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An Exact Test for Overdispersion in Screening Mammography Assessments

筛查乳腺 X 光检查评估中过度分散的精确测试

基本信息

批准号：
7140775
负责人：
JI-HYUN LEE
金额：
$ 8.15万
依托单位：
H. LEE MOFFITT CANCER CTR & RES INST
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-08-01 至 2008-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7140775
关键词：
breast neoplasms early diagnosis health science profession mammography mathematical model model neoplasm /cancer public health radiology

项目摘要

DESCRIPTION (provided by applicant): Early detection tests for breast cancer save many thousands of lives each year, and many more lives could be saved if even more women and their health care providers took advantage of these tests. Early detection of breast cancer depends in part on the accuracy of screening mammogram interpretation. The accuracy of human interpreters in detecting the presence or absence of breast cancer can be evaluated by estimating indices like sensitivity and specificity. Efficient and precise estimation of both of these accuracy parameters have important consequences for public health planning and for patients. When multiple observations and statistical modeling approaches are employed for assessing the accuracy indices, the standard assumption of the binomial distribution for the data needs confirmation. Several tests based on large sample theory are widely available. However, the data generated in biomedical studies frequently involve small samples, and thus the accuracy of the asymptotic approach for analyzing such data is in question. The goal of this research proposal is to develop a method of exact testing for overdispersion in small samples. The project will involve both theoretical and empirical work, drawing on existing data sources and collaborative opportunities provided through the investigator's collaboration at H. Lee Moffitt Cancer Center & Research Institute. The specific aims for this proposal are described as: Specific Aim 1: Develop an exact test for overdispersion; Specific Aim 2: Develop a computational algorithm and release a publicly available implementation; Specific Aim 3: Apply and evaluate the proposed method using a real life dataset.

乳腺癌早期检测每年挽救成千上万人的生命，如果更多的妇女及其医疗保健提供者利用这些检测，可以挽救更多的生命。乳腺癌的早期发现部分取决于筛查乳房X线照片解释的准确性。人类口译员检测乳腺癌存在或不存在的准确性可以通过估计敏感性和特异性等指标来评估。这两个准确度参数的有效和精确的估计对公共卫生规划和患者有重要的影响。当采用多重观测和统计建模方法评估准确性指标时，需要确认数据的二项分布的标准假设。基于大样本理论的几个测试是广泛可用的。然而，在生物医学研究中产生的数据往往涉及小样本，因此，分析这些数据的渐近方法的准确性是有问题的。本研究的目的是开发一种小样本过度分散的精确检验方法。该项目将涉及理论和实证工作，利用现有的数据来源和合作机会，通过研究者的合作在H。李莫菲特癌症中心和研究所。该提案的具体目标如下：具体目标1：开发过度分散的精确测试;具体目标2：开发计算算法并发布公开的实现;具体目标3：使用真实的数据集应用和评估所提出的方法。