Left truncation results in substantial bias of the relation between time-dependent exposures and adverse events.
OBJECTIVE
To assess the impact of random left truncation of data on the estimation of time-dependent exposure effects.


METHODS
A simulation study was conducted in which the relation between exposure and outcome was based on an immediate exposure effect, a first-time exposure effect, or a cumulative exposure effect. The individual probability of truncation, the moment of truncation, the exposure rate, and the incidence rate of the outcome were varied in different simulations. All observations before the moment of left truncation were omitted from the analysis.


RESULTS
Random left truncation did not bias estimates of immediate exposure effects, but resulted in an overestimation of a cumulative exposure effect and underestimation of a first-time exposure effect. The magnitude of bias in estimation of cumulative exposure effects depends on a combination of exposure rate, probability of truncation, and proportion of follow-up time left truncated.


CONCLUSIONS
In case of a cumulative or first-time exposure, left truncation can result in substantial bias in pharmacoepidemiologic studies. The potential for this bias likely differs between databases, which may lead to heterogeneity in estimated exposure effects between studies.
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: c.m.hazelbag@umcutrecht.nl.
Christijan M
CM
Hazelbag
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands.
Olaf H
OH
Klungel
Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands; Health eResearch Centre, The Farr Institute of Health Informatics Research, University of Manchester, Manchester, UK.
Tjeerd P
TP
van Staa
Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands.
Anthonius
A
de Boer
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands.
Rolf H H
RH
Groenwold
D015982:Bias; D003198:Computer Simulation; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D006801:Humans; D015233:Models, Statistical; D017891:Pharmacoepidemiology / Q000379:methods*; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012107:Research Design; D013997:Time Factors
Bias; Inception cohort; Simulation study; Time-dependent exposure; Truncation