Observational studies are commonly used to evaluate the association between a risk factor or “exposure” and the time that elapses until an outcome of interest occurs (eg, smoking decreasing the time to cardiovascular death). This relationship may be assessed by analyzing natural variation in the exposure and patient outcomes. Such studies may be subject to immortal time bias, meaning that, during the period of observation, there is some interval during which the outcome event cannot occur. The research participants are “immortal” in that they must survive long enough to receive the intervention being studied. An example of immortal time bias can be found in a study by Honigberg et al1 that evaluated the hypothesis that menopause occurring before age 40 years is associated with the development of cardiovascular disease (CVD). In that study, the authors examined CVD outcomes for postmenopausal women aged 40 to 69 years using the UK BioBank and found an increased risk of CVD associated with both natural premature menopause (hazard ratio, 1.36 [95% CI, 1.19-1.56]) and surgical premature menopause (hazard ratio, 1.87 [1.36-2.58]), relative to women who had experienced normally timed menopause.
Yadav K, Lewis RJ. Immortal Time Bias in Observational Studies. JAMA. 2021;325(7):686–687. doi:10.1001/jama.2020.9151
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