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Adding CAD to mammography failed to improve detection rate, prognostic characteristics of invasive disease
Berry DA. J Natl Cancer Inst. 2011;doi:10.1093/jnci/djr267.
Fenton JJ. J Natl Cancer Inst. 2011;doi:10.1093/jnci/djr206.
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The benefits of computer-aided detection during screening mammography remain unclear, according to a study published in the Journal of the National Cancer Institute.
Data demonstrated that computer-aided detection (CAD) was associated with lower specificity and positive predictive value, but it did not improve detection rates or prognostic characteristics of invasive breast cancer.
Researchers collected data for 684,956 women who received film-screened mammograms at 90 US facilities participating in the Breast Cancer Surveillance Consortium between 1998 and 2006. They aimed to determine the relationship between CAD and specificity, sensitivity and positive predictive value. They adjusted for mammography registry, patient age, time since last mammogram, breast density, hormone therapy status and year of examination.
Nearly 30% of facilities (27.8%) adopted CAD for an average of 27.5 study months. CAD was significantly associated with lower specificity (OR=0.87; 95% CI, 0.85-0.89) and positive predictive value (OR=0.89; 95% CI, 0.80-0.99), according to the researchers. There was a non-statistically significant increase in overall sensitivity associated with CAD (OR=1.06; 95% CI, 0.84-1.33) that was attributed to increased sensitivity for ductal carcinoma in situ (OR=1.55; 95% CI, 0.83-2.91). Sensitivity for invasive cancer was similar with or without CAD (OR=0.96; 95% CI, 0.75-1.24), the researchers wrote.
After adjusting for various factors, CAD was not statistically significantly associated with differences in odds of biopsy recommendation (OR=0.99; 95% CI, 0.93-1.05), overall breast cancer detection (OR=1.01; 95% CI, 0.92-1.12), detection of invasive disease (OR=0.97; 95% CI, 0.86-1.08), diagnosis of stage I invasive disease vs. later-stage invasive disease (OR=0.90; 95% CI, 0.73-1.11) or the diagnosis of invasive tumors of 15 mm or less vs. more than 15 mm (OR=0.92; 95% CI, 0.74-1.15).
“The ‘real-world’ study by Fenton et al is an example of comparative effectiveness research,” Donald A. Berry, PhD, department of biostatistics at The University of Texas MD Anderson Cancer Center, wrote in an accompanying editorial. “Such studies can be more relevant for policy and practice than controlled efficacy studies. A case in point is the lack of improvement in sensitivity in the Fenton study.”
One argument for the use of CAD with film or digital mammography is that the technology will get better with time, Berry said, adding that if that is the case, researchers and device manufacturers should improve the software. “But this should happen in an experimental setting and not while exposing millions of women to a technology that may be more harmful than it is beneficial.”
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