目的 通过收集绝经后出血（postmenopausal bleeding,PMB）患者的病史、危险因素以及子宫内膜超声影像学特征等临床数据,构建预测PMB患者子宫内膜恶性病变风险的模型。方法 选取2019年12月至2024年12月于浏阳市人民医院就诊的358例PMB患者为研究对象,根据病理检查结果分为病例组和对照组：将子宫内膜癌（endometrial cancer,EC）和子宫内膜非典型增生（atypical hyperplasia,AH）患者纳入病例组,其余患者纳入对照组。收集两组患者子宫内膜超声影像学特征及相关危险因素的临床数据,采用Logistic回归分析进行回顾性研究。结果 ①病例组与对照组在子宫内膜厚度、子宫内膜回声均匀性及子宫内膜血流分级（0级、I级、II级、III级）方面差异均有统计学意义;②两组患者在子宫内膜恶性病变高危因素（年龄、绝经年龄、子宫内膜厚度、反复阴道流血、肥胖、合并糖尿病、合并高血压及CA125水平）的比较中,差异均有统计学意义;③对高危因素进行Logistic回归分析显示,反复阴道流血、肥胖、糖尿病、超声显示子宫内膜增厚、内膜回声不均匀以及CA125>21 U/mL均为子宫内膜恶变的独立危险因素;④基于Logistic回归分析筛选子宫内膜恶性病变的最佳预测因子,构建“FBDNTC”（Frequency of bleeding,Body mass index,Diabetes,Non-uniform echogenicity & Thickness,CA125）预测模型。FBDNTC评分范围为0~21分,当评分≥8分（约登指数最大）时,预测子宫内膜恶性病变的灵敏度为84.7%,特异度为74.6%,受试者工作特征曲线下面积（area under the curve,AUC）为0.881（95%CI：0.845~0.917）。结论 结合PMB患者临床信息与超声影像学特征构建的风险预测模型FBDNTC,可有效辅助临床医生预测子宫内膜恶性病变风险,有助于临床分流及优化诊疗策略。
Abstract
Objective By collecting clinical data such as postmenopausal bleeding (PMB) patients, risk factors, and endometrial ultrasound imaging characteristics, a model that predicts the risk of endometrial malignant lesions in women with PMB was constructed. Methods A total of 358 PMB patients treated at Liuyang People's Hospital from December 2019 to December 2024 were enrolled. Based on pathological results, patients with endometrial cancer (EC) and atypical hyperplasia (AH) were assigned to the case group, while others formed the control group. Clinical data on endometrial ultrasound imaging features and risk factors were collected, and a logistic regression analysis was performed retrospectively. Results (1) Statistically significant differences were observed between groups in endometrial thickness, echo uniformity, and blood flow grading (grade 0, grade I, grade II, grade III); (2) Significant differences were found in high-risk factors for endometrial malignancy, including age, menopause age, endometrial thickness, recurrent vaginal bleeding, obesity, diabetes, hypertension, and CA125 levels; (3) Logistic regression identified recurrent vaginal bleeding, obesity, diabetes, endometrial thickening, non-uniform echogenicity, and CA125>21U/mL as independent risk factors; (4) The “FBDNTC” prediction model (Frequency of bleeding, Body mass index, Diabetes, Non-uniform echogenicity & Thickness, CA125) was established, with scores ranging from 0 to 21. At a cutoff of ≥8 points (maximizing Youden index), sensitivity was 84.7%, specificity 74.6%, and AUC 0.881(95%CI: 0.845-0.917). Conclusion The FBDNTC risk prediction model integrates clinical and ultrasound features to effectively assist clinicians in stratifying endometrial malignancy risk, optimizing 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
Key words
postmenopausal bleeding /
endometrial cancer /
endometrial atypical hyperplasia /
risk factors /
prediction model
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参考文献
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基金
国家自然科学基金面上项目“APBB1调控人类原细胞增殖与自我更新的作用机制”（82201771）; 湖南省卫生健康委员会项目“甲硝唑栓与阴道益生菌疗法在宫颈病变锥切术后应用价值的临床研究”（202105012209）
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