Quantifies opposing effects of radiological disease burden and type 2 inflammation on nasal nitric oxide in chronic rhinosinusitis, indicating complexities in treatment monitoring.
Background In chronic rhinosinusitis (CRS), nasal nitric oxide (nNO) levels are concurrently influenced by radiological disease burden and type 2 (T2) inflammation, yet their independent and interactive effects remain unquantified. Objective To quantify the independent and opposing effects of radiological disease burden (Lund–Mackay [LMK] score) and type 2 (T2) inflammation on nNO in patients with CRS. Methods A total of 169 CRS patients undergoing sinus surgery were enrolled. Radiologic burden was quantified using the LMK score, assessed both continuously and by tertiles (low, mid, high). T2 inflammation was stratified based on fractional exhaled nitric oxide (FeNO) and peripheral blood eosinophils into T2-Low/Low, T2-Mid, and T2-High/High groups. nNO was measured using a standardized protocol. Multivariable linear regression was performed with log-transformed nNO as the outcome, adjusting for clinical and inflammatory covariates. Percentage change (%Δ) was back-calculated from the regression coefficients. Results Each one-point increase in LMK score was associated with an 8.8% decrease in nNO (95% confidence interval [CI], −10.9% to −6.7%; p < .001). The T2-High/High phenotype was independently associated with an 86.9% increase in nNO (95% CI, +28.7% to +171.4%; p = .001). LMK score remained inversely correlated with nNO across all T2 strata (interaction p = .237). In the LMK-High group, nNO levels were significantly reduced across all T2 categories (13.2%-19.1% decrease; all p ≤ .031). Conclusion In CRS, radiological disease burden and T2 inflammation exert opposing yet independent effects on nNO. Structural obstruction predominantly lowers nNO, whereas high T2 inflammation may partially offset this reduction. These findings support the role of nNO as a composite biomarker integrating both anatomical patency and inflammatory activity, which can be utilized for CRS phenotyping and treatment monitoring.
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