Quantitative bias analysis for outcome phenotype error correction in comparative effect estimation: an empirical evaluation and simulation study (QBA evaluation)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness

  Effectiveness study (incl. comparative)

  Other
• If ‘other’, further details on the scope of the study:
  Observational research methods

Non-interventional study

• Non-interventional study design:
  Cohort

Population studied

• Age groups:
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)
• Estimated number of subjects:
  6000000

Study design details

• Main study objective:
  1) Empirically evaluate QBA for outcome phenotype error correction in several pharmacoepidemiologic comparative effect estimation scenarios 2) Simulate an analytic space defined by outcome incidence, observed effect estimates, and phenotype measurement errors to determine which QBA input combinations produce valid results
• Data analysis plan:
  Quantitative bias analysis (QBA) provides algebraic adjustment of person counts in an exposure by outcome 2x2 contingency table based on the magnitude of outcome misclassification. We will evaluate the impact of QBA for outcome phenotype error correction in several empirical and simulated comparative effect estimation pharmacoepidemiologic scenarios. We will evaluate QBA performance with several bias correction metrics.