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Measuring Screening Intensity in Case-Control Studies of the Efficacy of Mammography

机译:乳腺X线摄影有效性的病例对照研究中的筛查强度测量

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摘要

Of great interest in studies of screening for breast cancer is the relative efficacy of different screening frequencies (intensities). Prior work has suggested that estimates of the association between screening intensity and outcome in case-control studies would not produce valid results and that only binary indicators (no screens vs. one or more) of exposure can be used. Using case-control studies drawn from simulated cohorts of 30,000–40,000 women, the authors found that biases demonstrated in prior studies can be explained by 1) misclassification of true exposure groups by observed screening history, and 2) differential exposure misclassification of cases and controls. Binary as well as ordered categorical and interval measures can be biased unless they account for misclassification. By combining measurements of screening history from multiple periods of observation of varying lengths and using repeated-measures logistic regression models, the effect of screening intensity can be estimated in the presence of misclassification. Assessing the effect of screening intensity in case-control studies of mammography is possible if principles and methods for misclassification and measurement error guide the analysis.
机译:在乳腺癌筛查研究中非常感兴趣的是不同筛查频率(强度)的相对功效。先前的工作表明,病例对照研究中筛查强度与结果之间关联的估计将不会产生有效的结果,并且只能使用暴露的二元指标(无筛查与一个或多个筛查)。作者使用从30,000-40,000名妇女的模拟队列中得出的病例对照研究,发现以前的研究中显示的偏倚可以通过以下方式解释:1)通过观察的筛查历史对真实暴露人群进行错误分类,以及2)对病例和对照进行差异暴露的错误分类。二进制和有序的分类和区间测度可能会有偏差,除非它们考虑了错误分类。通过组合来自不同长度的多个观察期的筛选历史记录的测量结果,并使用重复测量的逻辑回归模型,可以在存在错误分类的情况下估算筛选强度的效果。如果分类错误和测量误差的原理和方法指导了分析,则可以在乳腺钼靶的病例对照研究中评估筛查强度的影响。

著录项

  • 来源
    《American Journal of Epidemiology 》 |2006年第3期| 272-281| 共10页
  • 作者单位

    Department of Biostatistics and Epidemiology Center for Clinical Epidemiology and Biostatistics University of Pennsylvania School of Medicine Philadelphia PA;

    Department of Statistics College of Science Texas AM University College Station TX;

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