Clayton D, Schifflers E
Stat Med. 1987 Jun;6(4):469-81. doi: 10.1002/sim.4780060406.
Our first paper reviewed methods for modelling variation in cancer incidence and mortality rates in terms of either period effects or cohort effects in the general multiplicative risk model. There we drew attention to the difficulty of attributing regular trends to either period or cohort influences. In this paper we turn to the more realistic problem in which neither period nor cohort effects alone lead to an adequate description of the data. We describe the age-period-cohort model and show how its ambiguities surrounding regular trends 'intensify'. We recommend methods for presenting the results of analyses based upon this model which minimize the serious risk of misleading implications and critically review previous suggestions. The discussion is illustrated by an analysis of breast cancer mortality in Japan with special reference to the phenomenon of 'Clemmesen's hook'.
我们的第一篇论文回顾了在一般乘法风险模型中,根据时期效应或队列效应来对癌症发病率和死亡率的变化进行建模的方法。在那里,我们提请注意将规律性趋势归因于时期或队列影响的困难。在本文中,我们转向一个更现实的问题,即单独的时期效应或队列效应都无法充分描述数据。我们描述了年龄-时期-队列模型,并展示了围绕规律性趋势的模糊性是如何“加剧”的。我们推荐基于该模型进行分析结果呈现的方法,这些方法能将误导性暗示的严重风险降至最低,并对先前的建议进行批判性审视。通过对日本乳腺癌死亡率的分析,特别是参考“克莱默森钩”现象,来说明该讨论。