Development and Validation of a Nomogram Integrative of Clinical Characteristics and Serum Inflammatory Biomarkers for Predicting Postoperative Recurrence in Patients with Chronic Rhinosinusitis with Nasal Polyps

Introduction: Postoperative recurrence remains a significant challenge in the management of chronic rhinosinusitis with nasal polyps (CRSwNP), imposing a heavy burden on patients and healthcare systems. Existing prediction models often rely on invasive tissue sampling or limited clinical phenotype. This study aimed to construct a broad-spectrum, noninvasive nomogram by integrating clinical characteristics with a panel of serum inflammatory biomarkers to predict the risk of recurrence after endoscopic sinus surgery (ESS). Methods: A total of 312 patients with CRSwNP who underwent ESS at our center between January 2019 and October 2023 were retrospectively recruited. Patients were randomly divided into a training cohort (n = 218) and a validation cohort (n = 94) at a 7:3 ratio. Clinical data and preoperative serum levels of inflammatory markers (eotaxin-1, periostin, IL-5, total IgE) were collected. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen optimal predictors. A nomogram was established based on multivariate logistic regression analysis. The model’s performance was assessed using the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Results: During a minimum of 2-year follow-up, recurrence occurred in 38.5% of the total cohort. LASSO and multivariate analyses identified five independent predictors: history of asthma (odds ratio [OR] = 3.45), revision surgery (OR = 2.12), Lund-Mackay score (OR = 1.15), serum eotaxin-1 level (OR = 1.02 per pg/mL), and serum periostin level (OR = 1.04 per ng/mL). The developed nomogram demonstrated robust discrimination, with a C-index of 0.892 (95% confidence interval [CI]: 0.851–0.933) in the training cohort and 0.865 (95% CI: 0.812–0.918) in the validation cohort. Internal validation showed an optimism-corrected C-index of 0.879. Calibration plots revealed excellent agreement between predicted and observed probabilities. DCA indicated that the nomogram provided substantial net clinical benefit across a wide range of threshold probabilities. Conclusion: We successfully developed a novel, high-discrimination nomogram incorporating clinical factors and serum biomarkers (eotaxin-1 and periostin). This tool offers a practical, noninvasive approach for clinicians to identify high-risk CRSwNP patients early, facilitating personalized postoperative management and potentially guiding the use of biological therapies.