Campbell Ulka B, Gatto Nicolle M, Schwartz Sharon
Department of Epidemiology, Mailman School of Public Health at Columbia University, New York, USA.
Epidemiol Perspect Innov. 2005 Mar 3;2:1. doi: 10.1186/1742-5573-2-1. eCollection 2005.
It is well known that the incidence odds ratio approximates the risk ratio when the disease of interest is rare, but increasingly overestimates the risk ratio as the disease becomes more common. However when assessing interaction, incidence odds ratios may not approximate risk ratios even when the disease is rare. We use the term "distributional interaction" to refer to interaction that appears when using incidence odds ratios that does not appear, or appears to a lesser degree, when using risk ratios. The interpretational problems that arise from this discrepancy can have important implications in epidemiologic research. Therefore, quantification of the relationship between the interaction odds ratio and the interaction risk ratio is warranted. In this paper, we provide a formula to quantify the differences between incidence odds ratios and risk ratios when they are used to estimate effect modification on a multiplicative scale. Using this formula, we examine the conditions under which these two estimates diverge. Furthermore, we expand this discussion to the implications of using incidence odds ratios to assess effect modification on an additive scale. Finally, we illustrate how distributional interaction arises and the problems that it causes using an example from the literature. Whenever the risk of the outcome variable is non-negligible, distributional interaction is possible. This is true even when the disease is rare (e.g., disease risk is less than 5%). Therefore, when assessing interaction on either an additive or multiplicative scale, caution should be taken in interpreting interaction estimates based on incidence odds ratios.
众所周知,当所关注的疾病罕见时,发病比值比近似于风险比,但随着疾病变得更加常见,发病比值比会越来越高估风险比。然而,在评估交互作用时,即使疾病罕见,发病比值比也可能不近似于风险比。我们使用“分布交互作用”一词来指代在使用发病比值比时出现而在使用风险比时不出现或出现程度较小的交互作用。这种差异所产生的解释问题在流行病学研究中可能具有重要意义。因此,有必要对交互作用比值比和交互作用风险比之间的关系进行量化。在本文中,我们提供了一个公式,用于量化发病比值比和风险比在用于估计乘法尺度上的效应修正时的差异。使用这个公式,我们研究了这两个估计值出现差异的条件。此外,我们将这个讨论扩展到使用发病比值比评估加法尺度上的效应修正的含义。最后,我们通过文献中的一个例子来说明分布交互作用是如何产生的以及它所导致的问题。只要结局变量的风险不可忽略,就可能存在分布交互作用。即使疾病罕见(例如,疾病风险小于5%),情况也是如此。因此,在评估加法或乘法尺度上的交互作用时,在解释基于发病比值比的交互作用估计值时应谨慎。