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Original Research |
1 South Carolina Comprehensive Breast Center, Palmetto Richland Memorial
Hospital, One Richland Medical Park Dr., Suite 120, Columbia, SC 29203.
2 Department of Obstetrics and Gynecology, School of Medicine, University of
South Carolina, Columbia, SC 29203.
3 South Carolina Comprehensive Cancer Center, Columbia, SC.
4 Department of Pathology, Palmetto Richland Memorial Hospital, Columbia, SC
29203.
OBJECTIVE. This study was conducted to prospectively assess the effect of computer-aided detection (CAD) on screening outcomes in a regional mammography program.
MATERIALS AND METHODS. Between January 1, 1998, and December 31, 2000, 27,274 consecutive screenings were performed. Radiologists' performance before CAD (n = 7,872) and with CAD (n = 19,402) was determined by annual audits. All positive biopsy results were reviewed; histopathology was reviewed and confirmed. Outcomes (recall, biopsy, and cancer detection rates) with CAD (1999, 2000) were compared with historical control data (1998).
RESULTS. With CAD, increases were seen in recall rate (8.1%, from 7.7% to 8.3%), biopsy rate (6.7%, from 1.4% to 1.5%), and cancer detection rate (16.1%, from 3.7 per 1,000 to 4.3 per 1,000). Detection rate of invasive cancers of 1.0 cm or less increased 164% (from 0.508 to 1.34 per 1,000 screens; p = 0.069). Detection rate of in situ cancers declined 6.7% (from 1.27 to 1.19 per 1,000; p = 0.849). In multivariable analysis of invasive cancers, early stage (stage I) was strongly associated with detection by CAD (odds ratio = 4.13, p = 0.025). Mean age at screening detection of cancer was 5.3 years younger in the CAD group than in the pre-CAD group (p = 0.060).
CONCLUSION. Increased detection rate, younger age at diagnosis, and significantly earlier stage of invasive cancer detection are consistent with a positive screening impact of CAD. Audit results were positive but generally not statistically significant due to sample size limitations. Our findings support the hypothesis that screening with CAD significantly improves detection of the specific cancer morphologies that CAD algorithms were designed to detect.
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