Development and validation of a nomogram prediction model for allergic rhinitis based on metabolic indicators
10.3760/cma.j.cn431274-20250311-00335
- VernacularTitle:基于代谢指标的变应性鼻炎列线图预测模型的构建和验证
- Author:
Xiangying MENG
1
;
Yi WANG
;
Qian ZHAO
;
Jing ZHOU
Author Information
1. 上海市徐汇区大华医院内分泌科，上海 200237
- Publication Type:Journal Article
- Keywords:
Rhinitis, allergic;
Metabolic syndrome;
Metabolic indicators;
Predictive model
- From:
Journal of Chinese Physician
2025;27(10):1527-1532
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the characteristics of metabolic indicators in patients with allergic rhinitis (AR) and the potential relationship between AR and metabolic syndrome (MetS).Methods:A total of 179 patients with MetS admitted to the Dahua Hospital in Xuhui District, Shanghai, from June 2021 to May 2024 were retrospectively included. They were divided into an AR group (69 cases) and a non-AR group (110 cases) based on the presence of AR. Clinical data including demographic information, metabolic indicators, and immunological test results were collected. Multivariate logistic regression analysis was used to identify clinical risk factors associated with MetS complicated with AR, and a nomogram prediction model was constructed. The model′s discriminative ability, calibration, and clinical predictive performance were evaluated using receiver operating characteristic (ROC) curves, consistency index (C-index), and decision curve analysis.Results:The AR group had a significantly higher proportion of males, fasting C-peptide levels, total cholesterol, low-density lipoprotein cholesterol, CD4/CD8 ratio, immunoglobulin M, immunoglobulin E, CD3 cell count, CD4 cell count, and interleukin-6 levels compared to the non-AR group, while hip circumference was significantly lower (all P<0.05). Logistic regression analysis showed that male sex ( OR=2.156, P=0.042), total cholesterol ( OR=1.504, P=0.003), fasting C-peptide ( OR=3.342, P=0.016), CD4 cell count ( OR=1.002, P=0.011), and interleukin-6 ( OR=1.124, P=0.002) were risk factors for AR in MetS patients, while hip circumference ( OR=0.956, P=0.026) was a protective factor. The area under the ROC curve of the nomogram model was 0.771(95% CI: 0.698-0.841), and the C-index was 0.769(95% CI: 0.732-0.806), indicating good predictive ability and consistency of the model. Conclusions:The occurrence of AR is closely associated with multiple metabolic indicators, suggesting that AR may not only be a local inflammatory condition but also involve systemic metabolic abnormalities. The nomogram model based on these risk factors can be used for individualized risk assessment and early intervention.
