46 research outputs found
Target trial emulation: teaching epidemiology and beyond
Observational epidemiology is continually held to thestandard of randomized trials. A typical epidemiology article references previous trials in the introduction (or reasons why trials are not feasible) and, when possible, compares the results to previous trials in the discussion. When the results from an observational study and trial disagree, we nearly always begin by questioning the former. Curiously, the methods section of an observational study — an undeniably crucial part of an article — rarely references trial methods or designs. Explicit target trial emulation aims to remedy this
Mendelian randomization with a binary exposure variable: interpretation and presentation of causal estimates
Mendelian randomization uses genetic variants to make causal inferences about a modifiable exposure. Subject to a genetic variant satisfying the instrumental variable assumptions, an association between the variant and outcome implies a causal effect of the exposure on the outcome. Complications arise with a binary exposure that is a dichotomization of a continuous risk factor (for example, hypertension is a dichotomization of blood pressure). This can lead to violation of the exclusion restriction assumption: the genetic variant can influence the outcome via the continuous risk factor even if the binary exposure does not change. Provided the instrumental variable assumptions are satisfied for the underlying continuous risk factor, causal inferences for the binary exposure are valid for the continuous risk factor. Causal estimates for the binary exposure assume the causal effect is a stepwise function at the point of dichotomization. Even then, estimation requires further parametric assu
Invited Commentary:Conducting and Emulating Trials to Study Effects of Social Interventions
All else being equal, if we had 1 causal effect we wished to estimate, we would conduct a randomized trial with a protocol that mapped onto that causal question, or we would attempt to emulate that target trial with observational data. However, studying the social determinants of health often means there are not just 1 but several causal contrasts of simultaneous interest and importance, and each of these related but distinct causal questions may have varying degrees of feasibility in conducting trials. With this in mind, we discuss challenges and opportunities that arise when conducting and emulating such trials. We describe designing trials with the simultaneous goals of estimating the intention-to-treat effect, the per-protocol effect, effects of alternative protocols or joint interventions, effects within subgroups, and effects under interference, and we describe ways to make the most of all feasible randomized trials and emulated trials using observational data. Our comments are grounded in the study results of Courtin et al. (Am J Epidemiol. 2022;191(8):1444–1452)
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Are Mendelian randomization investigations immune from bias due to reverse causation?
Funder: National Institute for Health Research (GB
Are Mendelian randomization investigations immune from bias due to reverse causation?
Funder: National Institute for Health Research (GB
Application of the Instrumental Inequalities to a Mendelian Randomization Study With Multiple Proposed Instruments
BACKGROUND: Investigators often support the validity of Mendelian randomization (MR) studies, an instrumental variable approach proposing genetic variants as instruments, via. subject matter knowledge. However, the instrumental variable model implies certain inequalities, offering an empirical method of falsifying (but not verifying) the underlying assumptions. Although these inequalities are said to detect only extreme assumptio
Causal null hypotheses of sustained treatment strategies: What can be tested with an instrumental variable?
Sometimes instrumental variable methods are used to test whether a causal effect is null rather than to estimate the magnitude of a causal effect. However, when instrumental variable methods are applied to time-varying exposures, as in many Mendelian randomization studies, it is unclear what causal null hypothesis is tested. Here, we consider different ver