Plotti Francesco, Capriglione Stella, Terranova Corrado, Montera Roberto, Scaletta Giuseppe, Lopez Salvatore, Luvero Daniela, Gianina Antonelli, Aloisi Alessia, Benedetti Panici Pierluigi, Angioli Roberto
Department of Obstetrics and Gynecology, University of Rome "Campus Bio-Medico", Via Alvaro del Portillo, 200, 00128, Rome, Italy.
Unit of Obstetrics and Gynecology, Magna Graecia University of Catanzaro, Catanzaro, Italy.
Med Oncol. 2017 May;34(5):82. doi: 10.1007/s12032-017-0945-y. Epub 2017 Apr 7.
The risk of endometrial malignancy (REM) score is a model formulated in a previous single-center validation study, which has been shown to predict endometrial cancer in women with ultrasound endometrial abnormalities based on multiple features (clinical, ultrasound and laboratorial). The purpose of this study was to validate the performance of REM score in an external validation setting. A population-based database with patients, who underwent elective hysteroscopy for ultrasound endometrial abnormalities between 2013 and 2016 at Department of Obstetrics and Gynecology of Campus Bio-medico of Rome, was used. Starting from January 2013 to June 2016, 330 patients were enrolled for hysteroscopy. Thirty-two patients were excluded due to Asherman syndrome or cervical stenosis. Therefore, a total of 298 patients were considered for the analysis. Based on pathologic examination, 102 patients were found to have endometrial cancer, and 196 had benign endometrial disease. Using the predefined cutoff of 0.3185, identified in the previous publication, in this independent cohort of patients we correctly classified 93/102 patients with endometrial cancer and 187/196 with benign disease, reporting an overall sensitivity and specificity of 93.9 and 95.4% (PPV = 0.91, NPV = 0.95), respectively. REM score showed a high positive predictive value for endometrial cancer prediction. However, before REM score can be applied in daily clinical practice, data from randomized controlled trials are needed.
子宫内膜恶性肿瘤（REM）评分是在先前的一项单中心验证研究中制定的模型，该模型已被证明可根据多种特征（临床、超声和实验室检查）预测超声检查发现子宫内膜异常的女性患子宫内膜癌的风险。本研究的目的是在外部验证环境中验证REM评分的性能。我们使用了一个基于人群的数据库，该数据库包含2013年至2016年期间在罗马生物医学大学校妇产科因超声检查发现子宫内膜异常而接受选择性宫腔镜检查的患者。从2013年1月至2016年6月，共有330例患者登记接受宫腔镜检查。由于阿谢曼综合征或宫颈狭窄，32例患者被排除在外。因此，共有298例患者纳入分析。根据病理检查，102例患者被诊断为子宫内膜癌，196例患有良性子宫内膜疾病。在这个独立的患者队列中，使用先前发表文章中确定的0.3185的预定义临界值，我们正确分类了93/102例子宫内膜癌患者和187/196例良性疾病患者，总体敏感性和特异性分别为93.9%和95.4%（阳性预测值=0.91，阴性预测值=0.95）。REM评分对子宫内膜癌预测显示出较高的阳性预测值。然而，在REM评分能够应用于日常临床实践之前，还需要来自随机对照试验的数据。
