Risk factors and prediction model construction of olfactory dysfunction in female patients with primary Sj?gren′s syndrome
10.3760/cma.j.cn141217-20230206-00033
- VernacularTitle:女性原发性干燥综合征患者嗅觉障碍危险因素及预测模型构建
- Author:
Xiaobing YANG
1
;
Hui CAI
;
Xiaoqin LONG
Author Information
1. 湖州市第三人民医院风湿免疫科，湖州 313000
- Keywords:
Sj?gren′s syndrome, primary;
Female;
Olfactory dysfunction;
Risk factors;
Clinical prediction model
- From:
Chinese Journal of Rheumatology
2024;28(11):808-812
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the risk factors of olfactory dysfunction (OD) of female patients with primary Sj?gren′s syndrome (pSS) and a prediction model was constructed.Methods:A total of 252 female pSS patients in the Third Municipal Hospital of Huzhou, from January 2021 to 2023 were recruited. According to the olfactory function,they were divided into OD group (144 cases) and without OD group (108 cases).The independent risk factors of OD were evaluated and the clinical prediction efficiency of the model was analyzed by receiver operating characteristic (ROC) curve, Hosmer-Lemeshow goodness-of-fit test and the decision curve analysis (DCA) curve.Results:The rate of OD was 57.1%((144/252)) in female pSS patients. Hyposmia was the main olfactory disorder in OD group (140/144, 97.2%). Univariate analysis showed that there were significant differences between OD and without OD groups, including disease course ( t=-2.05, P=0.040), RF( t=2.90, P=0.004), IgG( t=4.41, P=0.001), C3( t=5.47, P=0.001), ESSPRI( t=2.55, P=0.011), ESSDAI( t=3.80, P=0.001), HAMD ( t=3.38, P=0.001). Logistic regression analysis showed that high serum RF, IgG and low complement 3, high scores of ESSDAI and HAMD high scores were independent risk factors for pSS patients with OD patients[ OR(95% CI)=1.01(1.01, 1.03), 1.21(1.06, 1.38), 0.98(0.96, 0.89), 1.52 (1.20, 1.92), 1.13(1.03, 1.23)] ( P value were 0.016, 0.005, 0.004, <0.001 and 0.007 respectively). Based on the above independent risk factors, we constructed the prediction model nomogram and performed the internal data validation. The ROC curve AUC (95% CI) of the modeling group was 0.83(0.77, 0.89) and validation group was 0.69(0.57, 0.82), the prediction model was well differentiated.Hosmer-Lemeshow goodness-of-fit test showed that the prediction model had good calibration ability ( P=0.083), and the DCA curve display model is clinically valuable. Conclusion:The clinical prediction model developed in this study can be used to assess the risk of pSS-OD development, which is helpful for early detection and timely interention so can improve the quality of life of pSS-OD patients in turn.
