MEASUREMENT ERRORS IN OCCUPATIONAL EPIDEMIOLOGY

职业流行病学中的测量误差

• 批准号: 3069022
• 负责人: DONNA L SPIEGELMAN
• 金额: $ 5.4万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-08-01 至 1994-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3069022
• 关键词: cancer information system; cancer risk; computer program /software; computers; disease /disorder proneness /risk; epidemiology; human mortality; human population study; information systems; mathematical model; model design /development; neoplasm /cancer epidemiology; occupational health /safety; statistics /biometry; work site

Occupational epidemiologists frequently encounter large errors in measurement of exposures of interest, particularly in studies in which exposure must be retrospectively assessed. Even in studies where exposure assessment is concurrent with the collection of outcome data, measurement errors in occupational studies are often believed to be considerable. In general, these errors lead to bias of effect estimates toward the null and underestimation of the width of confidence intervals. Although statisticians have proposed numerous methods for treating this problem, these methods have not yet made their way into standard practice, because a) the proper use of these methods requires a detailed understanding of the statistical literature, and few examples exist of practical applications, b) the use of most of these methods requires custom software and time- consuming calculations, and c) they are often not appropriate for typical features of occupational studies. The work proposed in this grant will address each of these three obstacles. New and existing measurement-error methods will be applied to important occupational data sets. The GM/UAW study of the risk of respiratory cancer from machining fluids exposure is a retrospective cohort study of 40,000 workers. The New Mexico uranium miners study is also a retrospective design, investigating the relationship between radon decay products and lung cancer risk by following 3,469 miners. The ACE study is a cross- sectional design investigating the health effects of occupational exposure to anti-cancer drugs in 3550 nurses, pharmacists and nurses' aides. In all of these studies, more accurate exposure assessment has occurred in a subsample of work environments within some of the time periods during which the subjects are followed. Measurement error models will be developed from these more detailed data and used to produce estimates of relative risk which will be corrected for bias due to measurement error. Confidence bounds around these estimates will incorporate the additional variability due to uncertainty about "true" exposure values. The analysis of retrospective cohort, case-control and cross-sectional data will be considered using logistic regression, Cox regression, and other methods for "failure time" data, as required. When published, the analyses will provide other investigators with sound examples of the use of these techniques. The primary goal of this grant is to develop methods suitable for the types of studies and data most frequently encountered in occupational epidemiology.

职业流行病学家经常会遇到很大的错误， 测量感兴趣的暴露，特别是在研究中， 必须对暴露进行回顾性评估。 即使在研究中， 评估与收集结果数据、测量 职业研究中的错误通常被认为是相当大的。 在 一般来说，这些误差会导致效应估计值偏向零， 低估了置信区间的宽度。 虽然 统计学家已经提出了许多处理这个问题的方法， 这些方法还没有成为标准实践，因为 a）正确使用这些方法需要详细了解 统计文献，很少有实际应用的例子， B）使用大多数这些方法需要定制软件和时间- 消费计算，和c）他们往往不适合典型的 职业研究的特点。 这项赠款中提出的工作将 解决这三个障碍。 新的和现有的测量误差方法将适用于重要的 职业数据集。 GM/UAW关于呼吸道癌症风险的研究 是一项回顾性队列研究， 工人 对新墨西哥州铀矿工人的研究也是一种回顾 设计，调查氡衰变产物与 肺癌的危险性。 ACE研究是一个交叉- 职业暴露对健康影响的横断面研究 在3550名护士，药剂师和护士助理中使用抗癌药物。 在所有 在这些研究中， 在某些时间段内的工作环境子样本， 受试者被跟踪。 测量误差模型将从 这些更详细的数据，并用于产生相对风险的估计 其将被校正由于测量误差引起的偏差。 信心 这些估计值的边界将包含额外的可变性 由于“真实”暴露值的不确定性。 回顾性队列、病例对照和横断面资料分析 将使用逻辑回归、考克斯回归和其他 “故障时间”数据的方法。 分析报告发表后， 将为其他研究人员提供使用这些方法的良好例子， 技术. 该补助金的主要目标是开发适合的方法 最常遇到的研究和数据类型， 职业流行病学