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Pharmacoepidemiol Drug Saf. 2017 May;26(5):544-553. doi: 10.1002/pds.4193. Epub 2017 Mar 7.

Immeasurable time bias due to hospitalization in medico-administrative databases: which impact for pharmacoepidemiological studies?

Author information

UMR Inserm 1027, Université Toulouse III, Toulouse, France.
Service de Pharmacologie Clinique, CHU de Toulouse, Toulouse, France.
Inserm CIC 1436 Toulouse, CHU de Toulouse, Toulouse, France.
Institut des Neurosciences de la Timone, UMR 7289 CNRS Integrated Pharmacology and Clinical Interface, PiCii, Aix Marseille Université, Marseille, France.
Service de Pharmacologie clinique et pharmacovigilance, APHM, Hôpital de la Timone, Marseille, France.
Département Universitaire de médecine générale, Faculté de médecine, Université de Toulouse, Toulouse, France.
Centre d'addictovigilance (CEIP) PACA-Corse, APHM, Hôpital de la Timone, Marseille, France.



Drugs administered to hospitalized patients are not available within almost all health insurance databases. However, this unobservable exposure time bias is very rarely taken into account in pharmacoepidemiology. The objective was to model unobservable periods due to hospitalization and to assess their impact on risk estimates in the context of the association between benzodiazepines and mortality.


A cohort study was identified using the General Sample of Beneficiaries in France for the period 2006-2012. Benzodiazepines incident users were matched to incident users of antidepressants/non-benzodiazepine sedatives and to controls (non-users) according to age and gender. All-cause mortality at 1 year (Cox regression model) was studied using time-dependent variables (exposed/unexposed or under two hypotheses, inpatients are exposed or inpatients are unexposed), complemented with a multistate model based on observable/unobservable/death status.


In each group, 57 242 patients were included. All-cause mortality was significantly higher among those exposed to benzodiazepines (adjusted hazard ratio (aHR) = 1.17, 95% confidence interval (CI) = 1.04, 1.32), as compared with controls. Use of benzodiazepines exposure as a time-dependent variable resulted in significant results after adjustment (aHR = 1.45, 95%CI = 1.16, 1.80). When inpatients were considered as unexposed, all-cause mortality was not significantly increased (aHR = 0.85, 95%CI = 0.76, 1.10), but was significantly augmented when inpatients were considered as exposed (aHR = 2.93, 95%CI = 2.46, 3.48).


This study highlights the need to take account of the impact of unobservable exposure periods on risk estimates. Copyright © 2017 John Wiley & Sons, Ltd.


benzodiazepines; drug exposure; immeasurable time bias; medico-administrative database; pharmacoepidemiology

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