Purpose: Recent observational studies suggest that various drugs are remarkably effective at reducing morbidity and mortality. These cohort studies used a flawed approach to design and data analysis which can lead to immortal time bias. We describe the bias from 20 of these studies and illustrate it by showing that unrelated drugs can be made to appear effective at treating cardiovascular disease (CVD).
Methods: The illustration used a cohort of 3315 patients, with chronic obstructive pulmonary disease (COPD), identified from the Saskatchewan Health databases, hospitalised for CVD and followed for up to a year. We used the biased approach to assess the effect of two medications, namely gastrointestinal drugs (GID) and inhaled beta-agonists (IBA), both unknown to be effective in CVD, on the risk of all-cause mortality. We also estimated these effects using the proper person-time approach.
Results: Using the inappropriate approach, the rates ratios of all-cause death were 0.73 (95%CI: 0.57-0.93), with IBA and 0.78 (95%CI: 0.61-0.99), with GID. These rate ratios became 0.98 (95%CI: 0.77-1.25) and 0.94 (95%CI: 0.73-1.20), respectively, with the proper person-time analysis.
Conclusions: Several recent observational studies used a flawed approach to design and data analysis, leading to immortal time bias, which can generate an illusion of treatment effectiveness. Observational studies, with surprising beneficial drug effects should be re-assessed to account for this source of bias.
(c) 2007 John Wiley & Sons, Ltd.