TY - JOUR
T1 - Association of screening and treatment with breast cancer mortality by molecular subtype in US women, 2000-2012
AU - Plevritis, Sylvia K.
AU - Munoz, Diego
AU - Kurian, Allison W.
AU - Stout, Natasha K.
AU - Alagoz, Oguzhan
AU - Near, Aimee M.
AU - Lee, Sandra J.
AU - Van Den Broek, Jeroen J.
AU - Huang, Xuelin
AU - Schechter, Clyde B.
AU - Sprague, Brian L.
AU - Song, Juhee
AU - De Koning, Harry J.
AU - Trentham-Dietz, Amy
AU - Van Ravesteyn, Nicolien T.
AU - Gangnon, Ronald
AU - Chandler, Young
AU - Li, Yisheng
AU - Xu, Cong
AU - Ali Ergun, Mehmet
AU - Huang, Hui
AU - Berry, Donald A.
AU - Mandelblatt, Jeanne S.
N1 - Funding Information:
Funding/Support: This work was supported by grant U01 CA152958 from the National Cancer Institute of the National Institutes of Health, in part by grant MRSG 14-027-01 CPHPS from the American Cancer Society (Dr Chandler). The Collection of Breast Cancer Surveillance Consortium (BCSC) data used in this study was supported by grants P01CA154292 and U54CA163303 and contract HHSN261201100031C from the National Cancer Institute. The collection of cancer and vital status data from the BCSC was supported in part by several state public health departments and cancer registries throughout the United States. For a full description of these sources, please see http://www.bcsc-research.org /work/acknowledgement.html.
Funding Information:
Author Affiliations: Departments of Radiology and Biomedical Data Science, School of Medicine, Stanford University, Stanford, California (Plevritis, Munoz, Xu); Departments of Medicine and Health Research and Policy, School of Medicine, Stanford University, Stanford, California (Kurian); Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (Stout); Department of Industrial and Systems Engineering, University of Wisconsin-Madison (Alagoz, Ergun); Carbone Cancer Center, University of Wisconsin-Madison (Alagoz, Trentham-Dietz, Gangnon); Department of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (Near, Chandler, Mandelblatt); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (Lee, H. Huang); Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands (van den Broek, de Koning, van Ravesteyn); Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston (X. Huang, Song, Li, Berry); Departments of Family and Social Medicine and Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York (Schechter); Department of Surgery, College of Medicine, University of Vermont, Burlington (Sprague); Department of Biostatistics and Medical Informatics and Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health (Gangnon).
Funding Information:
Funding/Support: This work was supported by grant U01 CA152958 from the National Cancer Institute of the National Institutes of Health, in part by grant MRSG 14-027-01 CPHPS from the American Cancer Society (Dr Chandler). The Collection of Breast Cancer Surveillance Consortium (BCSC) data used in this study was supported by grants P01CA154292 and U54CA163303 and contract HHSN261201100031C from the National Cancer Institute. The collection of cancer and vital status data from the BCSC was supported in part by several state public health departments and cancer registries throughout the United States. For a full description of these sources, please see http://www.bcsc-research.org/work/acknowledgement.html.
Funding Information:
Dr Plevritis reported consulting for GRAIL. Dr Alagoz reported consulting for Renaissance Rx and Ally Clinical Diagnostics. Dr de Koning reported receiving grant funding from the Dutch National Institute for Public Health and the Environment and SCOR Global. Dr Berry reported being the co-owner of Berry Consultants. No other disclosures were reported.
PY - 2018/1/9
Y1 - 2018/1/9
N2 - IMPORTANCE Given recent advances in screening mammography and adjuvant therapy (treatment), quantifying their separate and combined effects on US breast cancer mortality reductions by molecular subtype could guide future decisions to reduce disease burden. OBJECTIVE To evaluate the contributions associated with screening and treatment to breast cancer mortality reductions by molecular subtype based on estrogen-receptor (ER) and human epidermal growth factor receptor 2 (ERBB2, formerly HER2 or HER2/neu). DESIGN, SETTING, AND PARTICIPANTS Six Cancer Intervention and Surveillance Network (CISNET) models simulated US breast cancer mortality from 2000 to 2012 using national data on plain-film and digital mammography patterns and performance, dissemination and efficacy of ER/ERBB2-specific treatment, and competing mortality. Multiple US birth cohorts were simulated. EXPOSURES Screening mammography and treatment. MAIN OUTCOMES AND MEASURES The models compared age-adjusted, overall, and ER/ERBB2-specific breast cancer mortality rates from 2000 to 2012 for women aged 30 to 79 years relative to the estimated mortality rate in the absence of screening and treatment (baseline rate); mortality reductions were apportioned to screening and treatment. RESULTS In 2000, the estimated reduction in overall breast cancer mortality rate was 37% (model range, 27%-42%) relative to the estimated baseline rate in 2000 of 64 deaths (model range, 56-73) per 100 000 women: 44% (model range, 35%-60%) of this reduction was associated with screening and 56% (model range, 40%-65%) with treatment. In 2012, the estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%-58%) relative to the estimated baseline rate in 2012 of 63 deaths (model range, 54-73) per 100 000 women: 37% (model range, 26%-51%) of this reduction was associated with screening and 63% (model range, 49%-74%) with treatment. Of the 63% associated with treatment, 31% (model range, 22%-37%) was associated with chemotherapy, 27% (model range, 18%-36%) with hormone therapy, and 4% (model range, 1%-6%) with trastuzumab. The estimated relative contributions associated with screening vs treatment varied by molecular subtype: for ER+/ERBB2?, 36% (model range, 24%-50%) vs 64% (model range, 50%-76%); for ER+/ERBB2+, 31% (model range, 23%-41%) vs 69% (model range, 59%-77%); for ER?/ERBB2+, 40% (model range, 34%-47%) vs 60% (model range, 53%-66%); and for ER?/ERBB2?, 48% (model range, 38%-57%) vs 52% (model range, 44%-62%). CONCLUSIONS AND RELEVANCE In this simulation modeling study that projected trends in breast cancer mortality rates among US women, decreases in overall breast cancer mortality from 2000 to 2012 were associated with advances in screening and in adjuvant therapy, although the associations varied by breast cancer molecular subtype.
AB - IMPORTANCE Given recent advances in screening mammography and adjuvant therapy (treatment), quantifying their separate and combined effects on US breast cancer mortality reductions by molecular subtype could guide future decisions to reduce disease burden. OBJECTIVE To evaluate the contributions associated with screening and treatment to breast cancer mortality reductions by molecular subtype based on estrogen-receptor (ER) and human epidermal growth factor receptor 2 (ERBB2, formerly HER2 or HER2/neu). DESIGN, SETTING, AND PARTICIPANTS Six Cancer Intervention and Surveillance Network (CISNET) models simulated US breast cancer mortality from 2000 to 2012 using national data on plain-film and digital mammography patterns and performance, dissemination and efficacy of ER/ERBB2-specific treatment, and competing mortality. Multiple US birth cohorts were simulated. EXPOSURES Screening mammography and treatment. MAIN OUTCOMES AND MEASURES The models compared age-adjusted, overall, and ER/ERBB2-specific breast cancer mortality rates from 2000 to 2012 for women aged 30 to 79 years relative to the estimated mortality rate in the absence of screening and treatment (baseline rate); mortality reductions were apportioned to screening and treatment. RESULTS In 2000, the estimated reduction in overall breast cancer mortality rate was 37% (model range, 27%-42%) relative to the estimated baseline rate in 2000 of 64 deaths (model range, 56-73) per 100 000 women: 44% (model range, 35%-60%) of this reduction was associated with screening and 56% (model range, 40%-65%) with treatment. In 2012, the estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%-58%) relative to the estimated baseline rate in 2012 of 63 deaths (model range, 54-73) per 100 000 women: 37% (model range, 26%-51%) of this reduction was associated with screening and 63% (model range, 49%-74%) with treatment. Of the 63% associated with treatment, 31% (model range, 22%-37%) was associated with chemotherapy, 27% (model range, 18%-36%) with hormone therapy, and 4% (model range, 1%-6%) with trastuzumab. The estimated relative contributions associated with screening vs treatment varied by molecular subtype: for ER+/ERBB2?, 36% (model range, 24%-50%) vs 64% (model range, 50%-76%); for ER+/ERBB2+, 31% (model range, 23%-41%) vs 69% (model range, 59%-77%); for ER?/ERBB2+, 40% (model range, 34%-47%) vs 60% (model range, 53%-66%); and for ER?/ERBB2?, 48% (model range, 38%-57%) vs 52% (model range, 44%-62%). CONCLUSIONS AND RELEVANCE In this simulation modeling study that projected trends in breast cancer mortality rates among US women, decreases in overall breast cancer mortality from 2000 to 2012 were associated with advances in screening and in adjuvant therapy, although the associations varied by breast cancer molecular subtype.
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U2 - 10.1001/jama.2017.19130
DO - 10.1001/jama.2017.19130
M3 - Review article
C2 - 29318276
AN - SCOPUS:85040614501
SN - 0002-9955
VL - 319
SP - 154
EP - 164
JO - JAMA - Journal of the American Medical Association
JF - JAMA - Journal of the American Medical Association
IS - 2
ER -
