title: Simulation Models of Misclassification Error for Single Thresholds of High-Sensitivity Cardiac Troponin I Due to Assay Bias and Imprecision.
abstract: BACKGROUND
  Clinical outcome studies for cardiac troponins (cTn) are expensive and difficult to design owing to variation in patients, in the assays, and in the incidence of different types of myocardial infarction (MI). To overcome these difficulties, simulation models were used to estimate the rate of misclassification error for MI and risk prediction resulting from assay bias and imprecision.
  
  
  METHODS
  Finite mixture analysis of Abbott high-sensitivity cTnI (hs-cTnI) results at time 0 h in patients presenting early with acute coronary syndrome (ACS) symptoms to the emergency department (ED) [n = 145, Reducing the Time Interval for Identifying New Guideline (RING) study] allowed derivation of a simulation data set (n = 10000). hs-cTnI concentrations were modified by addition of bias or imprecision error. The percentage of all 10000 modified hs-cTnI results that were misclassified for MI at thresholds of 2, 5, 26.2, and 52 ng/L was determined by Monte Carlo simulation. Analyses were replicated with an all-comer emergency department (ED) population (n = 1137) ROMI (Optimum Troponin Cutoffs for ACS in the ED) study.
  
  
  RESULTS
  In the RING study, simulation at 26.2-ng/L (99th percentile) and 52-ng/L thresholds were affected by both bias ±2 ng/L and imprecision (10%-20%) and had misclassification rates of 0.4% to 0.6%. Simulations at the 2-ng/L and 5-ng/L thresholds were only affected by bias. Misclassification rates at bias of ±1 ng/L were 10% for the 2-ng/L threshold, and 5% for the 5-ng/L threshold.
  
  
  CONCLUSIONS
  Simulation models predicted that hs-cTnI results are seldom misclassified (<1% of patients) when interpretative thresholds are near or exceed the overall 99th percentile. However, simulation models also predicted that low hs-cTnI results, as recommended in guidelines, are prone to misclassification of 5%-10% of patients.
authors.affiliation: Department of Pathology and Laboratory Medicine, Saskatoon Health Region, Saskatoon, SK, Canada; andrew.lyon@saskatoonhealthregion.ca.
authors.forename: Andrew W
authors.initials: AW
authors.lastname: Lyon
authors.affiliation: Department of Pathology and Molecular Medicine and.
authors.forename: Peter A
authors.initials: PA
authors.lastname: Kavsak
authors.forename: Oliver A S
authors.initials: OA
authors.lastname: Lyon
authors.affiliation: Division of Emergency Medicine, McMaster University, Hamilton, ON, Canada.
authors.forename: Andrew
authors.initials: A
authors.lastname: Worster
authors.affiliation: Department of Pathology and Laboratory Medicine, Saskatoon Health Region, Saskatoon, SK, Canada.
authors.forename: Martha E
authors.initials: ME
authors.lastname: Lyon
mesh_terms: D054058:Acute Coronary Syndrome / Q000175:diagnosis; D015982:Bias; D003198:Computer Simulation; D006801:Humans; D009010:Monte Carlo Method; D009203:Myocardial Infarction / Q000175:diagnosis; D012107:Research Design; D019210:Troponin I / Q000032:analysis*
chemical_list: D019210:Troponin I