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Journal of the National Cancer Institute Advance Access originally published online on December 11, 2007
JNCI Journal of the National Cancer Institute 2007 99(24):1854-1863; doi:10.1093/jnci/djm238
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© The Author 2007. Published by Oxford University Press.

ARTICLES

Radiologist Characteristics Associated With Interpretive Performance of Diagnostic Mammography

Diana L. Miglioretti, Rebecca Smith-Bindman, Linn Abraham, R. James Brenner, Patricia A. Carney, Erin J. Aiello Bowles, Diana S. M. Buist, Joann G. Elmore

Affiliations of authors: Group Health Center for Health Studies, Group Health Cooperative, Seattle, WA (DLM, LA, EJAB, DSMB); Department of Biostatistics, University of Washington School of Public Health and Community Medicine, Seattle, WA (DLM); Departments of Radiology (RSB, RJB) and Epidemiology and Biostatistics (RSB), University of California, San Francisco, CA; Departments of Family Medicine and Public Health and Preventive Medicine, Oregon Health & Science University, Portland, OR (PAC); Department of Medicine, University of Washington School of Medicine, Harborview Medical Center, Seattle, WA (JGE)

Correspondence to: Diana L. Miglioretti, PhD, Group Health Center for Health Studies, Group Health Cooperative, 1730 Minor Ave, Ste 1600, Seattle, WA 98101 (e-mail: miglioretti.d{at}ghc.org).

Background: Extensive variability has been noted in the interpretive performance of screening mammography; however, less is known about variability in diagnostic mammography performance.

Methods: We examined the performance of 123 radiologists who interpreted 35895 diagnostic mammography examinations that were obtained to evaluate a breast problem from January 1, 1996, through December 31, 2003, at 72 facilities that contribute data to the Breast Cancer Surveillance Consortium. We modeled the influence of radiologist characteristics on the sensitivity and false-positive rate of diagnostic mammography, adjusting for patient characteristics by use of a Bayesian hierarchical logistic regression model.

Results: The median sensitivity was 79% (range = 27%–100%) and the median false-positive rate was 4.3% (range = 0%–16%). Radiologists in academic medical centers, compared with other radiologists, had higher sensitivity (88%, 95% confidence interval [CI] = 77% to 94%, versus 76%, 95% CI = 72% to 79%; odds ratio [OR] = 5.41, 95% Bayesian posterior credible interval [BPCI] = 1.55 to 21.51) with a smaller increase in their false-positive rates (7.8%, 95% CI = 4.8% to 12.7%, versus 4.2%, 95% CI = 3.8% to 4.7%; OR = 1.73, 95% BPCI = 1.05 to 2.67) and a borderline statistically significant improvement in accuracy (OR = 3.01, 95% BPCI = 0.97 to 12.15). Radiologists spending 20% or more of their time on breast imaging had statistically significantly higher sensitivity than those spending less time on breast imaging (80%, 95% CI = 76% to 83%, versus 70%, 95% CI = 64% to 75%; OR = 1.60, 95% BPCI = 1.05 to 2.44) with non–statistically significant increased false-positive rates (4.6%, 95% CI = 4.0% to 5.3%, versus 3.9%, 95% CI = 3.3% to 4.6%; OR = 1.17, 95% BPCI = 0.92 to 1.51). More recent training in mammography and more experience performing breast biopsy examinations were associated with a decreased threshold for recalling patients, resulting in similar statistically significant increases in both sensitivity and false-positive rates.

Conclusions: We found considerable variation in the interpretive performance of diagnostic mammography across radiologists that was not explained by the characteristics of the patients whose mammograms were interpreted. This variability is concerning and likely affects many women with and without breast cancer.



CONTEXT AND CAVEATS

Prior knowledge

Although high variability has been reported in the interpretive performance of screening mammography, less is known about variability in diagnostic mammography.

Study design

Multifacility retrospective study of the performance of 123 radiologists who interpreted more than 35000 diagnostic mammographic examinations. The influence of radiologist characteristics on sensitivity and the false-positive rate were modeled by use of Bayesian hierarchical logistic regression.

Contribution

Considerable variation in interpretive performance of diagnostic mammography was found across radiologists that was not explained by characteristics of the patients whose mammograms were interpreted.

Implications

The variability in performance of diagnostic mammography is concerning and likely affects many women with and without breast cancer. Ways to improve the interpretive performance of diagnostic mammography should be investigated.

Limitations

This study represented a small percentage of radiologists working in breast imaging and of mammography facilities in the United States, which may limit the generalizability of its results.

 
Manuscript received July 12, 2007; revised October 9, 2007; accepted October 25, 2007.


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