Endometrial Findings in Patients with Breast Cancer Using Tamoxifen - Revista Brasileira de Ginecologia e Obstetrícia

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Endometrial Findings in Patients with Breast Cancer Using Tamoxifen

Revista Brasileira de Ginecologia e Obstetrícia. 2002;24(4):233-239

DOI: 10.1590/S0100-72032002000400004

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Purpose: to analyze sensitivity, specificity, positive and negative predictive values and the likelihood ratio of transvaginal ultrasound and hysteroscopy when compared with the histopathologic examination of the endometrium in women with breast cancer who have been treated with tamoxifen. Methods: transversal study with 30 women in whom transvaginal ultrasound evaluated the echogenic pattern of endometrial echo and its thickness. Hyteroscopy was performed and described as normal (normal or atrophic endometrium) or abnormal (thickening, polyps, leiomyoma, synechia). Material for histopathology was obtained from endometrial biopsy and the findings were considered normal (irregular endometrial maturation and/or atrophy) or abnormal (polyps, simple or complex hyperplasia, leiomyoma or endometrial carcinoma). Results: the general diagnosis of endometrial modifications was present in 36.6% of patients. The most frequent results were cystic atrophy (46.6%) and endometrial polyps (26.6%). Through the ROC curve the best cutoff of 8 mm of endometrial thickness measure was determined. This measure showed sensitivity of 72.7%, specificity of 72.9%, positive predictive value of 66.6%, negative predictive value of 83.3% and likelihood ratio of 3.4. Hysteroscopy showed sensitivity of 90.9%, specificity of 68.4%, positive predictive value of 62.5%, negative prediction value of 92.8% and likelihood ratio of 2.8. Conclusions: the most frequent endometrial modifications were cystic atrophy followed by polyps. Transvaginal ultrasound showed a higher rate of false-positive (42.1%), when the cutoff for the thickness of the endometrium was 5 mm; however acuracy improved when the measure of 8 mm was used. The cutoff of 8 mm was determined through the ROC curve.

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