Statistical Inference for Lead Time in Cancer Screening

描述(由申请人提供)：这项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，从而控制疾病的主要技术。筛查计划的有效性直接取决于准备时间，即筛查使诊断提前的时间长度。在今天的文献中，主要是在一个稳定的疾病模型中，已经推导出筛查发现病例的提前时间的属性。然而，未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。 其具体目标是：(1)在稳定和非稳定疾病模型中，对于筛查检测病例和间隔病例，推导出周期筛查计划中提前期的精确概率分布。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，以及没有受益的比例。准备时间的建议分布将取决于敏感度、逗留时间分布、过渡到临床前状态的概率以及筛查时间间隔。所提出的方法将通过大量的仿真得到验证。(2)应用所提出的方法帮助制定定期筛查的最优设计；特别是为具有不同风险的人群选择筛查时间间隔。将开发用户友好的软件，并向研究界提供。 总之，拟议的研究将有助于提高未来定期筛查试验的效率和降低成本。

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.