title: Quantifying the impact of survivor treatment bias in observational studies.
abstract: BACKGROUND
  Observational cohort studies are frequently used to measure the impact of therapies on the time to a particular outcome. Treatment often has a time-variant nature since it is frequently initiated at varying times during a patient's follow-up. Studies in the medical literature frequently ignore the time-dependent nature of treatment exposure. Survivor treatment bias can arise when the time dependent nature of treatment exposure is ignored since patients who survived to receive treatment may be healthier than patients who died prior to receipt of treatment.
  
  
  OBJECTIVE
  The objective of the current study was to explicitly quantify the magnitude of survivor-treatment bias.
  
  
  METHODS
  Monte Carlo simulations using parameters obtained from an analysis of patients admitted to hospital with a diagnosis of acute myocardial infarction in Ontario, Canada.
  
  
  CONCLUSIONS
  When the true treatment was null (hazard ratio of 1), estimated treatment effects varied from a 4% reduction in mortality to a reduction in mortality of 27% when the time varying nature of the treatment was ignored. Furthermore, survivor-treatment bias increased as the time required foe exposed patients to receive treatment increased. Similarly, survivor treatment bias was amplified as exposure was defined to be exposure at any time prior to mortality compared to exposure within a fixed time interval starting at the time origin. Ignoring the time-dependent nature of treatment results in overly optimistic estimates of treatment effects. Depending on the period required for patients to initiate therapy, treatments with no effect on survival can appear to be strongly associated with improved survival. The current study is the first to explicitly quantify the magnitude of bias that results from ignoring the time-varying nature of treatment exposure in survival studies.
authors.affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada. peter.austin@ices.on.ca
authors.forename: Peter C
authors.initials: PC
authors.lastname: Austin
authors.forename: Muhammad M
authors.initials: MM
authors.lastname: Mamdani
authors.forename: Carl
authors.initials: C
authors.lastname: van Walraven
authors.forename: Jack V
authors.initials: JV
authors.lastname: Tu
mesh_terms: D000319:Adrenergic beta-Antagonists / Q000627:therapeutic use*; D000368:Aged; D015331:Cohort Studies; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000627:therapeutic use*; D008297:Male; D009010:Monte Carlo Method; D009203:Myocardial Infarction / Q000188:drug therapy* / Q000401:mortality*; D019370:Observation; D009864:Ontario / Q000453:epidemiology; D016016:Proportional Hazards Models; D012372:ROC Curve; D012107:Research Design; D015983:Selection Bias; D017741:Survivors; D013997:Time Factors
chemical_list: D000319:Adrenergic beta-Antagonists; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors