title: A simulation study to compare three self-controlled case series approaches: correction for violation of assumption and evaluation of bias.
abstract: OBJECTIVE
  The assumption that the occurrence of outcome event must not alter subsequent exposure probability is critical for preserving the validity of the self-controlled case series (SCCS) method. This assumption is violated in scenarios in which the event constitutes a contraindication for exposure. In this simulation study, we compared the performance of the standard SCCS approach and two alternative approaches when the event-independent exposure assumption was violated.
  
  
  METHODS
  Using the 2009 H1N1 and seasonal influenza vaccines and Guillain-Barré syndrome as a model, we simulated a scenario in which an individual may encounter multiple unordered exposures and each exposure may be contraindicated by the occurrence of outcome event. The degree of contraindication was varied at 0%, 50%, and 100%. The first alternative approach used only cases occurring after exposure with follow-up time starting from exposure. The second used a pseudo-likelihood method.
  
  
  RESULTS
  When the event-independent exposure assumption was satisfied, the standard SCCS approach produced nearly unbiased relative incidence estimates. When this assumption was partially or completely violated, two alternative SCCS approaches could be used. While the post-exposure cases only approach could handle only one exposure, the pseudo-likelihood approach was able to correct bias for both exposures.
  
  
  CONCLUSIONS
  Violation of the event-independent exposure assumption leads to an overestimation of relative incidence which could be corrected by alternative SCCS approaches. In multiple exposure situations, the pseudo-likelihood approach is optimal; the post-exposure cases only approach is limited in handling a second exposure and may introduce additional bias, thus should be used with caution.
authors.affiliation: Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, Food and Drug Administration, Rockville, MD 20852, USA. wei.hua@fda.hhs.gov
authors.forename: Wei
authors.initials: W
authors.lastname: Hua
authors.forename: Guoying
authors.initials: G
authors.lastname: Sun
authors.forename: Caitlin N
authors.initials: CN
authors.lastname: Dodd
authors.forename: Silvana A
authors.initials: SA
authors.lastname: Romio
authors.forename: Heather J
authors.initials: HJ
authors.lastname: Whitaker
authors.forename: Hector S
authors.initials: HS
authors.lastname: Izurieta
authors.forename: Steven
authors.initials: S
authors.lastname: Black
authors.forename: Miriam C J M
authors.initials: MC
authors.lastname: Sturkenboom
authors.forename: Robert L
authors.initials: RL
authors.lastname: Davis
authors.forename: Genevieve
authors.initials: G
authors.lastname: Deceuninck
authors.forename: N J
authors.initials: NJ
authors.lastname: Andrews
mesh_terms: D015982:Bias; D003198:Computer Simulation; D000075202:Contraindications; D020275:Guillain-Barre Syndrome / Q000453:epidemiology* / Q000209:etiology; D006801:Humans; D015994:Incidence; D053118:Influenza A Virus, H1N1 Subtype; D007252:Influenza Vaccines / Q000008:administration & dosage; D007251:Influenza, Human / Q000517:prevention & control*; D016013:Likelihood Functions; D017891:Pharmacoepidemiology; D011336:Probability; D012107:Research Design; D013997:Time Factors
chemical_list: D007252:Influenza Vaccines
keywords: Guillain-Barré syndrome; assumption; bias; influenza vaccine; pharmacoepidemiology; self-controlled case series; simulation