3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Prioritizing Screening Mammograms for Immediate Interpretation and Diagnostic Evaluation on the Basis of Risk for Recall

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Purpose:

          The aim of this study was to develop a prioritization strategy for scheduling immediate screening mammographic interpretation and possible diagnostic evaluation.

          Methods:

          A population-based cohort with screening mammograms performed from 2012 to 2020 at 126 radiology facilities from 7 Breast Cancer Surveillance Consortium registries was identified. Classification trees identified combinations of clinical history (age, BI-RADS ® density, time since prior mammogram, history of false-positive recall or biopsy result), screening modality (digital mammography, digital breast tomosynthesis), and facility characteristics (profit status, location, screening volume, practice type, academic affiliation) that grouped screening mammograms by recall rate, with ≥12/100 considered high and ≥16/100 very high. An efficiency ratio was estimated as the percentage of recalls divided by the percentage of mammograms.

          Results:

          The study cohort included 2,674,051 screening mammograms in 925,777 women, with 235,569 recalls. The most important predictor of recall was time since prior mammogram, followed by age, history of false-positive recall, breast density, history of benign biopsy, and screening modality. Recall rates were very high for baseline mammograms (21.3/100; 95% confidence interval, 19.7–23.0) and high for women with ≥5 years since prior mammogram (15.1/100; 95% confidence interval, 14.3–16.1). The 9.2% of mammograms in subgroups with very high and high recall rates accounted for 19.2% of recalls, an efficiency ratio of 2.1 compared with a random approach. Adding women <50 years of age with dense breasts accounted for 20.3% of mammograms and 33.9% of recalls (efficiency ratio = 1.7). Results including facility-level characteristics were similar.

          Conclusions:

          Prioritizing women with baseline mammograms or ≥5 years since prior mammogram for immediate interpretation and possible diagnostic evaluation could considerably reduce the number of women needing to return for diagnostic imaging at another visit.

          Related collections

          Most cited references42

          • Record: found
          • Abstract: not found
          • Article: not found

          Random Forests

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Longitudinal data analysis using generalized linear models

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium.

              Purpose To establish performance benchmarks for modern screening digital mammography and assess performance trends over time in U.S. community practice. Materials and Methods This HIPAA-compliant, institutional review board-approved study measured the performance of digital screening mammography interpreted by 359 radiologists across 95 facilities in six Breast Cancer Surveillance Consortium (BCSC) registries. The study included 1 682 504 digital screening mammograms performed between 2007 and 2013 in 792 808 women. Performance measures were calculated according to the American College of Radiology Breast Imaging Reporting and Data System, 5th edition, and were compared with published benchmarks by the BCSC, the National Mammography Database, and performance recommendations by expert opinion. Benchmarks were derived from the distribution of performance metrics across radiologists and were presented as 50th (median), 10th, 25th, 75th, and 90th percentiles, with graphic presentations using smoothed curves. Results Mean screening performance measures were as follows: abnormal interpretation rate (AIR), 11.6 (95% confidence interval [CI]: 11.5, 11.6); cancers detected per 1000 screens, or cancer detection rate (CDR), 5.1 (95% CI: 5.0, 5.2); sensitivity, 86.9% (95% CI: 86.3%, 87.6%); specificity, 88.9% (95% CI: 88.8%, 88.9%); false-negative rate per 1000 screens, 0.8 (95% CI: 0.7, 0.8); positive predictive value (PPV) 1, 4.4% (95% CI: 4.3%, 4.5%); PPV2, 25.6% (95% CI: 25.1%, 26.1%); PPV3, 28.6% (95% CI: 28.0%, 29.3%); cancers stage 0 or 1, 76.9%; minimal cancers, 57.7%; and node-negative invasive cancers, 79.4%. Recommended CDRs were achieved by 92.1% of radiologists in community practice, and 97.1% achieved recommended ranges for sensitivity. Only 59.0% of radiologists achieved recommended AIRs, and only 63.0% achieved recommended levels of specificity. Conclusion The majority of radiologists in the BCSC surpass cancer detection recommendations for screening mammography; however, AIRs continue to be higher than the recommended rate for almost half of radiologists interpreting screening mammograms. (©) RSNA, 2016 Online supplemental material is available for this article.
                Bookmark

                Author and article information

                Journal
                101190326
                33174
                J Am Coll Radiol
                J Am Coll Radiol
                Journal of the American College of Radiology : JACR
                1546-1440
                1558-349X
                22 March 2023
                March 2023
                20 October 2022
                28 March 2023
                : 20
                : 3
                : 299-310
                Affiliations
                [a ]Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, School of Medicine, Davis, California.
                [b ]Breast Imaging Unit, Diagnostic Imaging Center, Tam Anh General Hospital, Ho Chi Minh City, Vietnam.
                [c ]Department of Training and Scientific Research, University Medical Center, Ho Chi Minh City, Vietnam.
                [d ]Breast Imaging, Department of Radiology, University of Washington School of Medicine, Seattle, Washington.
                [e ]Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, Washington.
                [f ]Hutchinson Institute for Cancer Outcomes Research, Seattle, Washington.
                [g ]Breast Imaging, Fred Hutchinson Cancer Center, Seattle, Washington.
                [h ]Northwest Screening and Cancer Outcomes Research Enterprise, University of Washington, Seattle, Washington.
                [i ]Deputy Editor, JACR.
                [j ]Department of Surgery, Office of Health Promotion Research, Larner College of Medicine at the University of Vermont and Co-Leader, Cancer Control and Population Health Sciences Program, University of Vermont Cancer Center, Burlington, Vermont.
                [k ]The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth and Associate Director for Population Sciences, Dartmouth Cancer Center, Lebanon, New Hampshire.
                [l ]Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California.
                [m ]Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington.
                [n ]Department of Radiology, University of North Carolina, Chapel Hill, North Carolina.
                [o ]Cancer Epidemiology Program, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina.
                [p ]Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.
                [q ]General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, San Francisco, California.
                [r ]Women’s Health Comprehensive Clinic, and Director, Advanced Post-doctoral Fellowship in Women’s Health, San Francisco Veterans Affairs Health Care System, San Francisco, California.
                [s ]Biostatistics and Population Sciences and Health Disparities Program, University of California, Davis, Comprehensive Cancer Center, Davis, California.
                Author notes

                Drs Ho and Bissell contributed equally to this work.

                Corresponding author and reprints: Diana L. Miglioretti, PhD, Department of Public Health Sciences, UC Davis School of Medicine, One Shields Avenue, Med Sci 1C, Davis, CA 95616; dmiglioretti@ 123456ucdavis.edu .
                Article
                NIHMS1884484
                10.1016/j.jacr.2022.09.030
                10044471
                36273501
                ed41593a-1c40-4e41-8123-e6b853456605

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Categories
                Article

                screening mammography,recall rate,immediate interpretation,breast cancer surveillance consortium

                Comments

                Comment on this article