Whittemore A S
Department of Family, Community and Preventive Medicine, Stanford University School of Medicine, California 94305.
Am J Ind Med. 1987;12(3):233-48. doi: 10.1002/ajim.4700120302.
The person-years approach to analyzing mortality data from occupational cohorts was introduced in the midtwentieth century. It cross-classifies all observed deaths and observation times into cells, computes the number of expected deaths for each cell based on referenced mortality rates, and then examines the ratio of total number of observed deaths to total number of expected deaths (the standardized mortality ratio). The maximum likelihood method of statistical inference was developed in the early twentieth century. However, only recently has it been applied to the analysis of occupational cohort data. When so applied, it provides estimates of measures of association between exposures and disease by maximizing the probability of the observed data. This paper shows how recent developments in the use of this tool justify and extend the person-years approach. In particular, problems with the standardized mortality ratio cited in the literature are shown to result from reliance on assumptions that are inappropriate for the data at hand. Methods for testing these assumptions are described. The discussion is illustrated with examples from occupational cohort studies of lung cancer.
用于分析职业队列死亡率数据的人年方法是在20世纪中叶引入的。它将所有观察到的死亡和观察时间交叉分类到各个单元格中，根据参考死亡率计算每个单元格的预期死亡人数，然后检查观察到的死亡总数与预期死亡总数的比率（标准化死亡率）。统计推断的最大似然方法是在20世纪初发展起来的。然而，直到最近它才被应用于职业队列数据的分析。当这样应用时，它通过最大化观察数据的概率来提供暴露与疾病之间关联度量的估计值。本文展示了使用这一工具的最新进展如何证明人年方法的合理性并对其进行扩展。特别是，文献中提到的标准化死亡率的问题被证明是由于依赖于不适用于手头数据的假设所致。描述了检验这些假设的方法。讨论通过肺癌职业队列研究的例子进行说明。
