Stachowicz Norbert, Smoleń Agata, Ciebiera Michał, Łoziński Tomasz, Poziemski Paweł, Borowski Dariusz, Czekierdowski Artur
Chair and Department of Epidemiology and Clinical Research Methodology, Medical University of Lublin, 20-080 Lublin, Poland.
Center of Postgraduate Medical Education, Second Department of Obstetrics and Gynecology, 01-809 Warsaw, Poland.
Diagnostics (Basel). 2021 Mar 4;11(3):442. doi: 10.3390/diagnostics11030442.
Abnormal uterine bleeding (AUB) represents a common diagnostic challenge, as it might be related to both benign and malignant conditions. Endometrial cancer may not be detected with blind uterine cavity sampling by dilatation and curettage or suction devices. Several scoring systems using different ultrasound image characteristics were recently proposed to estimate the risk of endometrial cancer (EC) in women with AUB.
The aim of the present study was to externally validate the predictive value of the recently proposed scoring systems including the Risk of Endometrial Cancer scoring model (REC) for EC risk stratification.
It was a retrospective cohort study of women with postmenopausal bleeding. From June 2012 to June 2020 we studied a group of 394 women who underwent standard transvaginal ultrasound examination followed by power Doppler intrauterine vascularity assessment. Selected ultrasound features of endometrial lesions were assessed in each patient.
The median age was 60.3 years (range ± 10.7). The median body mass index (BMI) was 30.4 (range ± 6.0). Histological examination revealed 158 cases of endometrial hyperplasia (EH) and 236 cases of EC. Of the studied ultrasound endometrial features, the highest areas under the curve (AUCs) were found for endometrial thickness (ET) (AUC = 0.76; 95% CI: 0.71-0.81) and for interrupted endomyometrial junction (AUC = 0.70, 95% CI: 0.65-0.75). Selected scoring systems presented moderate to good predictive performance in differentiating EC and EH. The highest AUC was found for REC model (AUC = 0.75, 95% CI: 0.70-0.79) and for the basic model that included ET, Doppler score and interrupted endometrial junction (AUC = 0.77, 95% CI: 0.73-0.82). REC model was more accurate than other scoring systems and selected single features for differentiating benign hyperplasia from EC at early stages, regardless of menopausal status.
New scoring systems, including the REC model may be used in women with AUB for more efficient differentiation between benign and malignant conditions.
异常子宫出血(AUB)是一个常见的诊断难题,因为它可能与良性和恶性疾病相关。通过扩张刮宫术或抽吸装置进行盲目子宫腔采样可能无法检测出子宫内膜癌。最近提出了几种使用不同超声图像特征的评分系统,以评估AUB女性患子宫内膜癌(EC)的风险。
本研究的目的是对外验证最近提出的包括子宫内膜癌风险评分模型(REC)在内的评分系统对EC风险分层的预测价值。
这是一项对绝经后出血女性的回顾性队列研究。2012年6月至2020年6月,我们研究了一组394名女性,她们接受了标准经阴道超声检查,随后进行了能量多普勒子宫内血管评估。对每位患者评估子宫内膜病变的选定超声特征。
中位年龄为60.3岁(范围±10.7)。中位体重指数(BMI)为30.4(范围±6.0)。组织学检查发现158例子宫内膜增生(EH)和236例EC。在所研究的超声子宫内膜特征中,子宫内膜厚度(ET)的曲线下面积(AUC)最高(AUC = 0.76;95%CI:0.71 - 0.81),内膜肌层交界中断的AUC也较高(AUC = 0.70,95%CI:0.65 - 0.75)。选定的评分系统在区分EC和EH方面表现出中等至良好的预测性能。REC模型的AUC最高(AUC = 0.75,95%CI:0.70 - 0.79),包括ET、多普勒评分和内膜交界中断的基本模型的AUC也较高(AUC = 0.77,95%CI:0.73 - 0.82)。REC模型比其他评分系统更准确,并且无论绝经状态如何,在早期区分良性增生和EC时,选定的单一特征表现更佳。
包括REC模型在内的新评分系统可用于AUB女性,以更有效地区分良性和恶性疾病。