Implementing the Risk of Endometrial Malignancy Algorithm (REM) adding obesity as a predictive factor: Results of REM-B in a single-center survey

Abstract

ObjectiveIn 2013, our group assessed a risk stratification tool of endometrial cancer (EC), called REM (Risk of Endometrial Malignancy). A well known risk factor for EC is body mass index (BMI). In fact, (BMI > 30 and <35 kg/m2) and severe obesity (BMI > 35 kg/m2) were associated with a 2.6-fold and a 4.7-fold increase in EC risk, respectively. Therefore, in the present study we aim to improve the performance of REM, including BMI and developing a new scoring system, called REM-B (Risk of Endometrial Malignancy score associated to BMI), to classify patients into high risk or low risk groups for EC. Study designWomen, between 45 and 80 years, diagnosed with ultrasound endometrial abnormalities and scheduled to have surgery were enrolled on a prospective study at Department of Gynaecologic Oncology of Campus Bio-Medico of Rome. Preoperative clinical, ultrasound and laboratory features were taken into account. ResultsA total of 675 patients (88 with EC and 587 with benign endometrial disease) were divided in training set (TS) and verification set (VS). Age, symptom, BMI, HE4 levels and ultrasound endometrial thickness were found statistically significant and included into multivariate logistic regression model in order to determine the probability to have EC. REM-B showed an overall sensitivity of 94.7% (versus 92% of REM) and a specificity of 97.4% (versus 96% of REM). ConclusionsOur data support the use of REM-B to triage patients into low and high risk of EC, even if an external validation of model is needed.