Jones M E, Swerdlow A J
Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, University of London, United Kingdom.
Am J Epidemiol. 1998 Nov 15;148(10):1012-7. doi: 10.1093/oxfordjournals.aje.a009567.
Cohort studies often compare the observed number of cases arising in a group under investigation with the number expected to occur on the basis of general population rates. The general population is taken to represent unexposed persons, but it is almost inevitably biased in that it comprises all types of people including exposed ones. To identify circumstances when this bias matters, the authors modeled its effect in relation to the size of the observed standardized mortality ratio (SMR) and the prevalence of exposed individuals in the general population. The authors found that bias may be a major problem, causing substantial underestimation of the true relative risk, when either the prevalence of exposure in the general population or the SMR are large. The bias can cause an apparent trend in SMRs with age when none exists. It also places a limit on the maximum size of the observed SMR, no matter how large the true relative risk. A table is provided showing the extent of bias in different circumstances. Cohort studies of people with common diseases or exposures, or that find large SMRs, when using general population expectations, need to consider the extent of bias from this source.
队列研究通常会将受调查群体中实际出现的病例数与基于一般人群发病率预期出现的病例数进行比较。一般人群被视为未暴露人群，但它几乎不可避免地存在偏差，因为它包含了所有类型的人，包括暴露人群。为了确定这种偏差何时重要，作者针对观察到的标准化死亡率（SMR）的大小以及一般人群中暴露个体的患病率对其影响进行了建模。作者发现，当一般人群中的暴露患病率或SMR较大时，偏差可能是一个主要问题，会导致对真实相对风险的大幅低估。这种偏差可能会在不存在年龄相关的SMR趋势时造成明显的趋势。无论真实相对风险有多大，它也会对观察到的SMR的最大规模设置限制。文中提供了一个表格，展示了不同情况下的偏差程度。对于患有常见疾病或暴露的人群进行队列研究，或者在使用一般人群预期时发现较大SMR的研究，需要考虑来自这一来源的偏差程度。
