| 张 赫,孔为民.代谢因素与子宫内膜不典型增生及子宫内膜癌的相关性列线图模型[J].肿瘤学杂志,2021,27(7):566-571. |
| 代谢因素与子宫内膜不典型增生及子宫内膜癌的相关性列线图模型 |
| Establishment of A Nomogram Model for Predicting Risk of Endometrial Malignant Hyperplasia Based on Analysis of Metabolic Factors of Patients |
| 投稿时间：2020-12-30 |
| DOI：10.11735/j.issn.1671-170X.2021.07.B010 |
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| 中文关键词: 子宫内膜癌 子宫内膜不典型增生 代谢综合征 Nomogram模型 |
| 英文关键词:endometrial cancer endometrial atypical hyperplasia metabolic factors nomogram model |
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| 中文摘要: |
| 摘 要：［目的］ 探讨代谢因素与子宫内膜不典型增生及子宫内膜癌的相关性，并建立列线图（Nomogram）预测子宫内膜恶性增生的发病风险。［方法］ 收集2010年1月1日至2015年12月31日首都医科大学附属北京妇产医院妇瘤科收治的子宫内膜不典型增生102例及子宫内膜癌103例共205例患者为病例组，选取同期子宫内膜单纯性增生或息肉样增生患者104例作为对照组。检索两组患者临床资料中血压、血糖、甘油三酯、高密度脂蛋白等代谢因素的实验室结果。采用Logistic回归模型确定与子宫内膜恶性增生相关的危险因素，并建立子宫内膜恶性增生相关危险因素的列线图模型。采用C指数、Calibration校准曲线、决策曲线（decision curve analysis，DCA）、受试者工作特征曲线和内部校准验证分析评估预测模型的临床有效性。［结果］ 列线图模型中包含的预测因子包括年龄、高血压、糖尿病、体质指数、尿酸和高血脂。该模型的C指数为0.772(95%CI：0.717~0.827)，分辨力良好，校准效果良好。对模型进行自举法验证（Bootstrapping）后C指数仍可达到较高的0.752。决策曲线分析显示，当阈值概率在36%~91%时，使用此列线图模型预测患者的发病风险以及干预治疗是有意义的。［结论］ 子宫内膜恶性增生的发生发展与代谢因素明显相关。年龄、体质指数、高尿酸血症、高脂血症为子宫内膜恶性增生的主要危险因素。本研究建立的以体格检查和实验室检测为基础的列线图模型可作为有代谢相关高危因素的女性人群预测子宫内膜恶性增生发病风险和筛查危险因素的快速方法。 |
| 英文摘要: |
| Abstract： ［Objective］ To investigate the association of metabolic factors with endometrial atypical hyperplasia and endometrial cancer， and to develop a nomogram model to predict the risk of developing endometrial cancer. ［Methods］ A total of 205 patients， including 102 cases of endometrial atypical hyperplasia and 103 cases of endometrial carcinoma admitted in Beijing Obstetrics and Gynecology Hospital from January 2010 to December 2015 were enrolled in the study；and 104 patients with simple endometrial hyperplasia or polypoid hyperplasia during the same period were selected as the control group. The blood pressure， blood glucose， triglycerides， and high-density lipoprotein were retrieved from the clinical data of patients. Multivariate Logistic regression analysis was used to determine the risk factors associated with endometrial malignant hyperplasia and a nomogram prediction model of risk factors associated with endometrial malignant hyperplasia was developed. Discrimination， calibration， and clinical usefulness of the predicting model were assessed using the C-index， calibration plot， and decision curve analysis. Internal validation was assessed using the bootstrapping validation. ［Results］ The age， hypertension， diabetes， BMI， uric acid， and hyperlipidemia were included in the nomogram prediction model as predictors. The model had a C-index of 0.772(95%CI：0.717~0.827) with good discrimination and good calibration. A high C-index value of 0.752 was reached in the interval validation. Decision curve analysis showed that it was meaningful to use this nomogram for patient interventions when the threshold probability was within 36%~91%. ［Conclusion］ The development of endometrial malignant hyperplasia is significantly associated with metabolic factors. Age>50， BMI≥25 kg/m2， hyperuricemia， and hyperlipidemia are the main risk factors for the development of endometrial malignant hyperplasia. The nomogram prediction model based on physical examination and laboratory testing developed in this study can be used for predicting the risk of endometrial malignancy and screening in women with metabolism-related high-risk factors. |
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