OPEN ACCESS: All Research Methods & Reporting
Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes
Cite this as:
BMJ
2010;340:b5087
- Linda E Lévesque, assistant professor of epidemiology123,
- James A Hanley, professor of biostatistics14,
- Abbas Kezouh, biostatistician4,
- Samy Suissa, professor of epidemiology and biostatistics14
- 1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Canada
- 2Department of Community Health and Epidemiology, Queen’s University, Kingston, Canada
- 3Kingston, Frontenac, Lennox and Addington Public Health, Kingston, Canada
- 4Center for Clinical Epidemiology, Jewish General Hospital, McGill University, Montréal, Canada
- Correspondence to: L Lévesque linda.levesque{at}queensu.ca
- Accepted 25 August 2009
Well designed observational studies have made important contributions to our understanding of the risks and benefits of drug treatment. Such studies are often the first to identify or confirm important adverse health events associated with drugs, as seen recently with the cardiac effects of ergot derived dopamine agonists1 and cyclo-oxygenase 2 inhibitors.2 3 Observational studies can also assess aspects of drug safety, such as the time varying nature of risk, which cannot be readily appraised using an experimental design.4
Cohort studies are often preferred to case-control studies because they are less susceptible to certain biases.5 6 However, the inappropriate accounting of follow-up time and treatment status in the design and analysis of such studies can introduce immortal time bias.7
What is immortal time bias?
Immortal time refers to a period of follow-up during which, by design, death or the study outcome cannot occur.8 In pharmacoepidemiology studies, immortal time typically arises when the determination of an individual’s treatment status involves a delay or wait period during which follow-up time is accrued—for example, waiting for a prescription to be dispensed after discharge from hospital when the discharge date represents the start of follow-up (box 1).9 10 11 12 13 14 This wait period is considered immortal because individuals who end up in the treated or exposed group have to survive (be alive and event free) until the treatment definition is fulfilled. If they have an event before taking up treatment they are in the untreated or unexposed group. Bias is introduced when this period of “immortality” is either misclassified with regards to treatment status or excluded from the analysis (fig 1⇓).7 Immortal time …
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