Two prediction models could help reduce false-positive breast cancer screening results among patients with high-density breasts, according to research published in Radiology.
The prediction models, which were based on clinical characteristics and MRI findings, could have prevented false-positive MRI screening results and benign biopsies without missing any cancers, according to researchers.
They noted that high breast density increases breast cancer risk and decreases the sensitivity of mammography, but supplemental MRI screening can increase the number of false-positive results.
“Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed,” the researchers wrote.
To that end, they developed 2 models — 1 based on all collected clinical characteristics and MRI findings and 1 based on MRI findings and age.
The researchers tested the models using data from the DENSE trial (ClinicalTrials.gov Identifier: NCT01315015). The cohort included 454 patients with a positive MRI result in a first supplemental MRI screening round.
The patients’ median age was 52 years (range, 50-57 years), their median body mass index was 22.1 kg/m2, and 222 patients were post-menopausal. The median Volpara breast density was 18.8%.
Ultimately, 375 of the 454 patients had false-positive results, and 79 were diagnosed with breast cancer.
The prediction model that included all clinical characteristics and MRI findings would have prevented 45.5% of false-positive results and 21.3% of benign biopsy results without missing any cancers, according to the researchers.
The model that included only MRI findings and age would have prevented 35.5% of false-positive MRI results and 13% of benign biopsy results without missing any cancers.
There was no significant difference between results of the 2 models (P =.15).
“In conclusion, prediction models based on clinical characteristics and MRI findings may reduce the false-positive first-round screening MRI rate and the number of benign biopsies, bringing supplemental screening MRI for women with dense breasts one step closer to implementation,” the researchers wrote. “Validation studies using data from different populations and incident screening rounds are warranted.”
Disclosure: Some study authors declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of disclosures.
den Dekker BM, Bakker MF, de Lange SV, et al. Reducing false-positive screening MRI rate in women with extremely dense breasts using prediction models based on data from the DENSE trial. Radiology. Published online August 17, 2021. doi:10.1148/radiol.2021210325
This article originally appeared on Cancer Therapy Advisor