title: Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics.
abstract: BACKGROUND
  Large health care utilization databases are frequently used to analyze unintended effects of prescription drugs and biologics. Confounders that require detailed information on clinical parameters, lifestyle, or over-the-counter medications are often not measured in such datasets, causing residual confounding bias.
  
  
  OBJECTIVE
  This paper provides a systematic approach to sensitivity analyses to investigate the impact of residual confounding in pharmacoepidemiologic studies that use health care utilization databases.
  
  
  METHODS
  Four basic approaches to sensitivity analysis were identified: (1) sensitivity analyses based on an array of informed assumptions; (2) analyses to identify the strength of residual confounding that would be necessary to explain an observed drug-outcome association; (3) external adjustment of a drug-outcome association given additional information on single binary confounders from survey data using algebraic solutions; (4) external adjustment considering the joint distribution of multiple confounders of any distribution from external sources of information using propensity score calibration.
  
  
  CONCLUSIONS
  Sensitivity analyses and external adjustments can improve our understanding of the effects of drugs and biologics in epidemiologic database studies. With the availability of easy-to-apply techniques, sensitivity analyses should be used more frequently, substituting qualitative discussions of residual confounding.
authors.affiliation: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, USA. schneeweiss@post.harvard.edu
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schneeweiss
mesh_terms: D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000009:adverse effects; D052246:Cyclooxygenase 2 Inhibitors / Q000009:adverse effects; D019992:Databases as Topic; D006801:Humans; D017891:Pharmacoepidemiology / Q000706:statistics & numerical data*; D012306:Risk; D012680:Sensitivity and Specificity
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal; D052246:Cyclooxygenase 2 Inhibitors