Multiple Biomarker Algorithms to Predict Epithelial Ovarian Cancer in Women with a Pelvic Mass: Can Additional Makers Improve Performance?
Sponsor
National Institutes of Health Grant: R01CA136491.
Published In
Gynecologic Oncology
Document Type
Citation
Publication Date
7-1-2019
Abstract
Introduction
Management of a woman with a pelvic mass is complicated by difficulty in discriminating malignant from benign disease. Many serum biomarkers have been examined to determine their sensitivity for detecting malignancy. This study was designed to evaluate if the addition of biomarkers to HE4 and CA125, as used in the Risk of Malignancy Algorithm (ROMA), can improve the detection of EOC.
Methods
This was an IRB approved, prospective clinical trial examining serum obtained from women diagnosed with a pelvic mass who subsequently underwent surgery. Serum biomarker levels for CA125, HE4, YKL-40, transthyretin, ApoA1, Beta-2-microglobulin, transferrin, and LPA were measured. Logistic regression analysis was performed for various marker combinations, ROC curves were generated, and the area under the curves (AUCs) were determined.
Results
A total of 184 patients met inclusion criteria with a median age of 56 years (Range 20–91). Final pathology revealed there were 103 (56.0%) benign tumors, 4 (2.2%) LMP tumors, 61 EOC (33.1%), 2 (1.1%) non-EOC ovarian cancers, 6 (3.3%) gynecologic cancers with metastasis to the ovary and 8 (4.3%) non-gynecologic cancers with metastasis to the ovary. The combination of HE4 and CA125 (i.e. ROMA) achieved an AUC of 91.2% (95% CI: 86.0–96.4) for the detection of EOC vs benign disease. The combination of CA125, HE4, YKL-40, transthyretin, ApoA1, Beta 2 microglobulin, transferrin, LPA and menopausal status achieved the highest AUC of 94.6% (95% CI: 90.1–99.2) but this combination was not significantly better than the HE4 and CA125 combination alone (p = 0.078).
Conclusions
The addition of select further serum biomarkers to HE4 and CA125 does not add to the performance of the dual marker combination for the detection of ovarian cancer.
Locate the Document
DOI
10.1016/j.ygyno.2019.04.006
Persistent Identifier
https://archives.pdx.edu/ds/psu/30263
Citation Details
Moore, R. G., Blackman, A., Miller, M. C., Robison, K., DiSilvestro, P. A., Eklund, E. E., … Messerlian, G. (2019). Multiple biomarker algorithms to predict epithelial ovarian cancer in women with a pelvic mass: Can additional makers improve performance? Gynecologic Oncology, 154(1), 150–155.
Description
© 2019 Elsevier Inc. All rights reserved.