Grant Number:	5U01CA253911-05 Interpret this number
Primary Investigator:	Trentham-Dietz, Amy
Organization:	University Of Wisconsin-Madison
Project Title:	Comparative Modeling of Precision Breast Cancer Control Across the Translational Continuum
Fiscal Year:	2024

ABSTRACT The CISNET Breast Working Group (BWG) proposes innovative modeling research focused on new precision oncology paradigms that are expected to re-define breast cancer control best practices. We selected significant topics where modeling is suited to fill evidence gaps and facilitate clinical and policy translation. Unique components of our approach include modeling of absolute risk of disease accounting for multiple risk factors, addressing important comorbidities—specifically type 2 diabetes—that affect both disease risk and survival, exploring emerging biomarker-based approaches for screening, providing guidance regarding precision systemic treatments and their impact on quality of life in survivors, and investigating race disparities. The specific aims are to: 1) Evaluate the impact of novel precision screening approaches; 2) Evaluate the impact of precision treatment paradigms in the adjuvant, neo-adjuvant, and metastatic setting; 3) Synthesize Aims 1 and 2 to quantify the contributions of precision screening and precision treatment to US breast cancer mortality reductions; and 4) Provide evidence to guide interventions to reduce race disparities by quantifying multiple risk, screening, treatment, and survival factors that impact disparities. This scope of work would not be feasible without the availability of six distinctive BWG models: Dana Farber (D), Erasmus (E), Georgetown- Einstein (GE), MD Anderson (M), Stanford (S) and Wisconsin-Harvard (W). The aims encompass multiple RFA priority areas, and we have set aside Rapid Response funds to address remaining priority areas, support cross-cancer CISNET collaborations, and foster junior career enhancement. Each aim includes three or more model groups selected for their unique structure and includes outside collaborators and junior investigators. The models will share common inputs and provide a standard set of outcomes for benefits (e.g., distant recurrences and deaths avoided, mortality reductions, distant disease-free survival, and life years and quality- adjusted life years), harms (e.g., false positives and benign biopsies, interval cancers, advanced stage diagnoses, overdiagnosis and treatment impact on quality of life), and costs. Continuously funded for the past 19 years, the modeling teams have published 204 research papers informing public health policy decisions and trained 13 junior investigators. For this proposal, the BWG will partner with the American Cancer Society, the American College of Radiology, the American Society of Clinical Oncology, the Breast Cancer Surveillance Consortium, and others. An experienced Coordinating Center provides the infrastructure to support the project goals including resource sharing and model accessibility. The exceptional environment provides unprecedented synergy and leveraging of resources to address new research questions and support career development that would not otherwise be possible. Overall, this research will advance modeling research and guide breast cancer control policy.




The population-level effects of omitting chemotherapy guided by a 21-gene expression assay in node-positive breast cancer: a simulation modeling study.
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Source: Bmc Cancer, 2024-08-08 00:00:00.0; 24(1), p. 975.
EPub date: 2024-08-08 00:00:00.0.
PMID: 39118050
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Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.
Authors: Trentham-Dietz A. , Chapman C.H. , Jayasekera J. , Lowry K.P. , Heckman-Stoddard B.M. , Hampton J.M. , Caswell-Jin J.L. , Gangnon R.E. , Lu Y. , Huang H. , et al. .
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EPub date: 2024-04-30 00:00:00.0.
PMID: 38687505
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Analysis of Breast Cancer Mortality in the US-1975 to 2019.
Authors: Caswell-Jin J.L. , Sun L.P. , Munoz D. , Lu Y. , Li Y. , Huang H. , Hampton J.M. , Song J. , Jayasekera J. , Schechter C. , et al. .
Source: Jama, 2024-01-16 00:00:00.0; 331(3), p. 233-241.
PMID: 38227031
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Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study.
Authors: Jayasekera J. , Stein S. , Wilson O.W.A. , Wojcik K.M. , Kamil D. , Røssell E.L. , Abraham L.A. , O'Meara E.S. , Schoenborn N.L. , Schechter C.B. , et al. .
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Using simulation modeling to guide policy to reduce disparities and achieve equity in cancer outcomes: state of the science and a road map for the future.
Authors: Mandelblatt J. , Meza R. , Trentham-Dietz A. , Heckman-Stoddard B. , Feuer E. .
Source: Journal Of The National Cancer Institute. Monographs, 2023-11-08 00:00:00.0; 2023(62), p. 159-166.
PMID: 37947330
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Data gaps and opportunities for modeling cancer health equity.
Authors: Trentham-Dietz A. , Corley D.A. , Del Vecchio N.J. , Greenlee R.T. , Haas J.S. , Hubbard R.A. , Hughes A.E. , Kim J.J. , Kobrin S. , Li C.I. , et al. .
Source: Journal Of The National Cancer Institute. Monographs, 2023-11-08 00:00:00.0; 2023(62), p. 246-254.
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Opportunities, challenges, and future directions for simulation modeling the effects of structural racism on cancer mortality in the United States: a scoping review.
Authors: Jayasekera J. , El Kefi S. , Fernandez J.R. , Wojcik K.M. , Woo J.M.P. , Ezeani A. , Ish J.L. , Bhattacharya M. , Ogunsina K. , Chang C.J. , et al. .
Source: Journal Of The National Cancer Institute. Monographs, 2023-11-08 00:00:00.0; 2023(62), p. 231-245.
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Population simulation modeling of disparities in US breast cancer mortality.
Authors: Mandelblatt J.S. , Schechter C.B. , Stout N.K. , Huang H. , Stein S. , Hunter Chapman C. , Trentham-Dietz A. , Jayasekera J. , Gangnon R.E. , Hampton J.M. , et al. .
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PMID: 37947337
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A health equity framework to support the next generation of cancer population simulation models.
Authors: Chapman C. , Jayasekera J. , Dash C. , Sheppard V. , Mandelblatt J. .
Source: Journal Of The National Cancer Institute. Monographs, 2023-11-08 00:00:00.0; 2023(62), p. 255-264.
PMID: 37947339
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Estimated US Cancer Deaths Prevented With Increased Use of Lung, Colorectal, Breast, and Cervical Cancer Screening.
Authors: Knudsen A.B. , Trentham-Dietz A. , Kim J.J. , Mandelblatt J.S. , Meza R. , Zauber A.G. , Castle P.E. , Feuer E.J. .
Source: Jama Network Open, 2023-11-01 00:00:00.0; 6(11), p. e2344698.
EPub date: 2023-11-01 00:00:00.0.
PMID: 37991759
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Breast cancer risk for women with diabetes and the impact of metformin: A meta-analysis.
Authors: Lu Y. , Hajjar A. , Cryns V.L. , Trentham-Dietz A. , Gangnon R.E. , Heckman-Stoddard B.M. , Alagoz O. .
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PMID: 36533539
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Reassessing the Benefits and Harms of Risk-Reducing Medication Considering the Persistent Risk of Breast Cancer Mortality in Estrogen Receptor-Positive Breast Cancer.
Authors: Jayasekera J. , Zhao A. , Schechter C. , Lowry K. , Yeh J.M. , Schwartz M.D. , O'Neill S. , Wernli K.J. , Stout N. , Mandelblatt J. , et al. .
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A flexible-hazards cure model with application to patients with soft tissue sarcoma.
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Optimal breast cancer risk reduction policies tailored to personal risk level.
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Source: Health Care Management Science, 2022 Sep; 25(3), p. 363-388.
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The Early Detection of Breast Cancer Using Liquid Biopsies: Model Estimates of the Benefits, Harms, and Costs.
Authors: van der Poort E.K.J. , van Ravesteyn N.T. , van den Broek J.J. , de Koning H.J. .
Source: Cancers, 2022-06-15 00:00:00.0; 14(12), .
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A new perspective on breast cancer diagnostic guidelines to reduce overdiagnosis.
Authors: Tunç S. , Alagoz O. , Burnside E.S. .
Source: Production And Operations Management, 2022 May; 31(5), p. 2361-2378.
EPub date: 2022-03-08 00:00:00.0.
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Breast Cancer Screening Strategies for Women With ATM, CHEK2, and PALB2 Pathogenic Variants: A Comparative Modeling Analysis.
Authors: Lowry K.P. , Geuzinge H.A. , Stout N.K. , Alagoz O. , Hampton J. , Kerlikowske K. , de Koning H.J. , Miglioretti D.L. , van Ravesteyn N.T. , Schechter C. , et al. .
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Breast Cancer Screening Among Childhood Cancer Survivors Treated Without Chest Radiation: Clinical Benefits and Cost-Effectiveness.
Authors: Yeh J.M. , Lowry K.P. , Schechter C.B. , Diller L.R. , O'Brien G. , Alagoz O. , Armstrong G.T. , Hampton J.M. , Hudson M.M. , Leisenring W. , et al. .
Source: Journal Of The National Cancer Institute, 2022-02-07 00:00:00.0; 114(2), p. 235-244.
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Source: Current Epidemiology Reports, 2022; 9(1), p. 1-9.
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Simulation modeling of breast cancer endocrine therapy duration by patient and tumor characteristics.
Authors: Chandler Y. , Schechter C. , Jayasekera J. , Isaacs C. , Kurian A.W. , Cadham C. , Mandelblatt J. .
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Identifying Equitable Screening Mammography Strategies for Black Women in the United States Using Simulation Modeling.
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Source: Annals Of Internal Medicine, 2021 12; 174(12), p. 1637-1646.
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Impact of the COVID-19 Pandemic on Breast Cancer Mortality in the US: Estimates From Collaborative Simulation Modeling.
Authors: Alagoz O. , Lowry K.P. , Kurian A.W. , Mandelblatt J.S. , Ergun M.A. , Huang H. , Lee S.J. , Schechter C.B. , Tosteson A.N.A. , Miglioretti D.L. , et al. .
Source: Journal Of The National Cancer Institute, 2021-11-02 00:00:00.0; 113(11), p. 1484-1494.
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Recent Changes in the Patterns of Breast Cancer as a Proportion of All Deaths according to Race and Ethnicity.
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Source: Epidemiology (cambridge, Mass.), 2021-06-21 00:00:00.0; , .
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Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.
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Source: Journal Of The National Cancer Institute, 2020-08-27 00:00:00.0; , .
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Authors: Yeh J.M. , Lowry K.P. , Schechter C.B. , Diller L.R. , Alagoz O. , Armstrong G.T. , Hampton J.M. , Leisenring W. , Liu Q. , Mandelblatt J.S. , et al. .
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Long-term Outcomes and Cost-effectiveness of Breast Cancer Screening with Digital Breast Tomosynthesis in the United States.
Authors: Lowry K.P. , Trentham-Dietz A. , Schechter C.B. , Alagoz O. , Barlow W.E. , Burnside E.S. , Conant E.F. , Hampton J.M. , Huang H. , Kerlikowske K. , et al. .
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Authors: Mariotto A. , Jayasekerea J. , Petkov V. , Schechter C.B. , Enewold L. , Helzlsouer K.J. , Feuer E.J. , Mandelblatt J.S. .
Source: Journal Of The National Cancer Institute, 2019-04-24 00:00:00.0; , .
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