Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity

The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the ‘peril’. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the ‘peril ratio index of synergy based on multiplicativity’ (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of ‘relative excess risk due to interaction’. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.

流行病学领域中，交互作用的传统评估方法一向基于风险比（risk-ratio）、比值比（odds-ratio）或率比的相乘性假设。然而，诸多流行病学家并未意识到，这类方法的选用主要出于统计计算的便利性，且常将具有统计学显著性的交互作用误判为真实的生物学机制性交互作用。本文作者提出了一种用于风险评估的替代度量体系——‘危度（peril）’，其定义为累积率的指数形式，简言之，即生存概率的倒数（又称风险补数），亦等同于比值加1。作者基于危度比的相乘性构建了全新的交互作用评估指标：‘基于相乘性的协同作用危度比指标（peril ratio index of synergy based on multiplicativity，PRISM）’。在无冗余假设的前提下，PRISM可用于充分病因框架下的协同作用评估，即因果协同作用或机制性因果交互作用。相较于此前提出的‘交互作用所致相对超额风险’指标，PRISM的协同作用检测阈值更为宽松。采用这一全新的PRISM判定标准时，诸多在传统指标下未显示出交互作用证据的场景，实则对应着真正的正向或负向协同作用。