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Evaluation of ovarian cancer biomarkers HE4 and CA-125 in women presenting with a suspicious cystic ovarian mass
Authors:Karolina Partheen  Bj?rg Kristjansdottir  Karin Sundfeldt
Affiliation:Institute of Clinical Sciences, Department of Obstetrics and Gynecology, Sahlgrenska Cancer Centre, University of Gothenburg, Gothenburg, Sweden.
Abstract:

Objective

Women presenting with a large or complex ovarian cyst are referred to extensive surgical staging to ensure the correct diagnosis and treatment of a possible epithelial ovarian cancer. We hypothesized that measurement of the biomarkers HE4 and CA-125 preoperatively would improve the assignment of these patients to the correct level of care.

Methods

Patients diagnosed with a cystic ovarian mass and scheduled for an operation at our center of excellence for ovarian cancer surgery from 2001 to 2010 were prospectively included (n=394) and plasma was collected consecutively. Cut-off for HE4 was calculated at 75% specificity (85 pM and 71.8 pM for post and premenopausal women). For CA-125, 35 U/mL cut-off was used. The study population included women with malignant (n=114), borderline (n=45), and benign (n=215) ovarian tumors.

Results

Receiver operator characteristic (ROC) area under the curve (AUC) in the benign versus malignant cohorts was 86.8% for CA-125 and 84.4% for HE4. Negative predictive value was 91.7% when at least one of the biomarkers was positive, with only early stage epithelial ovarian cancer showing false negative results. Sensitivity at set specificity (75%) was 87% for risk of ovarian malignancy algorithm (ROMA) in the postmenopausal cohort (cut-off point, 26.0%) and 81% in the premenopausal cohort (cut-off point, 17.3%). ROC AUC in the benign versus stage I epithelial ovarian cancer was only 72% for HE4 and 76% for CA-125.

Conclusion

In our study, population HE4 did not outperform CA-125. Based on our data a prospective trial with patients already diagnosed with an ovarian cyst may be conducted.
Keywords:CA-125   Human epididymis protein 4   Ovarian cancer   Risk of ovarian malignancy algorithm
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