Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial

Abstract

P opulation-based mammographic screening has proven effective in terms of mortality reduction due to breast cancer detection and treatment at an early stage (1,2). However, in women with high breast density, the sensitivity of mammography is markedly reduced because of the masking effect of the fibroglandular tissue (3-6). This is particularly important, as the breast cancer risk in women with extremely dense breasts is twice as high as that in women with average breast density (7).MRI is the most sensitive technique with which to screen women at high risk (8)(9)(10)(11)(12)(13)(14). More recently, MRI has also been considered as a screening tool in women at average risk with dense breasts (15-19). The Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial was Background: High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive screenings. Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed. Purpose:To build prediction models based on clinical characteristics and MRI findings to reduce the rate of false-positive screening MRI findings in women with extremely dense breasts. Materials and Methods:Clinical characteristics and MRI findings in Dutch breast cancer screening participants (age range, 50-75 years) with positive first-round MRI screening results (Breast Imaging Reporting and Data System 3, 4, or 5) after a normal screening mammography with extremely dense breasts (Volpara density category 4) were prospectively collected within the randomized controlled Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial from December 2011 through November 2015. In this secondary analysis, prediction models were built using multivariable logistic regression analysis to distinguish true-positive MRI screening findings from false-positive ones.Results: Among 454 women (median age, 52 years; interquartile range, 50-57 years) with a positive MRI result in a first supplemental MRI screening round, 79 were diagnosed with breast cancer (true-positive findings), and 375 had false-positive MRI results. The full prediction model (area under the receiver operating characteristics curve [AUC], 0.88; 95% CI: 0.84, 0.92), based on all collected clinical characteristics and MRI findings, could have prevented 45.5% (95% CI: 39.6, 51.5) of false-positive recalls and 21.3% (95% CI: 15.7, 28.3) of benign biopsies without missing any cancers. The model solely based on readily available MRI findings and age had a comparable performance (AUC, 0.84; 95% CI: 0.79, 0.88; P = .15) and could have prevented 35.5% (95% CI: 30.4, 41.1) of false-positive MRI screening results and 13.0% (95% CI: 8.8, 18.6) of benign biopsies. Conclusion:Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive firstround screening MRI rate and benign biopsy rate in women with extremely dense breasts.Clinical trial registration no...

An Improved Nomogram to Reduce False-Positive Biopsy Rates of Breast Imaging Reporting and Data System Ultrasonography Category 4A Lesions

“…However, it is believed that high breast density increases the high false positive rate. 33,34 In our study, we found that more than half of the BI-RADS(MG) 4B lesions were ultimately determined as benign. Therefore, it would be more rigorous to include BI-RADS(MG) as one component of the nomogram rather than relying solely on MG results due to the lower sensitivity of MG for women with dense breast tissue.…”

MRI versus Mammography plus Ultrasound in Women at Intermediate Breast Cancer Risk: Study Design and Protocol of the MRIB Multicenter, Randomized, Controlled Trial

“…As mentioned above, general countermeasures to curtail them, such as the repetition of MX or the use of targeted US, were implemented in this study and will be the object of specific analysis. In addition, to this purpose, future studies on the application of MRI in similar settings could benefit from the use of technological advances (such as fusion imaging [51]) or combined prediction models [52].…”

USPSTF Breast Cancer Screening Guidelines Do Not Go Far Enough

“…The cited Dense Tissue and Early Breast Neoplasm Screening trial in the Netherlands randomized women aged 50 to 75 years with extremely dense breasts and negative mammography results to a group invited to receive supplemental biennial MRI or to receive biennial mammography alone. 17,18 While the USPSTF cites a significant reduction in interval cancers in the MRI intervention arm, it understated that for women actually participating in MRI. Only 4 of 4783 women (0.8/1000) undergoing MRI experienced interval cancers compared to 16 of 3278 women (4.9/1000) invited to undergo MRI but declining, very similar to the rate of 161 of 32 312 (5.0/1000) among those not invited.…”