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

• 批准号: 10251326
• 负责人: Oguzhan Alagoz
• 金额: $ 196.76万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 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/10251326
• 关键词: Accounting; Address; Adjuvant; Adverse effects; Advisory Committees; Affect; Age; American Cancer Society; American College of Radiology; American Society of Clinical Oncology; Area; Basic Science; Benchmarking; Benign; Biological Markers; Biopsy; 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; Investigational Therapies; Life; 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; Preventive service; Public Health; Publishing; Quality of life; Quality-Adjusted Life Years; Race; Recommendation; Recording of previous events; Records; Recurrence; Registries; Research; Research Personnel; Resource Sharing; Resources; Risk; Risk Factors; Structure; Survivors; Technology; Testing; Training; Translations; Variant; Wisconsin; Woman; Work; base; breast density; breast imaging; cancer care; 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; personalized approach; personalized screening; precision oncology; primary outcome; programs; racial disparity; response; screening; synergism; technological innovation; trend; virtual laboratory; working group

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.

抽象的 CISNET 乳腺工作组 (BWG) 提出专注于新精度的创新建模研究 肿瘤学范式有望重新定义乳腺癌控制最佳实践。我们选择了 建模适合填补证据空白并促进临床和政策转化的重要主题。 我们方法的独特组成部分包括考虑多重风险的疾病绝对风险建模 因素，解决影响疾病风险和影响的重要合并症（特别是 2 型糖尿病） 生存，探索基于生物标志物的新兴筛查方法，提供有关以下方面的指导： 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）评估新型精密筛查方法的影响； 2) 评估 精准治疗模式对辅助、新辅助和转移治疗的影响； 3）合成 目标 1 和 2 量化精准筛查和精准治疗对美国乳腺癌的贡献 死亡率降低； 4) 提供证据来指导干预措施，通过量化来减少种族差异 影响差异的多种风险、筛查、治疗和生存因素。该工作范围不会 在没有六个独特的 BWG 模型的情况下也是可行的：Dana Farber (D)、Erasmus (E)、Georgetown- 爱因斯坦 (GE)、MD 安德森 (M)、斯坦福 (S) 和威斯康星-哈佛 (W)。目标包括多个 RFA 优先领域，我们已拨出快速反应资金来解决剩余的优先领域、支持 跨癌症 CISNET 合作，促进初级职业发展。每个目标包括三个或更多 模型组因其独特的结构而被选择，包括外部合作者和初级研究人员。 这些模型将共享共同的输入，并提供一组标准的收益结果（例如，遥远的 避免复发和死亡、降低死亡率、远处无病生存以及生命年和质量 调整后的生命年）、危害（例如，假阳性和良性活检、间期癌症、晚期 诊断、过度诊断和治疗对生活质量的影响）和费用。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和 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 (American Cancer Society) 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该项目的基础设施 目标包括资源共享和模型可访问性。得天独厚的环境提供了 前所未有的协同和利用资源来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，这项研究将推进建模研究和 指导乳腺癌控制政策。