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

作　　者：王婧[1] 周巧云[1] 王牧雨 肖豫[1] 宋冬梅[1] 郭艳[1] 夏恩兰[1] 李天照 黄晓武[1] Wang Jing;Zhou Qiaoyun;Wang Muyu;Xiao Yu;Song Dongmei;Guo Yan;Xia Enlan;Li Tinchiu;Huang Xiaowu(Hysteroscopy Center,Department of Obstetric and Gynecological,Fuxing Hospital,Capital Medical University,Beijing 100038,China;School of Biomedical Engineering,Capital Medical University,Beijing 100069,China;Union Hospital Reproductive Medicine Centre,Hong Kong 999077,China)

机构地区：[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,中国香港999077

出　　处：《首都医科大学学报》2025年第1期143-149,共7页Journal of Capital Medical University

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。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.

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 

分 类 号：R737.33[医药卫生—肿瘤] R711.74[医药卫生—临床医学]