Although applied during screening mammography for millions of women in the United States every year, computer-aided detection (CAD) technology does not improve tumor detection rates and may increase the risk for additional, needless testing due to false-positive results. These findings corroborate the results of a similar study conducted in 2007.
An analysis of more than 1.6 million film-screen mammograms conducted at 90 facilities in seven states from 1998 to 2006 indicated that CAD was not associated with higher breast cancer detection rates or more favorable stage, size, or lymph node status of invasive breast cancer. CAD software analyzes the mammogram image and marks suspicious areas for radiologists to review. Approved by the FDA in 1998, CAD has come into increasingly greater use since 2001, when Medicare began to cover payments for the technology.
But a team led by Joshua J. Fenton, MD, MPH, of the University of California–Davis (UC-Davis) Department of Family and Community Medicine and Center for Healthcare Policy and Research, reports in the Journal of the National Cancer Institute that for the facilities included in this evaluation, the false-positive rate typically increased from 8.1% before the implementation of CAD to 8.6% after CAD use was initiated. In a statement issued by the UC-Davis Health System, Fenton noted that breast cancers were detected at a similar stage and size regardless of whether or not CAD was used.
Fenton and several of his current coauthors had reached a similar conclusion four years ago, reporting their results in The New England Journal of Medicine (2007;356:1399-1409; www.nejm.org/doi/pdf/10.1056/NEJMoa066099). At that time, they contended that CAD was associated with reduced accuracy of interpretation of screening mammograms, and that the subsequent increased biopsy rate was not clearly associated with improved detection of invasive breast cancer. Critics of that study charged that it was based on the use of older CAD technology and therefore did not accurately reflect its effectiveness.
However, “In the current study, we evaluated a newer technology in a larger sample and over a longer time period,” affirmed Fenton in the UC-Davis statement. “We also looked for the first time at cancer stage and cancer size, which are critical for understanding how CAD may affect long-term breast cancer outcomes, such as mortality.”