DIFFERENTIAL DIAGNOSIS OF BENIGN, BORDERLINE, AND MALIGNANT OVARIAN MASSES IN PREGNANT WOMEN, BY USING LOGISTIC REGRESSION MODELS
- Authors: GERASIMOVA A.A1, SHVYREV S.L2, STEPANOV K.I2, GUS A.I3, KLIMENKO P.A2
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Affiliations:
- Center for Family Planning and Reproduction, Moscow Healthcare Department
- Russian State Medical University, Russian Agency for Health Care
- Academician V.I. Kulakov Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health and Social Development of Russia
- Issue: No 2 (2012)
- Pages: 50-56
- Section: Articles
- URL: https://journals.eco-vector.com/0300-9092/article/view/246693
- ID: 246693
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Abstract
Objective. To enhance the accuracy of differential diagnosis of benign, borderline, and malignant ovarian tumors in pregnant women, by building a logistic regression model. Material and methods. Regression logistic models were built to demonstrate that one can differentiate true tumors from tumor-like masses and benign neoplasms from malignant ones in 223 pregnant women on the basis of ultrasound signs of ovarian tumor-like masses and tumors. Results. While diagnosing benign ovarian tumors in pregnant women, the sensitivity and specificity of the model were 97 and 95%, respectively. While diagnosing borderline and malignant tumors, the sensitivity of the model was 100% and its specificity was 92.3% with a total accuracy of 92.8%. Conclusion. The performed studies have demonstrated that the authors’ regression logistic models can help a practitioner make timely a differential diagnosis of ovarian tumors in pregnant women, thus using their rational treatment policy.
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About the authors
A. A GERASIMOVA
Center for Family Planning and Reproduction, Moscow Healthcare DepartmentMoscow
S. L SHVYREV
Russian State Medical University, Russian Agency for Health CareMoscow
K. I STEPANOV
Russian State Medical University, Russian Agency for Health CareMoscow
A. I GUS
Academician V.I. Kulakov Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health and Social Development of RussiaMoscow
P. A KLIMENKO
Russian State Medical University, Russian Agency for Health CareMoscow
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