Future Cases as Present Controls to Adjust for Exposure... : Epidemiology (original) (raw)

Methods: Original Article

Future Cases as Present Controls to Adjust for Exposure Trend Bias in Case-only Studies

Wang, Shirleya; Linkletter, Crystala; Maclure, Malcolmb,c; Dore, Davida,d; Mor, Vincenta; Buka, Stephena; Wellenius, Gregory A.a

From the aDepartment of Community Health-Epidemiology, Brown University, Providence, RI; bDepartment of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada; cDepartment of Epidemiology, Harvard University, Cambridge, MA; and di3 Drug Safety, Waltham MA.

Submitted 29 October 2010; accepted 4 March 2011.

Pre-doctoral fellowship support by National Research Service Award; grant #2T32 HS000011 AHRQ Graduate Student Support for Research Assistants at Pfizer Epidemiology; award #A 29843-001, grant # 140-N-502134-V2, and ES015774 from the National Institute of Environmental Health Sciences.

Correspondence: Shirley Wang, 1620 Tremont St, Boston, MA 02120. E-mail: [email protected].

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.