ArticleYonsei medical journal2023
Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding.
Article in Yonsei medical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Application of artificial intelligence to ultrasound imaging for benign gynecological disorders: systematic review.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2025Pooled it
- Clinical treatment score post-5 years and survival benefit from extended endocrine therapy for breast cancer patients under and over 50 years of age.Breast cancer research and treatment · 2025Article
- Models for predicting risk of endometrial cancer: a systematic review.Diagnostic and prognostic research · 2025Article
- A risk prediction model for endometrial hyperplasia/endometrial carcinoma in premenopausal women.Scientific reports · 2025Article
- Development of a clinical diagnostic model for atypical endometrial hyperplasia and endometrial carcinoma in women aged 40-60 years based on refined abnormal uterine bleeding patterns.Frontiers in oncology · 2025Article
- Endometrial Thickness as a Prognostic Marker in Premenopausal Abnormal Uterine Bleeding: Diagnostic Accuracy and Kaplan-Meier Survival Insights.F1000Research · 2025Observational
- Analysis of Characteristics of Endometrial Carcinoma in Peri- and Postmenopausal Women with Abnormal Uterine Bleeding.BioMed research international · 2024Article
- Rapid identification of endometrial hyperplasia and endometrial endometrioid cancer in young women.Discover oncology · 2023Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
purposeThis study aimed to identify the risk factors and sonographic variables that could be integrated into a predictive model for endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) in women with abnormal uterine bleeding (AUB). MATERIALS AND
methodsThis retrospective study included 1837 patients who presented with AUB and underwent endometrial sampling. Multivariable logistic regression was developed based on clinical and sonographic covariates [endometrial thickness (ET), resistance index (RI) of the endometrial vasculature] assessed for their association with EC/AEH in the development group (n=1369), and a predictive nomogram was proposed. The model was validated in 468 patients.
resultsHistological examination revealed 167 patients (12.2%) with EC or AEH in the development group. Using multivariable logistic regression, the following variables were incorporated in the prediction of endometrial malignancy: metabolic diseases [odds ratio (OR)=7.764, 95% confidence intervals (CI) 5.042-11.955], family history (OR=3.555, 95% CI 1.055-11.971), age ≥40 years (OR=3.195, 95% CI 1.878-5.435), RI ≤0.5 (OR=8.733, 95% CI 4.311-17.692), and ET ≥10 mm (OR=8.479, 95% CI 5.440-13.216). A nomogram was created using these five variables with an area under the curve of 0.837 (95% CI 0.800-0.874). The calibration curve showed good agreement between the observed and predicted occurrences. For the validation group, the model provided acceptable discrimination and calibration.
conclusionThe proposed nomogram model showed moderate prediction accuracy in the differentiation between benign and malignant endometrial lesions among women with AUB.
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