The model-adjusted rate was adjusted for screening method and site. The density effect was adjusted for age to account for the potential confounding effect of age on breast density.
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Rafferty EA, Durand MA, Conant EF, et al. Breast Cancer Screening Using Tomosynthesis and Digital Mammography in Dense and Nondense Breasts. JAMA. 2016;315(16):1784–1786. doi:10.1001/jama.2016.1708
Copyright 2016 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
Breast density is associated with reduced mammographic sensitivity and specificity. Additionally, increased tumor size and worsened prognosis are associated with increased breast density.1,2 Dense breast tissue may also represent an independent risk factor for breast cancer.3 Currently, 24 states have laws mandating that women be notified of the implications of breast density, thereby encouraging discussions between patients and physicians regarding the need for supplemental screening.4 However, which, if any, additional modalities should be recommended for women with dense breasts is not known.
Using data from our previous multicenter study,5 we evaluated differential screening performance of digital mammography combined with tomosynthesis compared with digital mammography alone as a function of breast density.
The protocol was approved by institutional review boards of participating institutions with a waiver of informed consent. Screening performance metrics from 13 US institutions were reported for 12 months using digital mammography alone (beginning March 2011 to October 2012) and from the date of introduction of tomosynthesis until December 31, 2012 (range, 3-22 months).
Subgroups included the 4 breast density categories used for clinical reporting. Almost entirely fat and scattered fibroglandular densities were considered nondense tissue patterns, whereas heterogeneously dense and extremely dense were considered dense tissue patterns.
Overall and invasive cancer detection rates and recall rate with and without tomosynthesis were analyzed in patients with both nondense and dense breasts. Positive predictive value for recall was calculated. Exploratory analyses were conducted for all 4 density categories. Additive models were used to estimate rates as previously described (adjusting for screening method and site).5 An additional multivariable model including all subgroup effects was fit to determine age-adjusted density effect. Adjusted rates and 95% confidence intervals were calculated based on fitted models using SAS (SAS Institute), version 9.3. All tests were 2-sided and a P value less than .05 was considered statistically significant. Because data on interval cancers were not available, complete assessment of sensitivity and specificity could not be done.
Of 452 320 examinations, 278 906 were digital mammography alone and 173 414 digital mammography plus tomosynthesis; 2157 cancers were diagnosed. The Table summarizes results of primary (dense vs nondense) and exploratory (breast density categories) analyses showing model-adjusted rates. Recall rates per 1000 screens in nondense breasts decreased from 90 to 79 (difference, −12 [95% CI, −14 to −9]; P < .001); and in dense breasts from 127 to 109 (difference, −18 [95% CI, −21 to −15]; P < .001) with tomosynthesis. Positive predictive value of recalls increased in both nondense and dense breasts. Cancer detection rates also increased in both groups. Invasive cancer detection rate per 1000 screens in nondense breasts increased from 3.0 to 4.0 (difference, 0.9 [95% CI, 0.4 to 1.5]; P < .001) and in dense breasts from 2.9 to 4.2 (difference, 1.4 [95% CI, 0.9-1.9]; P < .001) with tomosynthesis.
For subgroups of breast density, improvements in rates were greatest for women with scattered fibroglandular densities and heterogeneously dense breasts. Differences were mostly not significant for almost entirely fat and extremely dense subgroups.
The Figure depicts density effect adjusted for age, consistent with the increased cancer detection and reduced recall rates after implementation of tomosynthesis not being solely attributable to confounding by age but possibly independently associated with improved screening performance.
Addition of tomosynthesis to digital mammography for screening was associated with an increase in cancer detection rate and a reduction in recall rate for women with both dense and nondense breast tissue. These combined gains were largest for women with heterogeneously dense breasts, potentially addressing limitations in cancer detection seen with digital mammography alone in this group, but were not significant in women with extremely dense breasts.
Limitations of this study include its retrospective design, collection of data at the population level rather than the patient level, and insufficient follow-up to determine if increased invasive cancer detection improved clinical outcomes. For women classified as having dense breast tissue, most have heterogeneously dense breasts, mandating caution in drawing conclusions regarding the performance of tomosynthesis for the small proportion of women with extremely dense breasts.
Corresponding Author: Elizabeth A. Rafferty, MD, L&M Radiology, PO Box 615, West Acton, MA 01720 (email@example.com).
Author Contributions: Dr Rafferty had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: All authors.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Miller.
Obtained funding: Conant, Friedewald, Plecha.
Administrative, technical, or material support: Rafferty, Conant, Friedewald.
Study supervision: Rafferty, Conant, Friedewald, Miller.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Funding and Support: This study was funded by a research grant from Hologic (Drs Rafferty, Durand, Copit, Friedewald, and Plecha).
Role of the Funder/Sponsor: Principal investigators from the 13 participating institutions along with Hologic jointly designed the study. Hologic provided logistical and technical support for the collection of data. The study contracts and data sharing agreements specified that Hologic had the right to review all publications prior to submission, but could not mandate any revision of the manuscript or prevent submission for publication. Each institution verified the accuracy of their performance data, which was then transferred to an independent statistical group (ICON) for analysis. The results reported in this article are the result of the independent analysis by Faith Beery and David Pasta (both from ICON).
Additional Contributions: We thank the following site principal investigators: Stephen L. Rose, MD (TOPS Comprehensive Breast Center); Linda N. Greer, MD (John C. Lincoln Breast Health and Research Center); Mary K. Hayes, MD (Radiology Associates of Hollywood); Ingrid L. Ott, MD (Washington Radiology Associates); Kara L. Carlson, MD (Evergreen Breast Health Center); Thomas M. Cink, MD (Edith Sanford Breast Health Institute); Lora D. Barke, DO (Invision Sally Jobe Breast Center). We also acknowledge Anne Marie McCarthy, PhD (Massachusetts General Hospital), for data analysis and David Pasta, MS, and Faith Beery, MS (both from ICON), for statistical analysis of the results. Drs Rose, Greer, Hayes, Ott, Carlson, Cink, and Barke received a research grant for their contributions in this study from Hologic. All other contributors did not receive compensation for their contribution aside from their salaries.
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