Time-window Bias in Case-control Studies. Statins and Lung Cancer (Epidemiology 2011; 22 (2):228-31) describes a case-control study which reported a 45% reduction in the rate of lung cancer with any statin use. A differential misclassification bias arose from the methods used to select controls and measure their exposure, which resulted in exposure assessment to statins being based on a shorter time-span for cases than controls and an over-representation of unexposed cases. Properly accounting for time produced a null association.
In many database studies, exposure status during hospitalisations is unknown. Exposure misclassification bias may occur with a direction depending on whether exposure to drugs prescribed preceding hospitalisations are continued or discontinued and if days of hospitalisation are considered as gaps of exposure or not, especially during hospitalisation when several exposure categories are assigned, such as current, recent and past. The differential bias arising from the lack of information on (or lack of consideration of) hospitalisations that occur during the observation period (called “immeasurable time bias” described in Immeasurable Time Bias in Observational Studies on Drug Effects on Mortality. Am J Epidemiol 2008;168 (3):329-35) can be particularly problematic when studying serious chronic diseases that require extensive medication use and multiple hospitalisations.
In the example of case control studies assessing (such as the use of inhaled corticosteroids and death in chronic obstructive pulmonary disease patients), no clearly valid approach to data analysis can fully circumvent this bias. However, sensitivity analyses such as restricting the analysis to nonhospitalised patients or providing estimates weighted by exposable time may provide additional information on the potential impact of this bias (Am J Epidemiol 2008;168 (3):329-35).
In cohort studies where a first-line therapy (such as metformin) has been compared with second- or third-line therapies, patients are unlikely to be at the same stage of the disease (e.g. diabetes), which can induce confounding of the association with an outcome (e.g. cancer incidence) by disease duration. An outcome related to the first-line therapy may also be attributed to the second-line therapy if it occurs after a long period of exposure. Such situation requires matching on disease duration and consideration of latency time windows in the analysis (example drawn from Metformin and the Risk of Cancer. Time-related biases in observational studies. Diabetes Care 2012;35(12):2665-73).
|Annex 1.||Guidance on conducting systematic revies and meta-analyses of completed comparative pharmacoepidemiological studies of safety outcomes|