Phillips A N, Smith G D
Academic Department of Genito-Urinary Medicine, University College and Middlesex School of Medicine, London.
J Clin Epidemiol. 1993 Oct;46(10):1203-11. doi: 10.1016/0895-4356(93)90120-p.
Prospective epidemiological studies which seek to relate potential risk factors to the risk of disease are subject to appreciable biases which are often unrecognized. The inability to precisely measure subjects' true values of the risk factors under consideration tends to result in bias towards unity in the univariate relative risks associated with them--the more imprecisely a risk factor is measured, the greater the bias. When correlated risk factors are measured with different degrees of imprecision the adjusted relative risk associated with them can be biased towards or away from unity. When designing a new prospective study cost considerations usually limit the total number of subject-evaluations that are available. The usual design approach is to maximize the study size and evaluate each subject on one occasion only. An alternative approach involves recruitment of a smaller number of subjects so that each can be evaluated on more than one occasion, thus resulting in a more precise measure of subjects' risk factor values and hence less bias in the relative risk estimates. In this paper we use a simulation approach to show that under conditions that prevail for most major prospective epidemiological studies the latter approach is actually more likely to produce accurate relative risk estimates. This emphasizes the importance of bias due to exposure measurement imprecision and suggests that attempts to anticipate and control it be given at least as high a priority as that given to sample size assessment in the design of epidemiological studies.
旨在将潜在风险因素与疾病风险联系起来的前瞻性流行病学研究容易受到明显的偏差影响，而这些偏差往往未被认识到。无法精确测量受试者所考虑的风险因素的真实值往往会导致与这些因素相关的单变量相对风险偏向于1——风险因素测量得越不精确，偏差就越大。当相关风险因素以不同程度的不精确性进行测量时，与之相关的调整后相对风险可能会偏向或偏离1。在设计一项新的前瞻性研究时，成本考虑通常会限制可进行的受试者评估总数。通常的设计方法是最大化研究规模，并且仅在一个时间点对每个受试者进行评估。另一种方法是招募较少数量的受试者，以便对每个受试者进行多次评估，从而更精确地测量受试者的风险因素值，进而在相对风险估计中产生较小的偏差。在本文中，我们使用模拟方法表明，在大多数主要前瞻性流行病学研究普遍存在的条件下，后一种方法实际上更有可能产生准确的相对风险估计。这强调了因暴露测量不精确而导致的偏差的重要性，并表明在流行病学研究设计中，尝试预测和控制这种偏差至少应与样本量评估给予同样高的优先级。
