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Ovarian endometriosis: risk factor analysis and prediction of malignant transformation.

Authors :
YanNa Zhou
Ke-qin Hua
Source :
Menopausal Review / Przegląd Menopauzalny. 2018, Vol. 17 Issue 1, p43-48. 6p.
Publication Year :
2018

Abstract

Introduction: For the prediction of endometriosis associated ovarian carcinoma (EAOC), the risk factors for malignant ovarian endometriosis (MOE) were explored. Material and methods: A group of 104 EAOC patients was compared with a group of 104 ovarian endometrial cyst patients. Using single and multivariate risk analysis of EAOC by calculating the area under the curve (AUC) of receiver-operator characteristics (ROC) curves, risks of MOE transformation were calculated for various burdens of risk factors. Results: The age range of 85 EAOC patients (81.73% of EAOC patients) was from 40 to 60 years old, as menopause occurs most frequently in this age range. From single factor ROC curve analysis, if disease duration/age/menopause/times of pregnancy/multiple foci of endometriosis index AUC were above 0.70, this suggested that the above indicators were predictive of MOE. Times of pregnancy/tumour size/myoma of uterus/multiple foci of endometriosis were taken as the independent risk factors of MOE. Using logistic regression, the AUC of 0.89 (95% confidence interval [CI]: 0.84-0.94) was statistically significant (p < 0.001), illustrating the predictive power of this model. Conclusions: Times of pregnancy/BMI/irregular vaginal bleeding/thyroid disease/myoma of uterus/tumour serious fixation index indicate higher risk of MOE; age/tumour size/menopause/disease duration/dysmenorrhea/multiple foci of endometriosis suggest lower risk of MOE. Therefore, in patients with endometriosis, malignant transformation could be predicted early. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*ENDOMETRIOSIS
*OVARIAN cancer

Details

Language :
English
ISSN :
16438876
Volume :
17
Issue :
1
Database :
Academic Search Index
Journal :
Menopausal Review / Przegląd Menopauzalny
Publication Type :
Academic Journal
Accession number :
129245111
Full Text :
https://doi.org/10.5114/pm.2018.74902