The Trend-in-Trend Research Design for Causal Inference.
Ji X, Small DS, Leonard CE, Hennessy S.
Cohort studies can be biased by unmeasured confounding. We propose a hybrid ecologic-epidemiologic design called the trend-in-trend design, which requires a strong time-trend in exposure, but is unbiased unless there are unmeasured factors affecting outcome for which there are time-trends in prevalence that are correlated with time-trends in exposure across strata with different exposure trends. Thus, the conditions under which the trend-in-trend study is biased are a subset of those under which a cohort study is biased. The trend-in-trend design first divides the study population into strata based on the cumulative probability of exposure given covariates, which effectively stratifies on time-trend in exposure, provided there is a trend. Next, a covariates-free maximum likelihood model estimates the odds ratio (OR) using data on exposure prevalence and outcome frequency within cumulative probability of exposure strata, across multiple periods. In simulations, the trend-in-trend design produced ORs with negligible bias in the presence of unmeasured confounding. In empiric applications, trend-in-trend reproduced the known positive association between rofecoxib and myocardial infarction (observed OR: 1.2, 95% confidence interval: 1.1, 1.4), and known null associations between rofecoxib and severe hypoglycemia [OR = 1.1 (0.92, 1.3)] and non-vertebral fracture [OR = 0.84 (0.64, 1.1)]. The trend-in-trend method may be useful in settings where there is a strong time-trend in exposure, such as a newly approved drug or other medical intervention.Link