Diana L. Miglioretti, PhD; Jane Lange, PhD; Jeroen J. van den Broek, MSc; Christoph I. Lee, MD, MSHS; Nicolien T. van Ravesteyn, PhD; Dominique Ritley, MPH; Karla Kerlikowske, MD; Joshua J. Fenton, MD, MPH; Joy Melnikow, MD, MPH; Harry J. de Koning, PhD; Rebecca A. Hubbard, PhD
Disclaimer: The authors are responsible for study design, analysis and interpretation of the data, writing of the manuscript, and the decision to submit the manuscript for publication. The findings and conclusions in this article are those of the authors, who are responsible for its contents, and do not necessarily represent the views of the funding sources.
Acknowledgment: The authors thank Benjamin Herman, PhD, at the American College of Radiology Imaging Network coordinating center for providing the DMIST data and helping with data interpretation; John Boone, PhD, Professor and Vice Chair of Radiology and Professor of Biomedical Engineering at the University of California, Davis, Medical Center, for helpful input and suggestions on our modeling strategy; Chris Tachibana, PhD, from the Group Health Research Institute for scientific editing; and an anonymous reviewer from the American College of Radiology Imaging Network for his/her comments on an earlier draft.
Grant Support: By the Agency for Healthcare Research and Quality (grant HHSA-290-2012-00015I), U.S. Preventive Services Task Force, and National Cancer Institute (grants P01CA154292, 5U01CA152958, and R03CA182986). Collection of mammography data was supported by the BCSC, which is funded by the National Cancer Institute (grants P01CA154292, HHSN261201100031C, and U54CA163303). The collection of BCSC data was supported in part by several state public health departments and cancer registries throughout the United States. For a full description of these sources, visit http://breastscreening.cancer.gov/work/acknowledgement.html. Primary research and data collection for the American College of Radiology Imaging Network DMIST were supported by the National Cancer Institute (grants U01 CA80098, U01 CA80098-S1, U01 CA79778, and U01 79778-S1).
Disclosures: Dr. Miglioretti reports grants from the Agency for Healthcare Research and Quality and National Cancer Institute during the conduct of the study. Dr. Lee reports grants and personal fees from GE Healthcare outside the submitted work. Dr. van Ravesteyn reports grants from the National Cancer Institute, National Institutes of Health, during the conduct of the study. Dr. Melnikow reports other from the Agency for Healthcare Research and Quality during the conduct of the study. Dr. Hubbard reports grants from the National Institutes of Health during the conduct of the study. Authors not named here have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOf InterestForms.do?msNum=M15-1241.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer.
Reproducible Research Statement:Study protocol: Available from Dr. Miglioretti (e-mail, firstname.lastname@example.org). Statistical code: The statistical code for the MISCAN-Fadia model is not available. The other statistical code is available from the BCSC's statistical coordinating center (e-mail, SCC@ghc.org). Data set: The BCSC data set is available with approval of the BCSC Steering Committee (http://breastscreening.cancer.gov).
Requests for Single Reprints: Diana L. Miglioretti, PhD, Department of Public Health Sciences, University of California, Davis School of Medicine, One Shields Avenue, Medical Science Building 1C, Room 144, Davis, CA 95616; e-mail, email@example.com.
Current Author Addresses: Dr. Miglioretti: Department of Public Health Sciences, University of California, Davis School of Medicine, One Shields Avenue, Medical Science Building 1C, Room 144, Davis, CA 95616.
Dr. Lange: Group Health Research Institute, 1730 Minor Avenue, Suite 1600, Seattle, WA 98101.
Mr. van den Broek and Drs. van Ravesteyn and de Koning: Department of Public Health, Erasmus MC University Medical Center Rotterdam, PO Box 2040, 3000 CA Rotterdam, The Netherlands.
Dr. Lee: Department of Radiology, University of Washington School of Medicine, 825 Eastlake Avenue East, G3-200, Seattle, WA 98109.
Ms. Ritley and Drs. Fenton and Melnikow: Center for Healthcare Policy and Research, University of California, Davis, 2103 Stockton Boulevard, Sacramento, CA 95817.
Dr. Kerlikowske: General Internal Medicine Section, San Francisco Veterans Affairs Medical Center, 111A1, 4150 Clement Street, San Francisco, CA 94121.
Dr. Hubbard: Department of Biostatistics & Epidemiology, University of Pennsylvania, 604 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021.
Author Contributions: Conception and design: D.L. Miglioretti, H.J. de Koning, R.A. Hubbard.
Analysis and interpretation of the data: D.L. Miglioretti, J.J. van den Broek, C.I. Lee, N.T. van Ravesteyn, K. Kerlikowske, J.J. Fenton, J. Melnikow, H.J. de Koning, R.A. Hubbard.
Drafting of the article: J. Lange, C.I. Lee, D. Ritley, K. Kerlikowske.
Critical revision of the article for important intellectual content: D.L. Miglioretti, J. Lange, J.J. van den Broek, C.I. Lee, N.T. van Ravesteyn, D. Ritley, K. Kerlikowske, J.J. Fenton, J. Melnikow, H.J. de Koning, R.A. Hubbard.
Final approval of the article: D.L. Miglioretti, J. Lange, J.J. van den Broek, C.I. Lee, N.T. van Ravesteyn, D. Ritley, K. Kerlikowske, J.J. Fenton, J. Melnikow, H.J. de Koning, R.A. Hubbard.
Statistical expertise: D.L. Miglioretti, J. Lange, J.J. van den Broek, H.J. de Koning, R.A. Hubbard.
Obtaining of funding: D.L. Miglioretti, K. Kerlikowske, H.J. de Koning, R.A. Hubbard.
Administrative, technical, or logistic support: D. Ritley.
Collection and assembly of data: J. Lange, J.J. van den Broek, C.I. Lee.
Estimates of risk for radiation-induced breast cancer from mammography screening have not considered variation in dose exposure or diagnostic work-up after abnormal screening results.
To estimate distributions of radiation-induced breast cancer incidence and mortality from digital mammography screening while considering exposure from screening and diagnostic mammography and dose variation among women.
2 simulation-modeling approaches.
Women aged 40 to 74 years.
Annual or biennial digital mammography screening from age 40, 45, or 50 years until age 74 years.
Lifetime breast cancer deaths averted (benefits) and radiation-induced breast cancer incidence and mortality (harms) per 100 000 women screened.
Annual screening of 100 000 women aged 40 to 74 years was projected to induce 125 breast cancer cases (95% CI, 88 to 178) leading to 16 deaths (CI, 11 to 23), relative to 968 breast cancer deaths averted by early detection from screening. Women exposed at the 95th percentile were projected to develop 246 cases of radiation-induced breast cancer leading to 32 deaths per 100 000 women. Women with large breasts requiring extra views for complete examination (8% of population) were projected to have greater radiation-induced breast cancer risk (266 cancer cases and 35 deaths per 100 000 women) than other women (113 cancer cases and 15 deaths per 100 000 women). Biennial screening starting at age 50 years reduced risk for radiation-induced cancer 5-fold.
Life-years lost from radiation-induced breast cancer could not be estimated.
Radiation-induced breast cancer incidence and mortality from digital mammography screening are affected by dose variability from screening, resultant diagnostic work-up, initiation age, and screening frequency. Women with large breasts may have a greater risk for radiation-induced breast cancer.
Agency for Healthcare Research and Quality, U.S. Preventive Services Task Force, National Cancer Institute.
Repeated digital mammography examinations expose women to ionizing radiation that can increase breast cancer risk.
This modeling study found that annual mammography screening of 100 000 women aged 40 to 74 years might induce 125 breast cancer cases and 16 deaths but avert 968 breast cancer deaths because of early detection. Factors associated with increased risk for radiation-induced cancer included large breasts requiring extra views, higher-than-average doses per view, beginning screening at younger ages, and annual screening.
The model had several assumptions.
Biennial mammography screening starting at age 50 years and use of the fewest number of views possible would decrease risk for radiation-induced breast cancer.
Schematic of 2 modeling approaches used to simulate mammography events and outcomes associated with 8 screening strategies.
Estimates of the number of screening examinations and false-positive results from the MISCAN-Fadia model were combined with the mean radiation dose from the radiation exposure model to estimate mean incidence of radiation-induced breast cancer. Estimates of the probability distribution of cumulative radiation dose at each age among women from the radiation exposure model were used to estimate the probability distribution of radiation-induced breast cancer incidence. Radiation-induced breast cancer incidence was combined with breast cancer survival estimates from the MISCAN-Fadia model to estimate radiation-induced breast cancer mortality. BCSC = Breast Cancer Surveillance Consortium; DMIST = Digital Mammographic Imaging Screening Trial; MISCAN-Fadia = Microsimulation of Screening Analysis–Fatal Diameter.
Appendix Table 1. Distribution of Compressed Breast Thickness on Digital Mammography From ACRIN DMIST*
Appendix Table 2. Prevalence of BI-RADS Breast Density (by Age) and Probability of Changing Density Category at Age 50 and 65 Years, Estimated From the Breast Cancer Surveillance Consortium*
Screening mammography process.
SIFU examinations included unilateral diagnostic views on the recalled breast at 6 mo after the initial SIFU recommendation. The examinations included unilateral diagnostic views on the recalled breast plus bilateral routine screening views at 12 and 24 mo after the initial SIFU recommendation for women who received annual screening and 24 mo after the initial SIFU recommendation for those who received biennial screening. The routine screening views could result in recall for additional imaging to work up a new finding, followed by a recommendation for another SIFU examination or tissue biopsy. SIFU = short-interval follow-up.
Appendix Table 3. Distribution of the Number of Screening Mammography Views From ACRIN DMIST
Appendix Table 4. Number of Plain and Magnification Mammography Views, by Examination or Procedure Type and Breast Size, Estimated From ACRIN DMIST and Expert Opinion, and Percentage of Women With That Number of Views, Where Applicable
Distribution of absorbed glandular (breast) dose of a single screening mammography view, by compressed breast thickness from DMIST.
The boxes show the middle 50% of the data, which is the interquartile range. The horizontal lines within the boxes correspond to the median, and the plus symbols correspond to the mean. The whiskers go out 1.5 box widths or to the last point inside that range. Circles represent values outside the whiskers and are potential outliers. DMIST = Digital Mammographic Imaging Screening Trial.
Appendix Table 5. Distribution of Number of Mammography Views and Radiation Dose From Each Screening Examination and All Follow-up Mammographies and Biopsies Within 1 Year of an Examination for Women Receiving Annual Screening From Age 40 to 74 Years
Table 1. Comparison of Lifetime Attributable Risks for Radiation-Induced Breast Cancer and Breast Cancer Death From 2 Modeling Approaches*
Table 2. Lifetime Attributable Risks for Radiation-Induced Breast Cancer and Breast Cancer Death for Different Screening Strategies, by Breast Size*
Table 3. Number of Breast Cancer Deaths Averted by Screening 100 000 Women and Number of Breast Cancer Deaths Averted per Case of and Death From Radiation-Induced Breast Cancer*
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William T. Phillips, Ralph Blumhardt
University of Texas Health Science Center at San Antonio
March 4, 2016
Radiation-Induced Breast Cancer?
We read with interest your recent issue (16 Feb 2016) devoted to breast cancer. We are concerned that women reading the article by Miglioretti et. al may choose not to have screening mammography due to fears of radiation-induced breast cancer. This issue also contains an editorial article entitled "Time to Douse the Firestorm Around Breast Cancer Screening" (1) that states "women deserve to be aware of what the science says so they can make the best choice for themselves, together with their doctor." So, what is the science behind screening with mammography? On the positive side of the issue, women age 50-69 undergoing screening mammography have a 25% to 31% relative reduction in mortality from breast cancer (2). We take issue with the negative side, particularly, the idea that patients are subject to significant cancer risk from screening mammograms. Although we agree that there is an increased incidence of radiation induced cancer in patients who have undergone therapeutic radiation, there is little evidence to support the view that diagnostic radiology exams cause a significant increased incidence of secondary cancer.
Diana L. Miglioretti, PhD, Christoph I. Lee, MD
University of California, Davis, University of Washington
July 6, 2016
We agree with the authors that the benefit of reduced breast cancer mortality associated with guideline-based screening mammography outweighs the risks of radiation-induced breast cancer, as stated in our article.1 Likewise, we also hope women do not forgo mammography due to fears of radiation-induced breast cancer; however, that is not a valid reason to not estimate and report these risks. Radiation exposure from mammography screening is a potential harm, even if a relatively small one, that should be considered when evaluating the benefit-harm tradeoff of different screening strategies. To model breast cancer risk from radiation exposure, we used the excess absolute risk model from pooled analysis of four cohorts by Preston et al.2, which is the model preferred by the BEIR-VII committee.3 Women in these cohorts were exposed to cumulative radiation doses to the breast of 20 mGy and higher. This level of exposure is reached after two to four rounds of mammography screening and associated diagnostic work-up; thus, our projections are not extrapolated beyond the range of data used for model development. Recent, updated analyses of atomic bomb survivors provide additional evidence of breast cancer risk from exposures in this dose range.4 They found that cancer risk increased linearly with increasing dose, and a formal dose-threshold analysis found no evidence of a threshold below which there was no increased cancer risk. Our study explored variation in radiation-induced cancer risk across women due to variation in radiation dose per view and additional imaging performed to evaluate abnormal screening results. We found that some women, e.g., women with large breasts, are receiving much higher radiation doses than previously recognized due to receiving extra views at each exam and higher doses per view. To minimize risks, radiology practices should ensure women with large breasts are imaged with large detectors and should minimize the number of additional views. There is no evidence that full disclosure of potential risks from cumulative radiation exposure would discourage women from obtaining screening mammography. In fact, the literature to date suggests that patients are not dissuaded from undergoing clinically indicated imaging exams when informed about associated radiation-induced cancer risks.5 In an era of greater transparency and shared-decision making, women want, and should be given, information about all of the potential benefits and risks of mammography screening in order to make a truly informed choice.Diana L. Miglioretti, PhDUniversity of California, DavisDivision of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis, CA 95616Group Health Research Institute, Seattle, WA 98101Christoph I. Lee, MD, MSHSDepartment of Radiology, University of Washington, Seattle, WADepartment of Health Services, University of Washington, Seattle, WAHutchinson Institute for Cancer Outcomes Research, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WAREFERENCES1. Miglioretti DL, Lange J, van den Broek JJ, Lee CI, van Ravesteyn NT, Ritley D, Kerlikowske K, Fenton JJ, Melnikow J, de Koning HJ, Hubbard RA. Radiation-Induced Breast Cancer Incidence and Mortality From Digital Mammography Screening: A Modeling Study. Ann Intern Med. 2016;164(4):205-14. PubMed PMID: 26756460.2. Preston DL, Mattsson A, Holmberg E, Shore R, Hildreth NG, Boice JD, Jr. Radiation effects on breast cancer risk: a pooled analysis of eight cohorts. Radiat Res. 2002;158(2):220-35. Epub 2002/07/11. PubMed PMID: 12105993.3. Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation and National Research Council. Health Risks from Exposure to Low Levels of Ionizing Radiation: BEIR VII Phase 2. Washington, D.C.: The National Academies Press; 2006.4. Ozasa K, Shimizu Y, Suyama A, Kasagi F, Soda M, Grant EJ, Sakata R, Sugiyama H, Kodama K. Studies of the mortality of atomic bomb survivors, Report 14, 1950-2003: an overview of cancer and noncancer diseases. Radiat Res. 2012;177(3):229-43. PubMed PMID: 22171960.5. Lam DL, Larson DB, Eisenberg JD, Forman HP, Lee CI. Communicating Potential Radiation-Induced Cancer Risks From Medical Imaging Directly to Patients. AJR Am J Roentgenol. 2015;205(5):962-70. Epub 2015/08/22. PubMed PMID: 26295534.
Miglioretti DL, Lange J, van den Broek JJ, Lee CI, van Ravesteyn NT, Ritley D, et al. Radiation-Induced Breast Cancer Incidence and Mortality From Digital Mammography Screening: A Modeling Study. Ann Intern Med. 2016;164:205–214. doi: 10.7326/M15-1241
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Published: Ann Intern Med. 2016;164(4):205-214.
Published at www.annals.org on 12 January 2016
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