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. 2011 Jul;22(4):568-74.
doi: 10.1097/EDE.0b013e31821d09cd.

Future cases as present controls to adjust for exposure trend bias in case-only studies

Shirley Wang  1 , Crystal Linkletter, Malcolm Maclure, David Dore, Vincent Mor, Stephen Buka, Gregory A Wellenius
Affiliations

Future cases as present controls to adjust for exposure trend bias in case-only studies

Shirley Wang et al. Epidemiology. 2011 Jul.

Abstract

Self-matched case-only studies (such as the case-crossover or self-controlled case-series method) control by design for time-invariant confounders (measured or unmeasured), but they do not control for confounders that vary with time. A bidirectional case-crossover design can be used to adjust for exposure-time trends. In pharmacoepidemiology, however, illness often influences future use of medications, making a bidirectional design problematic. Suissa's case-time-control design combines a case-crossover and case-control design, and adjusts for exposure-trend bias in the cases' self-controlled odds ratio by dividing that ratio by the corresponding self-controlled odds ratio in a concurrent matched control group. However, if not well matched, the control group may reintroduce selection bias. We propose a "case-case-time-control" that involves crossover analyses in cases and future-case controls. This person-time sampling strategy improves matching by restricting controls to future cases. We evaluate the proposed study design through simulations and analysis of a theoretically null relationship using Veterans Administration (VA) data. Simulation studies show that the case-case-time-control can adjust for exposure trends while controlling for time-invariant confounders. Use of an inappropriate control group left case-time-control analyses biased by exposure-time trends. When analyzing the relationship between vitamin exposure and stroke, using data on 3192 patients in the VA system, a case-crossover odds ratio of 1.5 (95% confidence interval = 1.3-1.7) was reduced to 1.1 (0.9-1.3) when divided by the concurrent exposure trend odds ratio (1.4) in matched future cases. This applied example demonstrates how our approach can adjust for exposure trends observed across time axes.

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Figures

FIGURE 1
FIGURE 1
Case-Case Time Control
FIGURE 2
FIGURE 2
A. Time-Invariant Confounding B. Time-Invariant Confounding Plus Change in Exposure Prevalence
FIGURE 3
FIGURE 3
Exposure Time Trends A. Calendar Time B. 365 Days Prior to Stroke Event
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