Abstract：
UNASSIGNED: This study aimed to evaluate characteristics of endometrial surveillance in women treated for breast cancer to build a clinical prediction model.
UNASSIGNED: A multicentric retrospective cohort study was conducted at two tertiary-care university hospitals from January 2020 to June 2023. Perimenopausal and postmenopausal women treated for breast cancer were categorized into two groups: patients with and without diagnosis of endometrial malignancy (endometrial carcinoma) or premalignancy (atypical endometrial hyperplasia). Characteristics of breast cancer and ultrasonographic and hysteroscopic examinations were compared. A prediction model for endometrial malignancy was built using logistic regression. Predictive accuracy was assessed using the receiver operating characteristic (ROC) curve and goodness of fit using the Hosmer-Lemeshow test.
UNASSIGNED: One hundred and thirty-two (28 with premalignancy or malignancy and 104 without malignancy) women were analyzed. A nomogram was produced for prediction model development utilizing the presence and duration in months of abnormal uterine (BL)eeding, ultrasound (US) vascular pattern and echogenicity and (H)ysteroscopic appearance of endometrium (BLUSH) as determined by logistic regression. Sensitivity and specificity were 79.17% and 95.19%, respectively, with an area under ROC curve of 0.965, indicating good accuracy. Good goodness of fit and prediction stability were indicated by the calibration curve and Hosmer-Lemeshow test (χ2 = 26.36; p = 0.999).
UNASSIGNED: Breast cancer survivors undergoing endometrial surveillance might benefit from a potentially useful prediction model based on hysteroscopic appearance, ultrasonographic uniformity of endometrium, Doppler flow and presence of abnormal uterine bleeding.
UNASSIGNED: A multicentric retrospective cohort study was conducted at two tertiary-care university hospitals from January 2020 to June 2023. Perimenopausal and postmenopausal women treated for breast cancer were categorized into two groups: patients with and without diagnosis of endometrial malignancy (endometrial carcinoma) or premalignancy (atypical endometrial hyperplasia). Characteristics of breast cancer and ultrasonographic and hysteroscopic examinations were compared. A prediction model for endometrial malignancy was built using logistic regression. Predictive accuracy was assessed using the receiver operating characteristic (ROC) curve and goodness of fit using the Hosmer-Lemeshow test.
UNASSIGNED: One hundred and thirty-two (28 with premalignancy or malignancy and 104 without malignancy) women were analyzed. A nomogram was produced for prediction model development utilizing the presence and duration in months of abnormal uterine (BL)eeding, ultrasound (US) vascular pattern and echogenicity and (H)ysteroscopic appearance of endometrium (BLUSH) as determined by logistic regression. Sensitivity and specificity were 79.17% and 95.19%, respectively, with an area under ROC curve of 0.965, indicating good accuracy. Good goodness of fit and prediction stability were indicated by the calibration curve and Hosmer-Lemeshow test (χ2 = 26.36; p = 0.999).
UNASSIGNED: Breast cancer survivors undergoing endometrial surveillance might benefit from a potentially useful prediction model based on hysteroscopic appearance, ultrasonographic uniformity of endometrium, Doppler flow and presence of abnormal uterine bleeding.
摘要：
■本研究旨在评估接受乳腺癌治疗的女性子宫内膜监测的特征，以建立临床预测模型。
■于2020年1月至2023年6月在两家三级护理大学医院进行了一项多中心回顾性队列研究。围绝经期和绝经后接受乳腺癌治疗的妇女分为两组：有和没有诊断为子宫内膜恶性肿瘤（子宫内膜癌）或癌前病变（非典型子宫内膜增生）的患者。比较乳腺癌的特征以及超声和宫腔镜检查。采用logistic回归建立子宫内膜恶性程度预测模型。使用受试者工作特征（ROC）曲线评估预测准确性，并使用Hosmer-Lemeshow检验评估拟合优度。
■分析了一百三十二名（28例有癌前或恶性肿瘤，104例无恶性肿瘤）妇女。利用异常子宫（BL）喂养的存在和持续时间，制作了用于预测模型开发的列线图，超声（US）血管模式和回声和（H）子宫内膜（BLUSH）通过逻辑回归确定的宫腔镜外观。敏感性和特异性分别为79.17%和95.19%,分别,ROC曲线下面积为0.965，表明准确性好。校准曲线和Hosmer-Lemeshow检验表明良好的拟合优度和预测稳定性（χ2=26.36；p=0.999）。
接受子宫内膜监测的乳腺癌幸存者可能受益于基于宫腔镜外观的潜在有用预测模型，子宫内膜的超声检查均匀性，多普勒血流和异常子宫出血的存在。
■于2020年1月至2023年6月在两家三级护理大学医院进行了一项多中心回顾性队列研究。围绝经期和绝经后接受乳腺癌治疗的妇女分为两组：有和没有诊断为子宫内膜恶性肿瘤（子宫内膜癌）或癌前病变（非典型子宫内膜增生）的患者。比较乳腺癌的特征以及超声和宫腔镜检查。采用logistic回归建立子宫内膜恶性程度预测模型。使用受试者工作特征（ROC）曲线评估预测准确性，并使用Hosmer-Lemeshow检验评估拟合优度。
■分析了一百三十二名（28例有癌前或恶性肿瘤，104例无恶性肿瘤）妇女。利用异常子宫（BL）喂养的存在和持续时间，制作了用于预测模型开发的列线图，超声（US）血管模式和回声和（H）子宫内膜（BLUSH）通过逻辑回归确定的宫腔镜外观。敏感性和特异性分别为79.17%和95.19%,分别,ROC曲线下面积为0.965，表明准确性好。校准曲线和Hosmer-Lemeshow检验表明良好的拟合优度和预测稳定性（χ2=26.36；p=0.999）。
接受子宫内膜监测的乳腺癌幸存者可能受益于基于宫腔镜外观的潜在有用预测模型，子宫内膜的超声检查均匀性，多普勒血流和异常子宫出血的存在。
