The Hazards of Hazard Ratios

By Miguel A. Hern'an. Epidemiology, 2010

1,222 citations recorded by the source corpus.

T he hazard ratio (HR) is the main, and often the only, effect measure reported in many epidemiologic studies. For dichotomous, non–time-varying exposures, the HR is deﬁned as the hazard in the exposed groups divided by the hazard in the unexposed groups. For all practical purposes, hazards can be thought of as incidence rates and thus the HR can be roughly interpreted as the incidence rate ratio. The HR is commonly and conveniently estimated via a Cox proportional hazards model, which can include potential confounders as covariates. I review 2 problems and some proposed solutions. As I will use the from a Initiative randomized experiment compared the risk of heart disease of women assigned to combined (estrogen plus progestin) hormone therapy with that of women assigned to placebo. 1 By using a randomized experiment as an example, the discussion can focus on the shortcomings of the HR, setting aside issues of confounding and other serious problems that arise in observational studies.

Subfields: Oncology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9c462ca236359360da305a6fb2da69eaf2ef8712

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In Oncology

In Statistics and Probability

Citations in the corpus

Structural nested models and G-estimation: the partially realized promise (2014, background): “This feature is shared with the causal rate or hazard ratio (Hernan, 2010).”
Observational data for comparative effectiveness research: an emulation of randomised trials to estimate the effect of statins on primary prevention of coronary heart disease (2011, background): “That is, even in the absence of a long-term protective effect of hormone therapy on the absolute risk of CHD, the HR will be less than 1 after excluding the first few years.(31) In our statin analysis, one could argue that excluding the early follow-up does not introduce selection bias because rando”