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Predictive Model may Identify Endometrial Hyperplasia and Cancer Risk in Patients with recurrent Uterine Bleed: Study
![Predictive Model may Identify Endometrial Hyperplasia and Cancer Risk in Patients with recurrent Uterine Bleed: Study Predictive Model may Identify Endometrial Hyperplasia and Cancer Risk in Patients with recurrent Uterine Bleed: Study](https://medicaldialogues.in/h-upload/2023/10/12/750x450_222609-uterine-cancer.webp)
A recent study made significant steps in predicting the risk of endometrial hyperplasia and endometrial cancer in patients with recurrent abnormal uterine bleeding (AUB). The condition characterized by unusual bleeding patterns has long been a concern due to its potential association with serious underlying conditions like endometrial cancer. The study published in the Obstetrics & Gynecology journal retrospectively analyzed patients over an 8-year period offered new inputs that could improve early detection and intervention.
The research focused on patients who had experienced recurrent AUB and had undergone previous endometrial sampling that returned benign results. The cohort included a total of 456 patients, with data collected from January 2013 to December 2021. The average interval between the first and second endometrial samplings was 25.1 months, during which 8.3% of the patients developed endometrial hyperplasia and 2.2% were diagnosed with endometrial cancer.
The study identified several significant factors that increased the risk of developing endometrial hyperplasia and cancer:
- Age Over 45 Years: Women older than 45 were nearly three times more likely to develop these conditions (OR 2.86).
- Nulliparity: The patients who had never given birth faced a significantly higher risk, with an odds ratio of 3.50.
- History of Endometrial Polyp: A previous diagnosis of endometrial polyps emerged as a strong predictor by increasing the odds of hyperplasia and cancer by over three times (OR 3.69).
- Short Interval Between Samplings: An interval of less than 12 months between endometrial samplings doubled the risk (OR 2.36).
These factors were used to create a predictive model with each factor assigned a specific risk score. The total score for each patient allowed categorization into 3 distinct risk groups which were, low (0-3 points), moderate (5-8 points) and high (9-11 points). The corresponding risks for developing endometrial hyperplasia and cancer were 4.7%, 15.5%, and 57.1%, respectively.
The overall performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC) which was 73.1%. This indicated a good predictive ability. This findings of the study offer a valuable tool for clinicians in managing patients with recurrent AUB. Clinicians can prioritize closer monitoring and earlier interventions y identifying those at higher risk for endometrial hyperplasia and cancer which could potentially improve patient outcomes. This predictive model marks a major leap forward against endometrial cancer, particularly for women who might otherwise fall through the cracks of early detection.
Reference:
Veeranaraphanit, U., Saeaib, N., & Srisintorn, W. (2024). Predicting Endometrial Hyperplasia and Endometrial Cancer on Recurrent Abnormal Uterine Bleeding. In Obstetrics & Gynecology. Ovid Technologies (Wolters Kluwer Health). https://doi.org/10.1097/aog.0000000000005641
Neuroscience Masters graduate
Jacinthlyn Sylvia, a Neuroscience Master's graduate from Chennai has worked extensively in deciphering the neurobiology of cognition and motor control in aging. She also has spread-out exposure to Neurosurgery from her Bachelor’s. She is currently involved in active Neuro-Oncology research. She is an upcoming neuroscientist with a fiery passion for writing. Her news cover at Medical Dialogues feature recent discoveries and updates from the healthcare and biomedical research fields. She can be reached at editorial@medicaldialogues.in
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: editorial@medicaldialogues.in. Contact no. 011-43720751