Time‐related biases in perinatal pharmacoepidemiology: A systematic review of observational studies

Abstract

Background: Time-related biases, such as immortal time and time-window bias, frequently occur in pharmacoepidemiologic research. However, the prevalence of these biases in perinatal pharmacoepidemiology is not well understood.Objective: To describe the frequency of time-related biases in observational studies of medications commonly used during pregnancy (antibiotic, antifungal, and antiemetic drugs) via systematic review.Method: We searched Medline and EMBASE for observational studies published between January 2013 and September 2020 and examining the association between antibiotic, antifungal, or antiemetic drugs and adverse pregnancy outcomes, including spontaneous abortion, stillbirth, preterm delivery, small-for-gestational age, preeclampsia, and gestational diabetes. The proportion of studies with time-related biases was estimated overall and by type (immortal time bias, time-window bias).Results: Our systematic review included 20 studies (16 cohort studies, 3 nested case-control studies, and 1 case-control study), of which 12 examined antibiotic, 6 antiemetic, and 2 anti-fungal drugs. Eleven studies (55%) had immortal time bias due to the misclassification of unexposed, event-free person-time between cohort entry and exposure initiation as exposed. No included study had time-window bias.The direction of effect varied for both studies with and without time-related bias, with many studies reporting very wide confidence intervals around the effect estimates, thus making the direction of effect less interpretable. However, studies with time-related bias were more likely to show protective or null associations compared with studies without time-related bias.Conclusion: Time-related biases occur frequently in observational studies of drug effects during pregnancy. The use of appropriate study design and analytical approaches is needed to prevent time-related biases and ensure study validity.immortal time bias, pharmacoepidemiology, pregnancy, systematic review, time-related bias, time-window bias Key Points• Time-related biases, such as immortal time and time-window bias, frequently occur in pharmacoepidemiologic research, but their prevalence in the perinatal pharmacoepidemiologic literature is unknown.

Interventions to improve perinatal outcomes among migrant women in high-income countries: a systematic review protocol

“…Studies including antenatal interventions and subsequent perinatal outcomes can be affected by time-related biases if women are recruited at various points throughout their pregnancy, that is, person-time of observation is not properly accounted for in the design or analysis of a study. 22 We are unable to adjust for these biases in quantitatively synthesising our findings, but will consider the implications of this in our conclusions. We are taking a coproduction approach to the planning, conducting and interpretation of this work by ensuring migrant women who have given birth or been pregnant in their host country are involved throughout.…”

“…Additionally, we are only including studies conducted in HICs which means we may miss effective interventions which were developed and tested in LMICs. Studies including antenatal interventions and subsequent perinatal outcomes can be affected by time-related biases if women are recruited at various points throughout their pregnancy, that is, person-time of observation is not properly accounted for in the design or analysis of a study 22. We are unable to adjust for these biases in quantitatively synthesising our findings, but will consider the implications of this in our conclusions.…”

Emulating Target Trials to Avoid Immortal Time Bias – An Application to Antibiotic Initiation and Preterm Delivery

“…However, analyses of observational data are susceptible to confounding, selection bias, and misclassification bias, especially in the setting of time-varying exposures. Immortal time bias, a bias that can be introduced when treatment initiation occurs after time zero of followup, [1][2][3] is particularly common in observational studies of medication safety and effectiveness in pregnancy, where exposures are often defined as "at any time during a period." [4][5][6][7][8][9][10][11][12] Target trial emulation aids researchers in defining causal estimands and attempting to estimate corresponding causal effects from observational data.…”

“…We apply this approach to identify the safety of antibiotic initiation between 24 and 37 weeks gestation with respect to preterm delivery, an association that has been extensively explored in the literature and that has led to conflicting results. 3,10 We use data from the Tsepamo Study, which has been conducting birth outcomes surveillance throughout Botswana since 2014.…”