Department of Population Medicine, College of Medicine, QU Health, Qatar University, Doha, Qatar.
Research School of Population Health, College of Health and Medicine, Australian National University, Canberra, Australia.
J Clin Epidemiol. 2022 Feb;142:271-279. doi: 10.1016/j.jclinepi.2020.08.019. Epub 2020 Nov 7.
In clinical trials, the relative risk or risk ratio (RR) is a mainstay of reporting of the effect magnitude for an intervention. The RR is the ratio of the probability of an outcome in an intervention group to its probability in a control group. Thus, the RR provides a measure of change in the likelihood of an event linked to a given intervention. This measure has been widely used because it is today considered a measure with "portability" across varying outcome prevalence, especially when the outcome is rare. It turns out, however, that there is a much more important problem with this ratio, and this paper aims to demonstrate this problem.
We used mathematical derivation to determine if the RR is a measure of effect magnitude alone (i.e., a larger absolute value always indicating a stronger effect) or not. We also used the same derivation to determine its relationship to the prevalence of an outcome. We confirm the derivation results with a follow-up analysis of 140,620 trials scraped from the Cochrane.
We demonstrate that the RR varies for reasons other than the magnitude of the effect because it is a ratio of two posterior probabilities, both of which are dependent on baseline prevalence of an outcome. In addition, we demonstrate that the RR shifts toward its null value with increasing outcome prevalence. The shift toward the null happens regardless of the strength of the association between intervention and outcome. The odds ratio (OR), the other commonly used ratio, measures solely the effect magnitude and has no relationship to the prevalence of an outcome in a study nor does it overestimate the RR as is commonly thought.
The results demonstrate the need to (1) end the primary use of the RR in clinical trials and meta-analyses as its direct interpretation is not meaningful, (2) replace the RR by the OR, and (3) only use the postintervention risk recalculated from the OR for any expected level of baseline risk in absolute terms for purposes of interpretation such as the number needed to treat. These results will have far-reaching implications such as reducing misleading results from clinical trials and meta-analyses and ushering in a new era in the reporting of such trials or meta-analyses in practice.
在临床试验中，相对风险或风险比（RR）是报告干预效果大小的主要指标。RR 是干预组中某结局发生概率与对照组中该结局发生概率的比值。因此，RR 提供了一种衡量与特定干预相关的事件发生可能性变化的指标。这种衡量方法得到了广泛应用，因为它被认为是一种具有“可移植性”的衡量方法，可以跨越不同结局发生率，尤其是当结局罕见时。然而，事实证明，这种比值存在一个更重要的问题，本文旨在证明这一问题。
我们使用数学推导来确定 RR 是否仅作为效应大小的衡量指标（即绝对值越大，效果越强），还是不仅如此。我们还使用相同的推导来确定它与结局发生率的关系。我们使用从 Cochrane 中提取的 140620 个试验的后续分析来确认推导结果。
我们证明，RR 会因效应大小以外的原因而发生变化，因为它是两个后验概率的比值，这两个概率都依赖于结局发生率的基线值。此外，我们证明，RR 会随着结局发生率的增加而向其零值偏移。这种向零值的偏移发生在干预与结局之间的关联强度无论强弱的情况下。比值比（OR），另一种常用的比值，仅衡量效应大小，与研究中的结局发生率无关，也不会像普遍认为的那样高估 RR。
结果表明，需要（1）结束 RR 在临床试验和荟萃分析中的主要使用，因为其直接解释没有意义，（2）用 OR 代替 RR，（3）仅在解释时使用从 OR 重新计算的干预后风险，以绝对术语表示任何预期的基线风险水平，例如需要治疗的人数。这些结果将产生深远的影响，例如减少临床试验和荟萃分析中的误导性结果，并开创此类试验或荟萃分析报告的新时代。
