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      Differential detection by breast density for digital breast tomosynthesis versus digital mammography population screening: a systematic review and meta-analysis

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          Abstract

          Background

          We examined whether digital breast tomosynthesis (DBT) detects differentially in high- or low-density screens.

          Methods

          We searched six databases (2009–2020) for studies comparing DBT and digital mammography (DM), and reporting cancer detection rate (CDR) and/or recall rate by breast density. Meta-analysis was performed to pool incremental CDR and recall rate for DBT (versus DM) for high- and low-density (dichotomised based on BI-RADS) and within-study differences in incremental estimates between high- and low-density. Screening settings (European/US) were compared.

          Results

          Pooled within-study difference in incremental CDR for high- versus low-density was 1.0/1000 screens (95% CI: 0.3, 1.6; p = 0.003). Estimates were not significantly different in US (0.6/1000; 95% CI: 0.0, 1.3; p = 0.05) and European (1.9/1000; 95% CI: 0.3, 3.5; p = 0.02) settings ( p for subgroup difference = 0.15). For incremental recall rate, within-study differences between density subgroups differed by setting ( p < 0.001). Pooled incremental recall was less in high- versus low-density screens (−0.9%; 95% CI: −1.4%, −0.4%; p < 0.001) in US screening, and greater (0.8%; 95% CI: 0.3%, 1.3%; p = 0.001) in European screening.

          Conclusions

          DBT has differential incremental cancer detection and recall by breast density. Although incremental CDR is greater in high-density, a substantial proportion of additional cancers is likely to be detected in low-density screens. Our findings may assist screening programmes considering DBT for density-tailored screening.

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          Most cited references38

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

          David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
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            QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

            In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
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              Breast cancer screening using tomosynthesis in combination with digital mammography.

              Mammography plays a key role in early breast cancer detection. Single-institution studies have shown that adding tomosynthesis to mammography increases cancer detection and reduces false-positive results. To determine if mammography combined with tomosynthesis is associated with better performance of breast screening programs in the United States. Retrospective analysis of screening performance metrics from 13 academic and nonacademic breast centers using mixed models adjusting for site as a random effect. Period 1: digital mammography screening examinations 1 year before tomosynthesis implementation (start dates ranged from March 2010 to October 2011 through the date of tomosynthesis implementation); period 2: digital mammography plus tomosynthesis examinations from initiation of tomosynthesis screening (March 2011 to October 2012) through December 31, 2012. Recall rate for additional imaging, cancer detection rate, and positive predictive values for recall and for biopsy. A total of 454,850 examinations (n=281,187 digital mammography; n=173,663 digital mammography + tomosynthesis) were evaluated. With digital mammography, 29,726 patients were recalled and 5056 biopsies resulted in cancer diagnosis in 1207 patients (n=815 invasive; n=392 in situ). With digital mammography + tomosynthesis, 15,541 patients were recalled and 3285 biopsies resulted in cancer diagnosis in 950 patients (n=707 invasive; n=243 in situ). Model-adjusted rates per 1000 screens were as follows: for recall rate, 107 (95% CI, 89-124) with digital mammography vs 91 (95% CI, 73-108) with digital mammography + tomosynthesis; difference, -16 (95% CI, -18 to -14; P < .001); for biopsies, 18.1 (95% CI, 15.4-20.8) with digital mammography vs 19.3 (95% CI, 16.6-22.1) with digital mammography + tomosynthesis; difference, 1.3 (95% CI, 0.4-2.1; P = .004); for cancer detection, 4.2 (95% CI, 3.8-4.7) with digital mammography vs 5.4 (95% CI, 4.9-6.0) with digital mammography + tomosynthesis; difference, 1.2 (95% CI, 0.8-1.6; P < .001); and for invasive cancer detection, 2.9 (95% CI, 2.5-3.2) with digital mammography vs 4.1 (95% CI, 3.7-4.5) with digital mammography + tomosynthesis; difference, 1.2 (95% CI, 0.8-1.6; P < .001). The in situ cancer detection rate was 1.4 (95% CI, 1.2-1.6) per 1000 screens with both methods. Adding tomosynthesis was associated with an increase in the positive predictive value for recall from 4.3% to 6.4% (difference, 2.1%; 95% CI, 1.7%-2.5%; P < .001) and for biopsy from 24.2% to 29.2% (difference, 5.0%; 95% CI, 3.0%-7.0%; P < .001). Addition of tomosynthesis to digital mammography was associated with a decrease in recall rate and an increase in cancer detection rate. Further studies are needed to assess the relationship to clinical outcomes.
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                Author and article information

                Contributors
                t.li@sydney.edu.au
                Journal
                Br J Cancer
                Br J Cancer
                British Journal of Cancer
                Nature Publishing Group UK (London )
                0007-0920
                1532-1827
                28 March 2022
                28 March 2022
                1 July 2022
                : 127
                : 1
                : 116-125
                Affiliations
                [1 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, The Daffodil Centre, , The University of Sydney, a joint venture with Cancer Council New South Wales, ; Sydney, NSW Australia
                [2 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, School of Public Health, Faculty of Medicine and Health, , The University of Sydney, ; Sydney, NSW Australia
                [3 ]GRID grid.1032.0, ISNI 0000 0004 0375 4078, Curtin School of Population Health, , Curtin University, ; Bentley, WA Australia
                Author information
                http://orcid.org/0000-0003-4956-765X
                http://orcid.org/0000-0002-3641-952X
                Article
                1790
                10.1038/s41416-022-01790-x
                9276736
                35352019
                50f0f011-a0bd-4925-9e5e-6e8f07d401c1
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 25 September 2021
                : 27 February 2022
                : 8 March 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000925, Department of Health | National Health and Medical Research Council (NHMRC);
                Award ID: 1194410
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001026, National Breast Cancer Foundation (NBCF);
                Award ID: EC-21-001
                Award ID: IIRS-20-011
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Oncology & Radiotherapy
                cancer screening,cancer imaging,breast cancer
                Oncology & Radiotherapy
                cancer screening, cancer imaging, breast cancer

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