Risk Assessment of Endometrial Hyperplasia and Endometrial Cancer

• Conditions: Endometrial Cancer

• Registration Number: NCT04995731
• Lead Sponsor: Assiut University

Brief Summary

Abnormal uterine bleeding (AUB) represents common diagnostic challenge in everyday gynecological practice. However, abnormal bleeding is a common symptom of many benign diseases and only indicates the presence of EC in 9% of postmenopausal women and 1% to 2% of premenopausal women, suggesting that many women at low risk undergo unnecessary invasive procedures to rule out cancer. The aim of the study is to create a risk-scoring model of endometrial hyperplasia and endometrial cancer.

Detailed Description

Approximately 90% of endometrial cancer (EC) cases are preceded by AUB in premenopausal or perimenopausal women or post-menopausal bleeding (PMB).Transvaginal ultrasonography(TVS) has become the first step diagnostic tool of AUB. The main advantage of ultrasound imaging is that it has high accuracy for the preoperative classification of intra and extra uterine lesions, both benign and malignant. If increased endometrial thickness (ET) is found in women with PMB, the risk of EC increases. However, in women with type II EC, ET below 3-4 mm might also be found. Because of these limitations, ET should not be the only factor for cancer risk estimation in women with AUB.

Three-dimensional sonography and blood flow vascular indices improve the diagnostic precision of the sonographic estimation of endometrial lesions. Several scoring systems using different ultrasound image characteristics were proposed to estimate the risk of EC in women with AUB including the recently proposed system" Risk of Endometrial Cancer scoring model "(REC).

Existing guidelines recommend considering clinical risk factors such as BMI, age, obesity, type II diabetes, polycystic ovary syndrome(PCOS) and use of unopposed estrogen when evaluating AUB. However, only few clinical risk prediction models have been developed.

Despite the important role of ultrasound imaging in assessment of endometrial lesions, one wonders if clinical variables can improve the diagnostic performance of risk prediction models.

The aim of the study is to create a risk-scoring model of endometrial hyperplasia and endometrial cancer using patient clinical characteristics and ultrasound image characteristics among women with abnormal uterine bleeding, and to validate the diagnostic performance of our model and to compare it's predictive value with the recently proposed REC score for EC risk stratification.

Study Timeline

• Study First Submitted: 2021-07-30
• Study First Submitted QC: 2021-07-30
• Study First Posted: 2021-08-09
• Study Start: 2021-09-01
• Status Verified: 2022-08
• Last Update Submitted: 2022-08-01
• Last Update Posted: 2022-08-03
• Primary Completion: 2023-07
• Study Completion: 2024-07

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: Female
• Target Recruitment: 328

Inclusion Criteria

women ≥40 years with pre- or perimenopausal AUB or PMB presenting to Women's Health Hospital, Department of Obstetrics and Gynecology, Faculty of medicine, Assiut University, Assiut, Egypt.

Exclusion Criteria

• Women with a vaginal bleeding arising from a cervical, vaginal or vulvar disease.
• Patients with cervical cancer or uterine metastases.
• History of prior hysterectomy, prior pelvic radiation, endometrial sampling within the past 3 months.
• Presence of existing pregnancy.
• Women with inadequate endometrial sampling or with no histopathological diagnosis.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
prevalence of endometrial cancer, endometrial hyperplasia	3 years	Magnitude and prevalence of endometrial cancer, endometrial hyperplasia using a practical clinical-ultrasound based scoring system.

Secondary Outcome Measures

Name	Time	Method
prevalence of endometrial benign lesions	3 years	calculate absolute risks (prevalent risk) of endometrial benign lesions.

Trial Locations

Locations (1)

Assiut University; 🇪🇬 Assiut, Egypt