The hazard ratio, typically estimated using Cox's famous proportional hazards model, is the most common effect measure used to describe the association or effect of a covariate on a time-to-event outcome. In recent years the hazard ratio has been argued by some to lack a causal interpretation, even in randomised trials, and even if the proportional hazards assumption holds. This is concerning, not least due to the ubiquity of hazard ratios in analyses of time-to-event data. We review these criticisms, describe how we think hazard ratios should be interpreted, and argue that they retain a valid causal interpretation. Nevertheless, alternative measures may be preferable to describe effects of exposures or treatments on time-to-event outcomes.

翻译：风险比通常通过Cox著名的比例风险模型进行估计，是描述协变量与时间-事件结局关联性或效应时最常用的效应度量指标。近年来有学者提出，即便在随机化试验中且满足比例风险假设的前提下，风险比仍缺乏因果解释性。这一观点值得关注，特别是考虑到风险比在时间-事件数据分析中的普遍性。本文系统评述了相关批评观点，阐述了我们认为风险比应有的解释方式，并论证其仍具备有效的因果解释性。尽管如此，在描述暴露或治疗对时间-事件结局的影响时，替代性度量指标可能更具优势。