title: Instrumental variable analysis as a complementary analysis in studies of adverse effects: venous thromboembolism and second-generation versus third-generation oral contraceptives.
abstract: OBJECTIVE
  A potentially useful role for instrumental variable (IV) analysis may be as a complementary analysis to assess the presence of confounding when studying adverse drug effects. There has been discussion on whether the observed increased risk of venous thromboembolism (VTE) for third-generation oral contraceptives versus second-generation oral contraceptives could be (partially) attributed to confounding. We investigated how prescribing preference IV estimates compare with conventional estimates.
  
  
  METHODS
  Women in the Clinical Practice Research Database who started a second-generation or third-generation oral contraceptive from 1989 to 2013 were included. Ordinary least squares and two-stage least squares regression were used to estimate risk differences in VTE. Cox regression and IV for Cox proportional hazards regression were used to calculate hazard ratios (HR). The instrument used was the proportion of prescriptions for third-generation oral contraceptives by the general practitioner in the year preceding the current prescription.
  
  
  RESULTS
  All analyses pointed in the direction of an increased VTE risk for third-generation oral contraceptives. The adjusted HR from the conventional Cox regression was 1.62 (95% confidence interval 1.16-2.27) and the fully adjusted HR from the IV Cox regression was 3.45 (95% confidence interval; 0.97-11.7), showing a larger risk and wider confidence intervals in the IV analysis.
  
  
  CONCLUSIONS
  The similarity in direction of results from the IV analyses and conventional analyses suggests that major confounding is unlikely. IV analysis can be a useful complementary analysis to assess the presence of confounding in studies of adverse drug effects in very large databases.
authors.affiliation: Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.
authors.forename: Anna G C
authors.initials: AG
authors.lastname: Boef
authors.affiliation: Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.
authors.forename: Patrick C
authors.initials: PC
authors.lastname: Souverein
authors.affiliation: Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.
authors.forename: Jan P
authors.initials: JP
authors.lastname: Vandenbroucke
authors.affiliation: Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.
authors.forename: Astrid
authors.initials: A
authors.lastname: van Hylckama Vlieg
authors.affiliation: Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.
authors.forename: Anthonius
authors.initials: A
authors.lastname: de Boer
authors.affiliation: Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.|Department of Medical Statistics and Bioinformatics, Leiden University Medical Centre, Leiden, The Netherlands.
authors.forename: Saskia
authors.initials: S
authors.lastname: le Cessie
authors.affiliation: Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.|Department of Endocrinology and Metabolic Diseases, Leiden University Medical Centre, Leiden, The Netherlands.
authors.forename: Olaf M
authors.initials: OM
authors.lastname: Dekkers
mesh_terms: D000293:Adolescent; D000328:Adult; D015986:Confounding Factors, Epidemiologic; D003277:Contraceptives, Oral, Combined / Q000008:administration & dosage / Q000009:adverse effects*; D003278:Contraceptives, Oral, Hormonal / Q000008:administration & dosage / Q000009:adverse effects*; D016208:Databases, Factual / Q000592:standards*; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D017723:Drug Utilization Review / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D017891:Pharmacoepidemiology / Q000379:methods* / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D020246:Venous Thrombosis / Q000139:chemically induced* / Q000453:epidemiology*; D055815:Young Adult
chemical_list: D003277:Contraceptives, Oral, Combined; D003278:Contraceptives, Oral, Hormonal
keywords: adverse effects; confounding; instrumental variable; pharmacoepidemiology