Stram Daniel O, Kopecky Kenneth J
Department of Preventive Medicine, School of Medicine, University of Southern California, Los Angeles, California 90033, USA.
Radiat Res. 2003 Oct;160(4):408-17. doi: 10.1667/3046.
This paper discusses practical effects of dosimetry error relevant to the design and analysis of an epidemiological study of disease risk and exposure. It focuses on shared error in radiation dose estimates for such studies as the Hanford Thyroid Disease Study or the Utah Thyroid Cohort Study, which use complex dosimetry systems that produce multiple replications of possible dose for the cohort. We argue that a simple estimation of shared multiplicative error components through direct examination of the replications of dose for each person provides information useful for estimating the power of a study to detect a radiation effect and illustrate this with an example based on the doses used for the Hanford Thyroid Disease Study. Uncertainty analysis (construction of confidence intervals) can be approached in the same way in simple cases. We also offer some suggestions for Monte Carlo-based confidence intervals.
本文讨论了与疾病风险和暴露的流行病学研究的设计与分析相关的剂量测定误差的实际影响。它聚焦于诸如汉福德甲状腺疾病研究或犹他甲状腺队列研究等此类研究中辐射剂量估计的共享误差，这些研究使用复杂的剂量测定系统，该系统会为队列产生可能剂量的多个复制品。我们认为，通过直接检查每个人的剂量复制品来简单估计共享的乘法误差分量，可为估计研究检测辐射效应的效能提供有用信息，并以基于汉福德甲状腺疾病研究所用剂量的一个例子对此进行说明。在简单情况下，不确定性分析（置信区间的构建）也可以用同样的方式进行。我们还为基于蒙特卡洛的置信区间提供了一些建议。
