绝经后出血子宫内膜癌危险因素分析及预测模型的建立

doi:10.3969/j.issn.1006-7795.2025.01.022

首都医科大学学报 ›› 2025, Vol. 46 ›› Issue (1): 143-149.doi: 10.3969/j.issn.1006-7795.2025.01.022

绝经后出血子宫内膜癌危险因素分析及预测模型的建立

王婧¹，周巧云 ¹，王牧雨²，肖豫¹，宋冬梅¹，郭艳¹，夏恩兰 ¹，李天照³，黄晓武^1*

1. 首都医科大学附属复兴医院宫腔镜中心，北京 100038；2. 首都医科大学生物医学工程学院，北京 100069；3. 仁安医院生殖医学中心，香港 999077

收稿日期:2024-04-08 出版日期:2025-02-21 发布日期:2025-02-25
通讯作者: 黄晓武 E-mail:hxiaowu_fxyy@126.com

Analysis of risk factors and establishment of a prediction model for endometrial cancer in postmenopausal bleeding

Wang Jing¹, Zhou Qiaoyun¹, Wang Muyu², Xiao Yu¹, Song Dongmei¹, Guo Yan¹, Xia Enlan¹, Li Tinchiu³, Huang Xiaowu^1*

1.Hysteroscopy Center, Department of Obstetric and Gynecological, Fuxing Hospital, Capital Medical University, Beijing 100038, China; 2. School of Biomedical Engineering, Capital Medical University, Beijing 100069, China; 3. Union Hospital Reproductive Medicine Centre, Hong Kong 999077, China

Received:2024-04-08 Online:2025-02-21 Published:2025-02-25

摘要/Abstract

摘要： 目的通过收集绝经后出血（postmenopausal bleeding，PMB）患者常规病史、危险因素和超声结果的临床数据，建立一种预测PMB妇女罹患子宫内膜癌（endometrial cancer，EC）及子宫内膜非典型增生（atypical hyperplasia, AH）风险的方法。方法连续性收集2013年12月至2023年12月就诊于首都医科大学附属复兴医院的408例PMB患者的病例资料。分为病例组和对照组，将EC和AH患者纳入恶性组（病例组），其余患者纳入非恶性组（对照组），收集有关子宫内膜恶性病变危险因素的临床数据，通过单因素和多因素Logistic回归分析进行回顾性研究。结果 408例患者平均年龄（60.4±7.8）岁，病例组74例(18.1%)，对照组334例（81.9%）。基于Logistic回归分析选择子宫内膜恶性病变的最佳预测因子，创建“LRDNT”（light bleeding, recurrent bleeding, diabetes, non-uniform echogenicity & thickness）模型。LRDNT分数在0至22之间。LRDNT评分≥15约登指数最大，预测恶性病变的灵敏度为79.73%，特异度为80.84%，预测准确率为80.64%。结论 PMB患者的临床信息与超声指标相结合的风险预测模型LRDNT，可帮助临床医生预测子宫内膜恶性病变发生的风险，有助于临床分流和优化诊疗策略。

关键词: 绝经后出血, 子宫内膜癌, 子宫内膜非典型增生, 危险因素, 预测模型

Abstract: Objective To establish a method for predicting the risk of endometrial cancer (EC) and endometrial atypical hyperplasia (AH) in women with postmenopausal bleeding (PMB) by collecting clinical data on routine medical history. Methods The clinical data of a total of 408 PMB patients admitted to Fuxing Hospital, Capital Medical University were consecutively collected in this retrospective study from December 2013 to December 2023. According to the results of endometrial pathology, patients were divided into case group and control group. EC and AH were included in the malignant group (case group) and the other endometrial pathologies were included in the non-malignant group (control group). Clinical data, including clinical history, high risk factors, and common gynecological ultrasound measurement indicators, were collected and studied by univariate and multivariate Logistic regression analysis. Results The mean age of 408 patients was (60.4±7.8) years. A total of 74 cases (18.1%) were in case group and 334 cases (81.9%) were in control group. Based on Logistic regression analysis, the best predictors of endometrial malignant lesions were selected to create a “LRDNT” (light bleeding, recurrent bleeding, diabetes, non-uniform echogenicity & thickness) model. LRDNT scores range from 0 to 22. The score of LRDNT ≥15 has the largest Yoden index, and the sensitivity to predict endometrial malignant lesions is 79.73%, the specificity is 80.84%, and the prediction accuracy is 80.64%. Conclusions The risk prediction model LRDNT, which combines clinical information and common gynecological ultrasound measurement indicators of PMB patients, can help clinicians classify patients at high and low risk of endometrial malignant lesions, and optimize the strategy of diagnosis and treatment.

Key words: postmenopausal bleeding, endometrial cancer, endometrial atypical hyperplasia, risk factors, prediction model

中图分类号:

王婧, 周巧云, 王牧雨, 肖豫, 宋冬梅, 郭艳, 夏恩兰, 李天照, 黄晓武. 绝经后出血子宫内膜癌危险因素分析及预测模型的建立[J]. 首都医科大学学报, 2025, 46(1): 143-149.

Wang Jing, Zhou Qiaoyun, Wang Muyu, Xiao Yu, Song Dongmei, Guo Yan, Xia Enlan, Li Tinchiu, Huang Xiaowu. Analysis of risk factors and establishment of a prediction model for endometrial cancer in postmenopausal bleeding[J]. Journal of Capital Medical University, 2025, 46(1): 143-149.

参考文献

［1］ Salinas-Vera Y M, Gallardo-Rincón D, Ruíz-García E, et al. The role of hypoxia in endometrial cancer［J］. Curr Pharm Biotechnol, 2022, 23(2): 221－234.
［2］中华人民共和国国家卫生健康委员会. 子宫内膜癌诊疗指南（2022年版）［EB/OL］. (2022-04－11)［2023-11-12］. http://www.nhc.gov.cn/yzygj/s2911/202204/a0e67177df1f439898683e1333957c74/files/22a422760c924a91bf07faf1e66ad7de.pdf
［3］郝建珍, 张淞文, 王涛,等. 北京地区子宫内膜癌发病相关因素的探讨［J］. 中华肿瘤防治杂志, 2009, 16(11): 805－809.
［4］ Clarke M A, Long B J, Del Mar Morillo A, et al. Association of endometrial cancer risk with postmenopausal bleeding in women: a systematic review and meta-analysis［J］. JAMA Intern Med, 2018, 178(9): 1210－1222.
［5］ Wong A S W, Cheung C W, Fung L W Y, et al. Development and validation of prediction models for endometrial cancer in postmenopausal bleeding［J］. Eur J Obstet Gynecol Reprod Biol, 2016, 203: 220－224.
［6］ Giannella L, Mfuta K, Setti T, et al. A risk-scoring model for the prediction of endometrial cancer among symptomatic postmenopausal women with endometrial thickness > 4 mm［J］. Biomed Res Int, 2014, 2014: 130569.
［7］ Burbos N, Musonda P, Giarenis I, et al. Predicting the risk of endometrial cancer in postmenopausal women presenting with vaginal bleeding: the Norwich DEFAB risk assessment tool［J］. Br J Cancer, 2010, 102(8): 1201－1206.
［8］ Burbos N, Musonda P, Duncan T J, et al. Estimating the risk of endometrial cancer in symptomatic postmenopausal women: a novel clinical prediction model based on patients' characteristics［J］. Int J Gynecol Cancer, 2011, 21(3): 500－506.
［9］ Musonda P, Burbos N, Duncan T J, et al. Comparing the performance of two clinical models in estimating the risk of endometrial cancer in symptomatic postmenopausal women［J］. Eur J Obstet Gynecol Reprod Biol, 2011, 159(2): 433－438.
［10］ Shen Y F, Li L, Wang H L, et al. Triage method for endometrial biopsy in postmenopausal women: a multicenter retrospective cohort study［J］. Menopause, 2023, 30(12): 1206－1212.
［11］ Dueholm M, Hjorth I M D, Dahl K, et al. Identification of endometrial cancers and atypical hyperplasia: development and validation of a simplified system for ultrasound scoring of endometrial pattern［J］. Maturitas, 2019, 123: 15－24.
［12］王丽, 毛文军, 白娥, 等. 绝经后出血的高危因素及预测子宫内膜病变模型的建立［J］. 实用妇产科杂志, 2022, 38(9): 679－684.
［13］王晓萍, 王明波, 佘昊清, 等. 绝经后子宫异常出血患者发生子宫内膜癌的危险因素及风险预测［J］. 中国性科学, 2022, 31(3): 89－93.
［14］中华医学会妇产科学分会绝经学组. 中国绝经管理与绝经激素治疗指南2023版［J］. 中华妇产科杂志, 2023, 58(1): 4－21.
［15］ Leone F P G, Timmerman D, Bourne T, et al. Terms, definitions and measurements to describe the sonographic features of the endometrium and intrauterine lesions: a consensus opinion from the International Endometrial Tumor Analysis (IETA) group［J］. Ultrasound Obstet Gynecol, 2010, 35(1): 103－112.
［16］ Committee on Clinical Consensus-Gynecology. Management of endometrial intraepithelial neoplasia or atypical endometrial hyperplasia: ACOG clinical consensus no. 5［J］. Obstet Gynecol, 2023, 142(3): 735－744.
［17］王立淑, 于腾飞, 杨保军, 等. 老年女性子宫内膜良恶性病变超声特征分析及诊断模型预测［J］. 中华老年医学杂志, 2022, 41(7): 822－826.
［18］ ACOG Committee Opinion. The role of transvaginal ultrasonography in evaluating the endometrium of women with postmenopausal bleeding［EB/OL］.［2023-01-02］.https://www.acog.org/clinical/clinical-guidance/committee-opinion/articles/2018/05/the-role-of-transvaginal-ultrasonography-in-evaluating-the-endometrium-of-women-with-postmenopausal-bleeding.
［19］周韩, 盛德乔. 糖尿病与肿瘤关系的研究进展［J］. 肿瘤防治研究, 2022, 49(11): 1107－1111.

绝经后出血子宫内膜癌危险因素分析及预测模型的建立

Analysis of risk factors and establishment of a prediction model for endometrial cancer in postmenopausal bleeding

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价