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Background: Previous studies have shown that the agreement among radiologists interpreting a test set of mammograms is relatively low. However, data available from real-world settings are sparse. We studied mammographic examination interpretations by radiologists practicing in a community setting and evaluated whether the variability in false-positive rates could be explained by patient, radiologist, and/or testing characteristics., Methods: We used medical records on randomly selected women aged 40-69 years who had had at least one screening mammographic examination in a community setting between January 1, 1985, and June 30, 1993. Twenty-four radiologists interpreted 8734 screening mammograms from 2169 women. Hierarchical logistic regression models were used to examine the impact of patient, radiologist, and testing characteristics. All statistical tests were two-sided., Results: Radiologists varied widely in mammographic examination interpretations, with a mass noted in 0%-7.9%, calcification in 0%-21.3%, and fibrocystic changes in 1.6%-27.8% of mammograms read. False-positive rates ranged from 2.6% to 15.9%. Younger and more recently trained radiologists had higher false-positive rates. Adjustment for patient, radiologist, and testing characteristics narrowed the range of false-positive rates to 3.5%-7.9%. If a woman went to two randomly selected radiologists, her odds, after adjustment, of having a false-positive reading would be 1.5 times greater for the radiologist at higher risk of a false-positive reading, compared with the radiologist at lowest risk (95% highest posterior density interval [similar to a confidence interval] = 1.17 to 2.08)., Conclusion: Community radiologists varied widely in their false-positive rates in screening mammograms; this variability range was reduced by half, but not eliminated, after statistical adjustment for patient, radiologist, and testing characteristics. These characteristics need to be considered when evaluating false-positive rates in community mammographic examination screening.

Background: The cumulative risk of a false-positive mammogram can be substantial. We studied which variables affect the chance of a false-positive mammogram and estimated cumulative risks over nine sequential mammograms., Methods: We used medical records of 2227 randomly selected women who were 40-69 years of age on July 1, 1983, and had at least one screening mammogram. We used a Bayesian discrete hazard regression model developed for this study to test the effect of patient and radiologic variables on a first false-positive screening and to calculate cumulative risks of a false-positive mammogram., Results: Of 9747 screening mammograms, 6. 5% were false-positive; 23.8% of women experienced at least one false-positive result. After nine mammograms, the risk of a false-positive mammogram was 43.1% (95% confidence interval [CI] = 36.6%-53.6%). Risk ratios decreased with increasing age and increased with number of breast biopsies, family history of breast cancer, estrogen use, time between screenings, no comparison with previous mammograms, and the radiologist's tendency to call mammograms abnormal. For a woman with highest-risk variables, the estimated risk for a false-positive mammogram at the first and by the ninth mammogram was 98.1% (95% CI = 69.3%-100%) and 100% (95% CI = 99.9%-100%), respectively. A woman with lowest-risk variables had estimated risks of 0.7% (95% CI = 0.2%-1.9%) and 4.6% (95% CI = 1. 1%-12.5%), respectively., Conclusions: The cumulative risk of a false-positive mammogram over time varies substantially, depending on a woman's own risk profile and on several factors related to radiologic screening. By the ninth mammogram, the risk can be as low as 5% for women with low-risk variables and as high as 100% for women with multiple high-risk factors.