Comparison of Three Clinical Models for Estimating the Risk of Endometrial Cancer in Post-Menopausal Women With Abnormal Vaginal Bleeding Publisher



Yazdani S^{1, 2} ; Javadian M² ; Sayarifard E³ ; Bouzari Z^{2, 4} ; Mohammadnetaj M⁵ ; Sayarifard A⁶
Source: International Journal of Cancer Management Published:2018

Abstract

Background: Given the prevalence of abnormal post-menopausal bleeding and the importance of its early examination for ensuring the timely diagnosis of any malignancies, the present study was conducted to investigate uterine pathologies in relation to post-menopausal bleeding patterns and endometrial thickness as observed in transvaginal ultrasounds and to offer models for predicting endometrial cancer. Methods: The present descriptive-analytical cross sectional study was conducted on 112 post-menopausal women presenting to Ayatollah Rouhani Hospital in Babol, Iran. The patients underwent a transvaginal ultrasound and hysteroscopy and their samples were sent for pathological examination. The logistic regression model and the receiver operating characteristic (ROC) curve were used. This study presents 3 models for predicting endometrial cancer, including AM30 [which considers the subject’s amount of bleeding, Menopause age and BMI (Body Mass Index) for assessing her risk of endometrial cancer], AMD30 (which additionally considers the subject’s history of diabetes) and AMDI30 (which additionally considers the subject’s history of internal diseases). Results: Menopause age, amount of bleeding, BMI, and history of internal diseases were significantly linked to endometrial cancer in post-menopausal women with abnormal bleeding; that is, the variables were higher in this group than in those without cancer (P = 0.007, P = 0.004, P = 0.001, and P = 0.02). The three models defined, i.e. AM30, AMD30, and AMI30 had a high area under the ROC curve and could predict endometrial cancer with a proper sensitivity and specificity in post-menopausal women with vaginal bleeding. There were no statistically significant differences among these models, although the AMI30 model had a higher area under the ROC curve compared to the other two models (P = 0.29). Conclusions: The present study recommends these three predictive models as alternatives for predicting endometrial cancer in post-menopausal women with vaginal bleeding. © 2018, Cancer Research Center (CRC), Shahid Beheshti University of Medical Sciences.