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Comparative Modeling of Precision Breast Cancer Control Across the Translational Continuum

跨转化连续体的乳腺癌精准控制的比较模型

基本信息

批准号：
10674788
负责人：
Oguzhan Alagoz
金额：
$ 179.19万
依托单位：
UNIVERSITY OF WISCONSIN-MADISON
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10674788
关键词：
Accounting Address Adjusted Life Years Adjuvant Adverse effects Affect Age American Cancer Society American College of Radiology American Society of Clinical Oncology Area Basic Science Benchmarking Benign Biological Markers Biopsy Black race Breast Breast Cancer Risk Factor Breast Cancer Surveillance Consortium Breast Cancer therapy Cancer Biology Cancer Control Cancer Intervention and Surveillance Modeling Network Cardiomyopathies Centers for Disease Control and Prevention (U.S.)Cessation of life Chronic Chronic Disease Clinical Collaborations Complex Computer Models Diabetes Mellitus Diagnosis Disease Disease-Free Survival Distant Environment Equilibrium Fostering Funding Future Goals Guidelines Health Policy Hematologic Neoplasms Incidence Infrastructure Intervention Investigation Magnetic Resonance Imaging Malignant Neoplasms Mammary Gland Parenchyma Mammographic screening Mammography Mentors Modality Modeling Modernization Natural History Neoadjuvant Therapy Neuropathy Non-Insulin-Dependent Diabetes Mellitus Outcome Paper Performance Policies Positioning Attribute Precision therapeutics Public Health Publishing Quality of life Quality-Adjusted Life Years Race Recording of previous events Records Recurrence Recurrent Malignant Neoplasm Registries Research Research Personnel Resource Sharing Resources Risk Risk Factors Second Primary Cancers Structure Survivors Technology Testing Training Translations United States Preventative Services Task Force Variant Wisconsin Woman Work breast density breast imaging cancer care cancer recurrence career career development circulating biomarkers clinically relevant comorbidity comparative cost density disorder risk disparity reduction experience flexibility improved innovation liquid biopsy malignant breast neoplasm models and simulation molecular subtypes mortality mortality disparity novel novel strategies novel therapeutics outcome disparities personalized approach personalized screening policy recommendation precision oncology primary outcome programs racial disparity response screening synergism technological innovation translational oncology trend virtual laboratory working group

项目摘要

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.

摘要 CISNET乳腺工作组（BWG）提出了创新的建模研究，重点是新的精度肿瘤学范例，有望重新定义乳腺癌控制的最佳实践。我们选择重要的主题，其中建模适合填补证据空白，促进临床和政策翻译。我们的方法的独特组成部分包括建模的绝对风险的疾病占多种风险因素，解决重要的合并症-特别是2型糖尿病-影响疾病风险和生存，探索新兴的基于生物标志物的筛查方法，提供有关精确的系统治疗及其对幸存者生活质量的影响，并调查种族差异。具体目标是：1）评估新的精确筛选方法的影响; 2）评估精确治疗模式在辅助、新辅助和转移性环境中的影响; 3）目标1和2量化精确筛查和精确治疗对美国乳腺癌的贡献降低死亡率;以及4）提供证据，指导干预措施，通过量化影响差异的多种风险、筛查、治疗和生存因素。这一工作范围将不会可行的没有六个独特的BWG模型的可用性：达纳法伯（D），伊拉斯谟（E），乔治敦- 爱因斯坦（GE）、MD安德森（M）、斯坦福大学（S）和威斯康星-哈佛大学（W）。目标包括多种RFA 我们已拨出快速反应资金，以解决剩余的优先领域，跨癌症CISNET合作，并促进初级职业发展。每个目标包括三个或更多根据其独特的结构选择了示范小组，其中包括外部合作者和初级调查员。这些模型将共享共同的投入，并提供一套标准的效益结果（例如，遥远避免的复发和死亡、死亡率降低、无远处疾病生存率、生命年和质量- 调整生命年），危害（例如，假阳性和良性活检，间隔癌，晚期诊断，过度诊断和治疗对生活质量的影响）和成本。过去持续资助 19年来，建模团队发表了204篇研究论文，为公共卫生政策决策提供信息，培训了13名初级调查员。对于这项提案，BWG将与美国癌症协会合作，美国放射学会、美国临床肿瘤学会、乳腺癌监测财团等。经验丰富的协调中心提供支持项目的基础设施目标包括资源共享和模型可访问性。特殊的环境提供了前所未有的协同作用和资源利用，以解决新的研究问题和支持职业生涯否则不可能实现的发展。总的来说，这项研究将推动建模研究，指导乳腺癌控制政策。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Simulation modeling of breast cancer endocrine therapy duration by patient and tumor characteristics.

DOI：
10.1002/cam4.4084
发表时间：
2022-01
期刊：
Cancer medicine
影响因子：
4
作者：
Chandler Y;Schechter C;Jayasekera J;Isaacs C;Kurian AW;Cadham C;Mandelblatt J
通讯作者：
Mandelblatt J

Optimal breast cancer risk reduction policies tailored to personal risk level.

DOI：
10.1007/s10729-022-09596-2
发表时间：
2022-09
期刊：
HEALTH CARE MANAGEMENT SCIENCE
影响因子：
3.6
作者：
Ergun, Mehmet A.;Hajjar, Ali;Alagoz, Oguzhan;Rampurwala, Murtuza
通讯作者：
Rampurwala, Murtuza

Analysis of Breast Cancer Mortality in the US-1975 to 2019.

1975 年至 2019 年美国乳腺癌死亡率分析。

DOI：
10.1001/jama.2023.25881
发表时间：
2024
期刊：
JAMA
影响因子：
0
作者：
Caswell-Jin,JenniferL;Sun,LiyangP;Munoz,Diego;Lu,Ying;Li,Yisheng;Huang,Hui;Hampton,JohnM;Song,Juhee;Jayasekera,Jinani;Schechter,Clyde;Alagoz,Oguzhan;Stout,NatashaK;Trentham-Dietz,Amy;Lee,SandraJ;Huang,Xuelin;Mandelblatt,
通讯作者：
Mandelblatt,

The Early Detection of Breast Cancer Using Liquid Biopsies: Model Estimates of the Benefits, Harms, and Costs.