Risk Algorithm Using Biomarker May Double Screen-Detected Ovarian Cancers

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Screening through the use of a risk of ovarian cancer algorithm (ROCA) doubled the number of screen-detected primary invasive epithelial ovarian or tubal cancers (iEOCs), according to a recent study published online ahead of print in the Journal of Clinical Oncology.

Researchers led by Usha Menon, MD, of the University College London looked at patient data of 640 women from the United Kingdom Collaborative Trial of Ovarian Cancer Screening.

Among these women, all of whom underwent surgery, the researchers found that 133 had primary iEOCs, with 22 interval iEOCs occurring within one year of screening.

ROCA alone was able to detect 87.1 percent of the iEOCs, compared with fixed CA-125 cutoffs which would have identified 41.5 percent of women with more than 35 U/mL, 48.4 percent of more than 30 U/mL, and 66.5 percent of more than 22 U/mL.

“In the context of cancer screening, reliance on predefined single-threshold rules may result in biomarkers of value being discarded,” the authors concluded.

NSCLC patients with African-American ancestry may not differ from European backgrounds in somatic dr
Screening through the use of a risk of ovarian cancer algorithm doubled the number of screen-detected cancers.
Cancer screening strategies have commonly adopted single-biomarker thresholds to identify abnormality. We investigated the impact of serial biomarker change interpreted through a risk algorithm on cancer detection rates.
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