Short-term outcomes of screening mammography using computer-aided detection a population-based study of medicare enrollees

In the past decade, 2 technologies have transformed screening methods in the United States. First, digital mammography has supplanted film-screen mammography as the predominant method of image acquisition and storage. Second, most radiologists now use computer algorithms, or computer-aided detection (CAD), to mark and reassess potentially suspicious lesions that may have been missed on initial mammogram review. In 2001, Congress extended Medicare coverage to CAD, and CAD has since diffused widely into U.S. practice (1–3). In Europe, where double-reading by 2 radiologists is common, some have proposed replacing the second reader with CAD (4). Despite broad uptake, the effectiveness and clinical utility of CAD in screening mammography remains controversial. In individual radiology practices, CAD adoption has been associated with greater rate of cancer detection, along with commensurate increases in false-positive rates (5–9), and within 3 British health system breast screening centers, outcomes were similar whether mammograms were double-read or interpreted by a single reader using CAD (10). However, in some practices, CAD adoption has been associated with little, if any, clinical effect (11, 12). The clinical effect of CAD may be heterogeneous across practices (13) or radiologists (14). In addition, CAD may differentially facilitate detection of noninvasive breast cancer, or ductal carcinoma in situ (DCIS), rather than invasive breast cancer (6–8, 15– 18). Because randomized clinical trials suggest that the effect of mammography on breast cancer mortality derives chiefly from detecting invasive cancer (19, 20), it is crucial to delineate the effect of CAD on the detection of invasive and noninvasive breast cancer. In multicenter studies, CAD has not been associated with a clear improvement in the diagnosis of invasive breast cancer (15, 16) despite greater false-positive (15, 16) and biopsy rates (15). However, because breast cancer is uncommon, studies to date may have had insufficient sample sizes of participants with cancer to precisely estimate the association of CAD with detection of invasive versus noninvasive breast cancer or its association with invasive breast cancer stage, size, or lymph node status, all of which are important predictors of breast cancer survival. As stated in a U.S. Preventive Services Task Force evidence review, new digital technologies, such as CAD, “have become widely used in the United States without definitive studies of their effect on screening” (21). Ideally, clinical trials would compare breast cancer outcomes among women screened with CAD versus without CAD, but such trials would require long-term follow-up of very large samples (22). To our knowledge, no such trials are planned or ongoing. However, now that CAD has diffused into clinical practice in the United States, the linked SEER (Surveillance, Epidemiology and End Results)–Medicare data enable a large-sample, population-based observational study of the clinical effect of CAD within the Medicare population. Although evaluation of CAD among both younger and older women having screening is desirable, the SEER–Medicare data offer sample sizes and analytic precision that cannot otherwise be achieved. Therefore, we assessed associations between CAD use during screening mammography received by Medicare enrollees and the incidence of invasive breast cancer and DCIS; invasive breast cancer stage, size, and lymph node status; and subsequent diagnostic testing among women without breast cancer.