Analytical Investigation of Breast Cancer Progression: DCIS, Overdiagnosis

乳腺癌进展的分析调查：DCIS、过度诊断

• 批准号: 8676739
• 负责人: Sandra J Lee
• 金额: $ 37.62万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-03 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8676739
• 关键词: Abnormal Cell; Applications Grants; Area; Breast; Breast Cancer Detection; Breast Cancer Early Detection; Breast Cancer Model; Clinical; Contralateral; Country; Data; Development; Diagnosis; Disease; Disease Progression; Disputes; Duct (organ) structure; Early Diagnosis; Exhibits; Film; Incidence; Indolent; Investigation; Knowledge; Lead; Life; Light; Likelihood Functions; Malignant Neoplasms; Mammography; Maximum Likelihood Estimate; Medical Surveillance; Menopause; Meta-Analysis; Methodology; Methods; Modeling; Natural History; Nature; Noninfiltrating Intraductal Carcinoma; Norway; Persons; Probability; Process; Publishing; Relative (related person); Research; Research Personnel; Residual state; Risk; Risk Factors; Screening for cancer; Staging; Statistical Methods; Symptoms; Time; Woman; Work; base; case finding; clinical practice; digital; disease diagnosis; malignant breast neoplasm; pre-clinical; programs; screening; treatment as usual; tumor progression

DESCRIPTION (provided by applicant): This grant proposal is targeted at research problems arising in the early detection of cancer with special emphasis on the early diagnosis of breast cancer. The principal research areas include:(i) Develop a stochastic model for the disease progression of breast ductal carcinoma in situ (DCIS), (ii) Investigate the natural history of breast cancer, including methods for estimating the pre-clinical sojourn time and lead time distributions and (iii) Develop a new method for investigating the over diagnosis of disease. The diagnosis of breast DCIS in the U.S. has risen rapidly consistent with the dissemination of mammographic screening. Little is known about the natural history of DCIS. However women diagnosed with DCIS are known to be at elevated risk for invasive breast cancer (IBC). Knowledge on the natural history of DCIS, i.e. how it develops, if and when it will progress to IBC, would be an essential first step to the management of DCIS. Modeling the natural history of DCIS is challenging as there are no "ideal" data on DCIS progression of untreated DCIS cases. The first main aim of this research is to develop a stochastic model to evaluate the DCIS progression process. This model will utilize the U.S. Surveillance Epidemiology and End Results (SEER) and Norwegian data. Another aim involves a theoretical investigation of the sojourn time distribution in the early stage of breast cancer and the lead time associated with early detection of cancer. The last aim develops a new method for over diagnosis estimation. It arises in the early detection of disease setting, by screening programs finding cases which would never have become clinical in one's life time. Currently the actual level of over diagnosis from breast cancer screening is in dispute. It is planned to develop a new statistical method for estimating over diagnosis. This method will be unique in that it will make use of the disease incidence data. Applications will be made using the data from the Norwegian Breast Cancer Screening Program. Overall the proposed research will contribute greatly to the management of DCIS in clinical practice and shed some light on ongoing debate of 'harms" of breast cancer screening.

描述（由申请人提供）：该赠款提案针对的是在早期发现癌症时引起的研究问题，并特别强调了乳腺癌的早期诊断。主要研究领域包括：（i）开发一种随机模型，用于原位乳腺导管癌的疾病进展（DCIS），（ii）研究乳腺癌的自然史，包括用于估计临床前的Sojourn时间和领先时间分布和（III）开发出一种用于研究疾病过度诊断的新方法。美国乳腺DCI的诊断与乳房X线筛查的传播相一致。关于DCI的自然历史知之甚少。然而，众所周知，被诊断出患有DCI的妇女的侵入性乳腺癌风险较高（IBC）。关于DCI的自然历史的知识，即它如何发展，如果它会发展到IBC，这将是DCIS管理的重要第一步。对DCI的自然历史进行建模是具有挑战性的，因为没有关于未经处理的DCIS病例的DCIS进展的“理想”数据。这项研究的第一个主要目的是开发一个随机模型来评估DCIS进程过程。该模型将利用美国监视流行病学和最终结果（SEER）和挪威数据。另一个目的涉及对乳腺癌早期寄居时间分布的理论研究以及与癌症早期发现有关的提前时间。最后一个目标开发了一种用于过度诊断估计的新方法。它是在早期发现疾病设置的情况下出现的，它通过筛选计划发现的病例在一个人的一生中永远不会成为临床。目前，乳腺癌的实际诊断水平 筛选存在争议。计划开发一种估计诊断的新统计方法。该方法将是独一无二的，因为它将利用疾病发病率数据。将使用挪威乳腺癌筛查计划的数据进行应用。总体而言，拟议的研究将在临床实践中对DCI的管理有很大贡献，并阐明了正在进行的乳腺癌筛查“危害”的辩论。