title: When should case-only designs be used for safety monitoring of medical products?
abstract: OBJECTIVE
  To assess case-only designs for surveillance with administrative databases.
  
  
  METHODS
  We reviewed literature on two designs that are observational analogs to crossover experiments: the self-controlled case series (SCCS) and the case-crossover (CCO) design.
  
  
  RESULTS
  SCCS views the 'experiment' prospectively, comparing outcome risks in windows with different exposures. CCO retrospectively compares exposure frequencies in case and control windows. The main strength of case-only designs is they entail self-controlled analyses that eliminate confounding and selection bias by time-invariant characteristics not recorded in healthcare databases. They also protect privacy and are computationally efficient, as they require fewer subjects and variables. They are better than cohort designs for investigating transient effects of accurately recorded preventive agents, for example, vaccines. They are problematic if timing of self-administration is sporadic and dissociated from dispensing times, for example, analgesics. They tend to have less exposure misclassification bias and time-varying confounding if exposures are brief. Standard SCCS designs are bidirectional (using time both before and after the first exposure event), so they are more susceptible than CCOs to reverse-causality bias, including immortal-time bias. This is true also for sequence symmetry analysis, a simplified SCCS. Unidirectional CCOs use only time before the outcome, so they are less affected by reverse causality but susceptible to exposure-trend bias. Modifications of SCCS and CCO partially deal with these biases. The head-to-head comparison of multiple products helps to control residual biases.
  
  
  CONCLUSIONS
  The case-only analyses of intermittent users complement the cohort analyses of prolonged users because their different biases compensate for one another.
authors.affiliation: Department Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada. malcolm.maclure@gov.bc.ca
authors.forename: Malcolm
authors.initials: M
authors.lastname: Maclure
authors.forename: Bruce
authors.initials: B
authors.lastname: Fireman
authors.forename: Jennifer C
authors.initials: JC
authors.lastname: Nelson
authors.forename: Wei
authors.initials: W
authors.lastname: Hua
authors.forename: Azadeh
authors.initials: A
authors.lastname: Shoaibi
authors.forename: Antonio
authors.initials: A
authors.lastname: Paredes
authors.forename: David
authors.initials: D
authors.lastname: Madigan
mesh_terms: D015331:Cohort Studies; D015986:Confounding Factors, Epidemiologic; D018592:Cross-Over Studies; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions; D015340:Epidemiologic Research Design; D004864:Equipment and Supplies / Q000009:adverse effects; D006801:Humans; D017891:Pharmacoepidemiology / Q000379:methods; D018907:Privacy; D011358:Product Surveillance, Postmarketing / Q000379:methods*; D015983:Selection Bias; D012646:Self Administration; D013997:Time Factors