Purpose: It is often difficult to distinguish a benign endometrial disease from a malignancy and tools to help the physician are needed to triage patients into high and low risk of endometrial cancer. The purpose of this study was to obtain a predictive model to assess the risk of endometrial malignancy (REM) in women with ultrasound endometrial abnormalities.
Experimental design: Women, between ages 45 to 80 years, diagnosed through ultrasound with endometrial abnormalities and scheduled to have surgery were enrolled on a prospective study at the Department of Gynaecologic Oncology of Campus Bio-Medico, University of Rome. Preoperative clinical, ultrasound and laboratory characteristics were taken into account. Logistic regression algorithm was used to categorize patients into low- and high-risk groups for endometrial cancer.
Results: A total of 675 patients were considered for the analysis: 88 with endometrial cancer and 587 with benign endometrial disease. We divided the patients into two groups: training set (TS) and verification set (VS). Preoperative age, symptom, HE4 levels, and ultrasound endometrial thickness were found statistically significant, and were included into a multivariate logistic regression model to determine the probability to have endometrial cancer. In the TS, REM reported 93.3% sensitivity and 97.1% specificity [positive predictive value (PPV), 0.83; negative predictive value (NPV), 0.98; AUC, 0.957; 95% confidence interval (CI), 0.908-0.984]. In the VS, REM reported 89.3% sensitivity and 95.4% specificity (PPV, 0.73; NPV, 0.98; AUC, 0.919; 95% CI, 0.829-0.970).
Conclusions: Our data support the use of REM to triage patients into low- and high-risk groups for endometrial cancer, even if an external validation of the model is needed.
©2013 AACR.