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A panel of biomarkers to improve specificity in presurgical assessment of adnexal masses for risk of ovarian malignancy.

Ovarian Cancer

Gynecologic Cancer

2013 ASCO Annual Meeting

Abstract No:

J Clin Oncol 31, 2013 (suppl; abstr 5573)

Publication-only abstracts (abstract number preceded by an "e"), published in conjunction with the 2013 Annual Meeting but not presented at the Meeting, can be found online only.

Author(s): Zhen Zhang, Danni Li, Lori J. Sokoll, Xiaer Sun, Robert Bristow, Daniel W Chan; The Johns Hopkins University, School of Medicine, Baltimore, MD; University of Minnesota Medical Center Fairview, Minneapolis, MN; Johns Hopkins University School of Medicine, Baltimore, MD; University of California, Irvine, School of Medicine, Orange, CA

Abstract Disclosures


Background: OVA1 is a panel of biomarkers cleared by FDA currently in clinical use for pre-surgical assessment of adnexal masses for risk of ovarian malignancy. To further improve the specificity of OVA1, we evaluated biomarkers using a designed set of clinical samples enriched with OVA1 false positive benign patients and selected insulin-like growth factor binding protein 2 (IGFBP2), interleukin 6 (IL6), and follicle-stimulating hormone (FSH) to be further evaluated along with the original five biomarkers of OVA1 on a prospectively collected clinical sample set. The inclusion of FSH was to eliminate the need for menopause-specific cutoffs. Methods: Consecutive patients with a documented pelvic mass planned for surgical intervention were prospectively enrolled at 27 sites. Exclusion criteria included a diagnosis of malignancy in the previous 5 years or initial enrollment by a gynecologic oncologist. At the time of analysis, 384 subjects had all biomarker values. Among them 69 were ovarian cancer cases (13 LMPs, 27 stages 1/2, 19 serous, 11 endometrioid , 5 mucinous, and 4 clear cell). Biomarkers were tested by ELISA and reported as continuous values. Using a subset of the samples, the biomarkers were first selected for inclusion in a final panel based on contributions in multivariate models estimated by bootstrap. The selected biomarkers were further assessed for ability to improve specificity of risk stratification at a fixed sensitivity over that of OVA1 using the full data set. This was done by cross-validation of multivariate models with 50/50 split between training and testing. Results: The final panel of biomarkers consisted of CA125II, prealbumin, IGFBP2, IL6, and FSH. At a fixed sensitivity of 90%, the mean and median specificity of models using the new panel in testing were 78.2% (95% CI: 76.7 – 79.8%), and 80.6%, respectively. The mean and median absolute improvements over that of OVA1 were 18.6% (95% CI: 16.4% – 20.9%) and 20.3%, respectively. Conclusions: The new panel demonstrated the potential to significantly improve specificity over that of the first-generation OVA1 algorithm, while maintaining a high sensitivity in pre-surgical assessment of adnexal masses for risk of malignancy.


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