A prediction modeling based on SNOT-22 score for endoscopic nasal septoplasty: a retrospective study
Xue-ran Kang,
Bin Chen,
Yi-sheng Chen,
Bin Yi,
Xiaojun Yan,
Chenyan Jiang,
Shulun Wang,
Lixing Lu,
Runjie Shi
Affiliations
Xue-ran Kang
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Bin Chen
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Yi-sheng Chen
Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Bin Yi
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Xiaojun Yan
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Chenyan Jiang
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shulun Wang
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Lixing Lu
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Runjie Shi
Department of Otorhinolaryngology Head and Neck Surgery, Shanghai ninth people’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Background To create a nomogram prediction model for the efficacy of endoscopic nasal septoplasty, and the likelihood of patient benefiting from the operation. Methods A retrospective analysis of 155 patients with nasal septum deviation (NSD) was performed to develop a predictive model for the efficacy of endoscopic nasal septoplasty. Quality of life (QoL) data was collected before and after surgery using Sinonasal Outcome Test-22 (SNOT-22) scores to evaluate the surgical outcome. An effective surgical outcome was defined as a SNOT-22 score change ≥ 9 points after surgery. Multivariate logistic regression analysis was then used to establish a predictive model for the NSD treatment. The predictive quality and clinical utility of the predictive model were assessed by C-index, calibration plots, and decision curve analysis. Results The identified risk factors for inclusion in the predictive model were included. The model had a good predictive power, with a AUC of 0.920 in the training group and a C index of 0.911 in the overall sample. Decision curve analysis revealed that the prediction model had a good clinical applicability. Conclusions Our prediction model is efficient in predicting the efficacy of endoscopic surgery for NSD through evaluation of factors including: history of nasal surgery, preoperative SNOT-22 score, sinusitis, middle turbinate plasty, BMI, smoking, follow-up time, seasonal allergies, and advanced age. Therefore, it can be cost-effective for individualized preoperative assessment.
