Analysis on constructing a risk prediction model for premature ovarian function failure in patients with uterine fibroids complicated with hypertension after surgery based on decision tree method
10.3760/cma.j.cn.115807-20221107-00309
- VernacularTitle:基于决策树法构建子宫肌瘤合并高血压患者术后卵巢功能早衰的风险预测模型
- Author:
Dan WANG
1
;
Zijuan ZHANG
;
Huichun YANG
;
Meili LIANG
;
Lingzhi ZHENG
Author Information
1. 浙江省台州医院妇产科,台州 317000
- Keywords:
Uterine fibroids;
High blood pressure;
Premature ovarian failure;
Decision tree prediction model
- From:
Chinese Journal of Endocrine Surgery
2023;17(3):323-326
- CountryChina
- Language:Chinese
-
Abstract:
Objective:The decision tree Chi-square automatic interactive detection (CHAID) algorithm and binary Logistic regression analysis were used to construct the risk prediction model of premature ovarian failure (POF) in patients with uterine fibroids complicated with hypertension after surgery, and the results of the risk prediction model were compared and analyzed.Methods:Patients with uterine fibroids complicated with hypertension admitted to Taizhou Hospital of Zhejiang Province from Jan. 2019 to Sep. 2022 were retrospectively analyzed as the research objects. CHAID algorithm and Logistic regression analysis were used to establish risk prediction models, respectively. The area under the curve (AUC) of receiver operating characteristic curve (ROC) was used to compare and evaluate the prediction effects of the two models.Results:A total of 860 patients were collected, including 56 patients with premature ovarian function failure after operation, and the incidence of premature ovarian function failure was 6.51%. CHAID method and Logistic regression analysis showed that uterine myoma surgery, hypertension, smoking or passive smoking, family history of premature ovarian failure, sleep status, physical exercise and history of induced curettage were important influencing factors of premature ovarian failure. The accuracy of risk prediction of decision tree model was 88.2%, and the fitting effect of the model was good. The Logistic regression model Hosmer-Leme-show goodness of fit test showed that the model fit was good. The AUC of Logistic regression model was 0.893 (95% CI: 0.862-0.899), and the AUC of decision tree model was 0.882 (95% CI: 0.856-0.899). The predictive value of the two models was moderate, and there was no significant difference between them ( Z=0.254, P>0.05) . Conclusions:The combination of decision tree and Logistic regression model can find the influencing factors of premature ovarian function failure in patients with uterine fibroids complicated with hypertension after operation from different levels, and the relationship between the factors can be more fully understood. The establishment of a risk model for premature ovarian function failure in patients with uterine fibroids complicated with hypertension after surgery can provide a reference for postoperative intervention in patients with uterine fibroids complicated with hypertension, and more effectively help patients actively prevent and slow down the occurrence and development of POF.
