Pre-operative imaging with CA125 is a poor predictor for granulosa cell tumors
Abstract Objective To determine the radiographic characteristics of ovarian granulosa cell tumors (GCTs) and to evaluate the use of CA125 levels > 35 in combination with imaging as an algorithm for preoperative diagnosis. Methods A retrospective analysis of women from two academic medical centers...
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Veröffentlicht in: | Gynecologic oncology 2013-10, Vol.131 (1), p.59-62 |
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Zusammenfassung: | Abstract Objective To determine the radiographic characteristics of ovarian granulosa cell tumors (GCTs) and to evaluate the use of CA125 levels > 35 in combination with imaging as an algorithm for preoperative diagnosis. Methods A retrospective analysis of women from two academic medical centers who were diagnosed with ovarian GCT between January 1998 and August 2012 was conducted. Clinical data included tumor appearance on pre-operative imaging and CA125 levels. Ovarian cysts were defined as complex if imaging exhibited multicystic areas, hemorrhagic, solid, or cystic and solid components. A CA125 level > 35 was abnormal. Results One hundred and fifteen women were diagnosed with GCTs, of whom 63 underwent pre-operative imaging. Median age at surgery was 46 years (12–87). Forty women had preoperative ultrasounds, 43 had CT scans and 20 underwent both modalities. GCTs were almost exclusively classified as complex cysts in 62 (98%) cases. The most common morphology was solid and cystic (n = 44 (70%)). Forty-four (70%) patients had tumors > 10 cm. Forty-two patients had a pre-operative CA125 performed. Eighteen (43%) patients had complex masses and CA125 > 35. Twenty-three (55%) had CA125 < 35 with a complex mass, and one (2%) had a unilocular cyst with a CA125 > 35. Conclusions In this study, there was a near equal distribution of patients with complex masses and CA125 levels > or < 35. If established strategies to predict malignancy are applied to GCTs, we will frequently fail to make the diagnosis pre-operatively. Additional research is necessary to generate an appropriate algorithm to guide pre-operative referral to a gynecologic oncologist. |
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ISSN: | 0090-8258 1095-6859 |
DOI: | 10.1016/j.ygyno.2013.06.030 |