statistically significant. These results further validate the robustness of our findings. Conclusion The study indicates a positive affiliation between NPAR and the occurrence of psoriasis. However, this study has several limitations. The diagnosis of psoriasis was based on self‐reported physician diagnosis, which may introduce misclassification bias. In addition, the cross‐sectional design precludes causal inference. Therefore, large‐sample prospective studies are still needed in the future to further verify the above conclusions and explore the underlying mechanisms.
Yang et al. (Thu,) studied this question.