Statistical Inference for Lead Time in Cancer Screening

癌症筛查提前期的统计推断

• 批准号: 6938206
• 负责人: Dongfeng Wu
• 金额: $ 6.77万
• 依托单位: MISSISSIPPI STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6938206
• 关键词: breast neoplasms; computer human interaction; computer simulation; computer system design /evaluation; early diagnosis; human data; mathematical model; method development; model design /development; neoplasm /cancer diagnosis; statistics /biometry

DESCRIPTION (provided by applicant): The long-term goal of this research is to develop new statistical methodology for the design and analysis of cancer screening trials. Cancer screening is the major technique for early detection of cancer, hence for disease control. The effectiveness of the screening program directly depends on lead time, which is the length of time the diagnosis is advanced by screening. The property of the lead time for the screening detected cases has been derived in today's literature, mainly in a stable disease model. However, the proportion of people who does not benefit from the screening is not addressed; further more, the long-term contribution of screening has not been evaluated. The specific aims are: (1) Derive the exact probability distribution for the lead time in a periodic screening program, for both the screening-detected cases and the interval cases, in both stable and nonstable disease models. Hence we can make statistical inference about the lead time, estimate the proportion of people who truly benefit from periodic screenings in a long-term scenario, and the proportion that does not. The proposed distribution of the lead time will depend on the sensitivity, the sojourn time distribution, the transition probability into the preclinical state, and the screening time intervals. The proposed method will be verified by extensive simulations. (2) Apply the proposed method to aid in developing the optimal design of periodic screening; in particular, choosing screening time intervals for groups of people with different risks. User-friendly software will be developed and made available to the research community. In summary, the proposed research will be an aid to increase the efficiency and reduce the cost of future periodic screening trials.

描述（由申请人提供）：本研究的长期目标是为癌症筛查试验的设计和分析开发新的统计方法。癌症筛查是早期发现癌症的主要技术，因此也是疾病控制的主要技术。筛查计划的有效性直接取决于前置时间，即通过筛查提前诊断的时间长度。在今天的文献中，主要是在稳定的疾病模型中，已经推导出了筛选检测病例的提前期的属性。然而，没有从筛查中受益的人的比例没有得到解决;此外，筛查的长期贡献也没有得到评估。 具体目标是：（1）在稳定和非稳定疾病模型中，推导出筛查检测病例和间隔病例的周期性筛查计划中提前时间的精确概率分布。因此，我们可以对准备时间进行统计推断，估计在长期情况下真正受益于定期筛查的人的比例，以及不受益的比例。拟定的前置时间分布将取决于灵敏度、逗留时间分布、进入临床前状态的转换概率和筛选时间间隔。所提出的方法将通过大量的模拟验证。(2)应用所提出的方法，以帮助开发周期性筛选的最佳设计，特别是，选择筛选时间间隔的人群具有不同的风险。将开发方便用户的软件，并提供给研究界。 总之，拟议的研究将有助于提高效率，降低未来定期筛查试验的成本。