title: Misclassification in assessment of diabetogenic risk using electronic health records.
abstract: OBJECTIVE
  Suspected diabetogenic effects or drug indication may increase testing for diabetes mellitus (DM), resulting in measurement bias when evaluating diabetogenic drug effects. We sought to evaluate the validity of electronic health record data in determining DM risk.
  
  
  METHODS
  We used time-dependent Cox proportional hazard models within a retrospective cohort design to assess associations between use of antihypertensives, statins, atypical antipsychotics, and antidepressants, and two endpoints: (i) DM onset defined as fasting blood glucose (BG) ≥126 mg/dl, random BG ≥200 mg/dl, HbA1c ≥7.0%, or antidiabetic drug initiation; and (ii) first negative DM test. We used Poisson regression to assess the influence of these drugs on DM testing rates. Patients aged 35-64 years enrolled in Kaiser Permanente Northwest between 1997 and 2010 entered the cohort at the first negative BG test after ≥6 months without manifest DM.
  
  
  RESULTS
  All drug classes showed significant associations not only with DM onset but also with first negative BG test and with DM testing rates. Antipsychotics had the greatest diabetogenic risk (adjusted hazard ratio [HR] = 1.73 [1.44-2.08]), the greatest propensity for a first negative test (adjusted HR = 1.87 [1.74-2.01]), and the highest testing rate (adjusted rate ratio = 1.76 [1.72-1.81]. Although renin-angiotensin system blockers and calcium channel blockers have shown no diabetogenic risk in clinical trials, both were associated with DM (HR = 1.19 [1.12-1.26] and 1.27 [1.17-1.38]), a negative glucose test (1.38 [1.35-1.41] and 1.24 [1.20-1.28]), and increased testing rates (rate ratio = 1.26 [1.24-1.27] and 1.27 [1.25-1.28]).
  
  
  CONCLUSIONS
  Caution should be used when diabetogenic risk is evaluated using data that rely on DM testing in general practice.
authors.affiliation: Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, USA; Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL, USA.
authors.forename: Almut G
authors.initials: AG
authors.lastname: Winterstein
authors.forename: Paul
authors.initials: P
authors.lastname: Kubilis
authors.forename: Steve
authors.initials: S
authors.lastname: Bird
authors.forename: Rhonda M
authors.initials: RM
authors.lastname: Cooper-DeHoff
authors.forename: Greg A
authors.initials: GA
authors.lastname: Nichols
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Delaney
mesh_terms: D000328:Adult; D015982:Bias; D001786:Blood Glucose / Q000187:drug effects; D015331:Cohort Studies; D003920:Diabetes Mellitus / Q000139:chemically induced* / Q000453:epidemiology; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D023381:Endpoint Determination; D015340:Epidemiologic Research Design; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016012:Poisson Distribution; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D012306:Risk
chemical_list: D001786:Blood Glucose
keywords: antihypertensives; antipsychotics; diabetogenic risk; drug safety; electronic health records; measurement bias; pharmacoepidemiology; statins