Duffy S W, Rohan T E, McLaughlin J R
MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge, U.K.
Stat Med. 1994 Feb 28;13(4):379-90. doi: 10.1002/sim.4780130405.
Cohort studies commonly involve a single determination of exposure, and one or more assessments of whether or not the outcome of interest has occurred. This approach is appropriate when the exposure does not change with time, and when one can readily determine the time of outcome (for example, mortality). If either of these conditions is not met, however, we may introduce bias into the estimate of effect, since we may misclassify individual members of the cohort with respect to exposure, outcome or both. We can reduce this bias by measuring exposure and outcome on more than one occasion. In this paper, we illustrate the design and analysis issues that arise in such circumstances, by reference to an ongoing prospective study of the relationship between genital papillomavirus infection and risk of cervical intraepithelial neoplasia. This study entails annual assessments of the status of the study subjects with respect to both conditions. In particular, we examine the implications that use of this design has on the statistical power of the study.
队列研究通常涉及对暴露情况的单次测定，以及对感兴趣的结局是否发生进行一次或多次评估。当暴露情况不随时间变化，且能够轻易确定结局发生时间（例如死亡率）时，这种方法是合适的。然而，如果不满足这两个条件中的任何一个，我们可能会在效应估计中引入偏差，因为我们可能会在暴露、结局或两者方面对队列中的个体成员进行错误分类。我们可以通过在多个时间点测量暴露和结局来减少这种偏差。在本文中，我们通过参考一项正在进行的关于人乳头瘤病毒感染与宫颈上皮内瘤变风险关系的前瞻性研究，来说明在这种情况下出现的设计和分析问题。这项研究需要每年对研究对象在这两种情况方面的状况进行评估。特别是，我们研究了使用这种设计对研究统计效力的影响。
