鼻中隔偏曲并发慢性鼻窦炎风险预测模型的构建与验证

doi:10.6040/j.issn.1673-3770.0.2024.536

摘要/Abstract

摘要： 目的鼻中隔偏曲(nasal septal deviation, NSD)和慢性鼻窦炎(chronic rhinosinusitis, CRS)是耳鼻咽喉科常见的两种疾病,现有研究多聚焦于相关性分析,缺乏可指导临床决策的预测工具。为了开发兼具高精度与可解释性的预测工具,从而为个体化干预提供新的循证支持,本研究分析患者的临床资料和影像学资料,运用传统Logistic回归,构建风险预测模型并进行内部验证。方法纳入2022年10月1日至2024年6月1日确诊为NSD的310例患者临床资料。经过数据预处理,最终将285例患者按照7:3比例随机分为训练集(199例)和验证集(86例)。通过Logistic回归分析确定独立危险因素,根据结果建立列线图风险预测模型。使用受试者工作特征(receiver operating characteristic, ROC)曲线、校准曲线以及决策曲线分析(decision curve analysis, DCA)评估模型的性能。结果训练集ROC曲线下面积为0.760(95%CI:0.686~0.834),验证集ROC曲线下面积为0.800(95%CI:0.689~0.911),训练集和验证集校准曲线的平均绝对误差分别为0.017和0.015,临床决策曲线显示该模型有一定的临床适用性。结论年龄、过敏性鼻炎病史、偏曲程度、偏曲位置是NSD患者并发CRS的独立危险因素。基于这些因素建立的列线图预测模型可协助临床筛选NSD并发CRS的高危患者。

关键词: 鼻中隔偏曲, 慢性鼻窦炎, 列线图, 过敏性鼻炎

Abstract: Objective Nasal septal deviation(NSD)and chronic rhinosinusitis(CRS)are two common otolaryngology conditions. While existing research has primarily focused on analyzing their correlation, there is a lack of predictive tools to guide clinical decision-making. This study analyzed patients' clinical and imaging data to develop a highly accurate and interpretable predictive tool, and provide novel, evidence-based support for personalized interventions, Using traditional logistic regression, we constructed a risk prediction model and performed internal validation. Methods A total of 310 patients diagnosed with NSD between October 1,2022, and June 1,2024, were enrolled in the study, and their clinical data was collected. After preprocessing the data, 285 patients were included in the analysis and randomly assigned to a training set(199 cases, or 70%)and a validation set(86 cases, or 30%)in a 7∶3 ratio. Independent risk factors were identified through logistic regression analysis, and based on these results, a nomogram risk prediction model was constructed. The model's performance was then evaluated using a receiver operating characteristic(ROC)curve, a calibration plot(with bootstrapping), and a decision curve analysis(DCA). Results In the training set, the area under the ROC curve(AUC)was 0.760(95% confidence interval ［CI］): 0.686-0.834). In the validation set, the AUC was 0.800(95% CI: 0.689-0.911). The mean absolute error(MAE)for the calibration plots was 0.017 in the training set and 0.015 in the validation set. Decision curve analysis(DCA)showed that the model has potential clinical utility. Conclusion Age, history of allergic rhinitis, degree of septal deviation, and location of deviation were identified as independent risk factors for concurrent CRS in NSD patients. The nomogram prediction model developed, which is based on these factors, can be used to identify high-risk patients with NSD complicated by CRS in clinical practice.

Key words: Nasal septum deviation, Chronic sinusitis, Nomogram, Allergic rhinitis

中图分类号:

R765

杜康丽,郑振宇,徐战将,张宇,陈露,卢梦垚. 鼻中隔偏曲并发慢性鼻窦炎风险预测模型的构建与验证[J]. 山东大学耳鼻喉眼学报, 2025, 39(6): 78-86.

DU Kangli, ZHENG Zhenyu, XU Zhanjiang, ZHANG Yu, CHEN Lu, LU Mengyao. Construction and validation of risk prediction model for nasal septal deviation complicated with chronic sinusitis[J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2025, 39(6): 78-86.

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