The effect of measurement error in risk factors that change over time in cohort studies: do simple methods overcorrect for 'regression dilution'?
The effect of measurement error in risk factors that change over time in cohort studies: do simple methods overcorrect for 'regression dilution'?
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DOI：
10.1093/ije/dyi148
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发表时间：
2005-12-01
影响因子：
7.7
通讯作者：
White, IR
中科院分区：
文献类型：
--
作者：
Frost, C;White, IR
背景通过“回归稀释”，疾病和易受误差影响的风险因素之间的关系减弱是众所周知的，研究人员经常尝试调整其影响。然而，队列研究中最经常采用的调整方法是一个隐含的假设，即这种关系完全由当前无错误的风险因素水平驱动，而不是由过去的水平驱动。方法我们根据特定时间的风险因素在当时和过去时期的无误差水平对疾病风险进行建模，并使用粗略的当前水平、历史调整后的当前水平和终生水平关联来总结生命过程中的风险因素与疾病的关系。使用弗雷明翰心脏研究的收缩压数据，我们展示了测量误差对这些相关性的影响，并调查了简单校正方法可能出现的偏差。结果简单的范围比类型校正系数高估了29%的终生水平关联，存在相对温和的当前风险对过去水平的依赖(5年前的水平预测当前风险的一半)。结论如果风险因素-疾病关系不是短期的，回归稀释偏差的简单校正方法可能会导致严重的过度校正。
Background The attenuation of the relationship between disease and a risk factor subject to error through 'regression dilution' is well recognized, and researchers often make attempts to adjust for its effects. However, the adjustment methods most often adopted in cohort studies make an implicit assumption that the relationship is driven exclusively by current error-free levels of the risk factor and not by past levels. Here we investigate the bias that is introduced if this assumption is invalid.Methods We model disease risk at a particular time in terms of error-free levels of the risk factor at that time and in past periods, and summarize the 'life-course' risk factor-disease relationship using crude current level, history adjusted current level and lifetime level associations. Using systolic blood pressure data from the Framingham Heart Study we show the impact of measurement error on these associations and investigate the biases that can occur with simple correction methods.Results A simple 'ratio of ranges' type correction factor overestimates the lifetime level association by 29% in the presence of a relatively modest dependency of current risk on past levels (levels 5 years ago half as predictive of current risk as current levels).Conclusions Simple methods of correction for regression dilution bias can lead to substantial overcorrection if the risk factor-disease relationship is not short term.