Development and validation of a nomogram model for the prediction of recurrence after endoscopic sinus surgery in patients with chronic rhinosinusitis with nasal polyps
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective To analyze the factors influencing recurrence after endoscopic sinus surgery (ESS) in patients with chronic rhinosinusitis with nasal polyps (CRSwNP). A nomogram model for risk prediction was constructed and validated. Methods Retrospective analysis of clinical data of 460 patients with chronic sinusitis and nasal polyps at the 82nd Group Military Hospital of the People’s Liberation Army of China from January 2020 to May 2022. Randomly divide into training set (n = 322) and validation set (n = 138) in a 7:3 ratio. Divide the training set into a Recurrence group or a Non-recurrence group based on whether the patient relapses within one year after surgery. Analysis the risk factors of postoperative recurrence in patients and draw a risk prediction nomogram model. Results Gastroesophageal reflux disease (GERD), bronchial asthma, sinusitis type, allergic rhinitis, eosinophil count, neutrophil count, lymphocyte count, and total sinus score were independent risk factors for postoperative recurrence in CRSwNP patients (P < 0.05). The Nomogram model constructed based on the above factors was validated, and the results showed that the C-indices of the training set and validation set are 0.935 and 0.923, respectively. The internal validation receiver operating characteristic (ROC) curve of area under the curve (AUC) was 0.948; The external validation set AUC is 0.932. The decision curve shows a higher net benefit value when the threshold probability is between 5% and 100%. Conclusions The predictive nomogram model constructed in this article has high recognition efficiency.
Source: Frontiers in Surgery
Authors: Ruiying Ma, Zhibin Lu, Jianguang Zhu, Yundong Bai, Xuyan Wang
Institution: Chinese People's Liberation Army
Language: English
Subfield: Otorhinolaryngology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4409825547