Journal of Mid-life Health Journal of Mid-life Health
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Year : 2019  |  Volume : 10  |  Issue : 4  |  Page : 179-183

A clinicopathological evaluation of postmenopausal bleeding and its correlation with risk factors for developing endometrial hyperplasia and cancer: A hospital-based prospective study

1 Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
2 Department of Obstetrics and Gynaecology, Mahatma Gandhi Medical College and Research Institute, Puducherry, India

Correspondence Address:
Jasmina Begum
Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, Bhubaneswar - 751 019, Odisha
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jmh.JMH_136_18

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Objective: The aim of this study is to investigate the clinical data from history and endometrial pathology by endometrial sampling in patients with postmenopausal bleeding and to identify risk factors associated with future development of endometrial cancer (EC). Methods: We prospectively studied 76 postmenopausal women with vaginal bleeding and endometrial thickness (ET) >5 mm undergoing endometrial biopsy or dilatation and curettage. Patient characteristics and endometrial assessment of women with or without EC and hyperplasia were compared. Univariate and multivariate logistic regression identified factors associated with risks of endometrial neoplasia. Results: In this study, the mean age at the time of presentation was 57.17 ± 7.11 years, mean menopausal age was 49.18 ± 3.69 years, and mean thickness of endometrial was 11.13 ± 6.37 mm. The histopathological analysis showed atrophic endometrium (30.3%), proliferative endometrium (27.6%), EC (15.8%), endometrium hyperplasia (11.8%), disordered proliferative endometrium (9.2%), and endometrial polyp (5.3%). Women of EC and hyperplasia group were more likely to be multiparous, diabetic, hypertensive, obese or overweight, has a history of recurrent bleeding episodes or thick endometrium. Using multivariate logistic regression, we found ET (adjusted odds ratio [AOR] = 17.76, confidence interval [CI] 1.91–165.02, P < 0.011, criterion ≥11 mm), recurrent episode of bleeding (AOR = 13.21, CI 1.10–158.91, P < 0.042), diabetes (AOR = 8.03, CI 1.15–55.78, P < 0.035) the best predictors of EC. Conclusion: As clinical characteristics are possible predictors of EC, these should also be taken into account in risk estimations and in the formulation of management plans. This not only has benefit in the process of disease detection but also may result in improved the efficiency of care.

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