A novel risk score for disease control prediction of Chronic rhinosinusitis

Abstract Objectives: To assess the impact of risk factors on the disease control among CRS patients, following 1 year of functional endoscopic sinus surgery (FESS), and combining the risk factors to formulate a convenient, visualized prediction model. Design: A retrospective and nonconcurrent cohort study Setting and Participants: A total of 325 patients with Chronic rhinosinusitis (CRS) from June 2018 to July 2020 at the First Affiliated Hospital, the Third Affiliated Hospital, and the Seventh Affiliated Hospital of Sun Yat-sen University. Main Outcomes Measures: Outcomes were time to event measures: the disease control of CRS after surgery 1 year. The presence of nasal polyps, smoking habits, allergic rhinitis (AR), the ratio of tissue eosinophil (TER), and peripheral blood eosinophil count (PBEC)and asthma was assessed. The logistic regression models were used to conduct multivariate and univariate analyses. Asthma, TER, AR, PBEC were also included in the nomogram. The calibration curve and AUC (Area Under Curve) were used to evaluate the forecast performance of the model. Results: In univariate analyses, most of the covariates had significant associations with the endpoints, except for age, gender, and smoking. The nomogram showed the highest accuracy with an AUC of 0.760 (95% CI, 0.688-0.830) in the training cohort. Conclusions: In this cohort study that included the asthma, AR, TER, PBEC had significantly affected the disease control of CRS after surgery. The model provided relatively accurate prediction in the disease control of CRS after FESS and served as a visualized reference for daily diagnosis and treatment.