Table 1.

Comparison of Randomized Controlled Trials and Observational Study Design Features

Feature	Common in RCTs	Common in Observational Studies	How to Make Observational Studies More Relevant to RCT Design
Eligibility criteria	Narrow, with a defining risk factor	Few restrictions on study participants	Compare estimated effects within subgroups, particularly those aligning with particular risk strata or potential for disproportionate benefit
Sample composition	Convenience samples, with potential for highly selected samples	Clinical or population-based samples	Systematically evaluate effect modifiers and report subgroup effect estimates; reweight estimates or apply restriction to explore effects in samples with different composition
Length of follow-up	Relatively brief, with intervention often lasting for only ~12–48 months; stopped when continuation would result in harm to 1 group	Feasible and common to follow participants for years to decades	Evaluate how exposures relate to subsequent outcomes in the short, medium, or long term; quantify the likelihood and timing of other benefits and harms of change in exposure that might lead to termination of treatment in a trial (e.g., evidence of benefit or harm on a different outcome)
Treatment conditions	Test intervention vs. control condition (e.g., a specific medication regimen); intervention condition is chosen based on expectation it will lead to a desired risk factor status	Contrast groups with given levels or intensity of an exposure (e.g., presence or absence of a risk factor at a given time)	Evaluate the impact of treatments that affect risk-factor status or changes in exposure using methods that address issues of confounding by indication and reverse causation; evaluate heterogeneity in estimated effects of changes in exposure based on the presumed cause of exposure change (e.g., medication, lifestyle change, prevalent disease); use study designs that exploit sources of variation in exposure that are unlikely to be confounded (e.g., quasi-experimental study designs)
Outcome	Primary outcome prespecified, sometimes with governmental or marketing approval in mind	Based on outcome measure available in the data and most statistically significant	Systematically report results for all available measures, regardless of statistical significance, to identify heterogeneity in strength of effect
Analysis	Analyses are prespecified; intent-to-treat analysis estimating the average marginal treatment effect of randomization	Analytic options are endless; conventional analysis is often a conditional effect estimate comparing those with or without a given exposure	Report average marginal effect of exposure (contrasting everyone vs. nobody exposed) to provide bounds on potential effect sizes, recognize or estimate attenuation due to nonadherence and bias due to misclassification

Abbreviation: RCT, randomized controlled trial.