AnnEpi Mammography Interpretation 2012-10-08 CLEAN.pdf (136.66 kB)
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Potential missed detection with screening mammography: does the quality of radiologist’s interpretation vary by patient socioeconomic advantage/disadvantage?

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journal contribution
posted on 03.12.2013, 00:00 by Garth H. Rauscher, Jenna A. Khan, Michael L. Berbaum, Emily F. Conant
PURPOSE: We examined whether quality of mammography interpretation as performed by the original reading radiologist varied by patient sociodemographic characteristics. METHODS: For 149 patients residing in Chicago and diagnosed in 2005‐2008, we obtained the original index mammogram that detected the breast cancer and at least one prior mammogram that did not detect the cancer performed within 2 years of the index mammogram. A single breast imaging specialist performed a blinded review of the prior mammogram. Potentially missed detection was defined as an actionable lesion seen during a blinded review of the prior mammogram that was in the same quadrant as the cancer on the index mammogram. RESULTS: Of 149 prior mammograms originally read as non‐malignant, 46% (N=68) had a potentially detectable lesion. In unadjusted analyses, potentially missed detection was greater among minority patients (54% vs. 39%, p=0.07), for patients with incomes below $30,000 (65% vs. 36%, p<0.01), with less education (58% vs. 39%, p=0.02), and lacking private health insurance (63% vs. 40%, p=0.02). Likelihood ratio tests for the inclusion of socioeconomic variables in multivariable logistic regression models were highly significant (p<=0.02). CONCLUSIONS: Disadvantaged socioeconomic status appears to be associated with potentially missed detection of breast cancer at mammography screening.


This work was funded by grants to the University of Illinois at Chicago from the Illinois division of the American Cancer Society, and the Illinois Department of Public Health (#86280168). Additional funding was provided by the National Cancer Institute (Grant # 2P50CA106743‐06); the National Center for Minority Health Disparities (Grant # 1 P60MD003424‐01); and the Agency for Health Research and Quality (Grant # 1 R01 HS018366‐01A1).


Publisher Statement

NOTICE: This is the author’s version of a work that was accepted for publication in Annals of Epidemiology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Annals of Epidemiology, [Vol 23, Issue 4, 2013] DOI: 10.1016/j.annepidem.2013.01.006


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