Literature DB >> 27974385

Simulation Models of Misclassification Error for Single Thresholds of High-Sensitivity Cardiac Troponin I Due to Assay Bias and Imprecision.

Andrew W Lyon1, Peter A Kavsak2, Oliver A S Lyon, Andrew Worster3, Martha E Lyon4.   

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.
© 2016 American Association for Clinical Chemistry.

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Year:  2016        PMID: 27974385     DOI: 10.1373/clinchem.2016.265058

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  9 in total

Review 1.  Toward a Framework for Outcome-Based Analytical Performance Specifications: A Methodology Review of Indirect Methods for Evaluating the Impact of Measurement Uncertainty on Clinical Outcomes.

Authors:  Alison F Smith; Bethany Shinkins; Peter S Hall; Claire T Hulme; Mike P Messenger
Journal:  Clin Chem       Date:  2019-08-23       Impact factor: 8.327

2.  A Simulation Study to Assess the Effect of Analytic Error on Neonatal Glucose Measurements Using the Canadian Pediatric Society Position Statement Action Thresholds.

Authors:  Mark Inman; Kayla Parker; Lannae Strueby; Andrew W Lyon; Martha E Lyon
Journal:  J Diabetes Sci Technol       Date:  2019-11-06

3.  Using the clinical chemistry score in the emergency department to detect adverse cardiac events: a diagnostic accuracy study.

Authors:  Peter A Kavsak; Joshua O Cerasuolo; Dennis T Ko; Jinhui Ma; Jonathan Sherbino; Shawn E Mondoux; Natasha Clayton; Stephen A Hill; Matthew McQueen; Lauren E Griffith; Shamir R Mehta; Richard Perez; Hsien Seow; P J Devereaux; Andrew Worster
Journal:  CMAJ Open       Date:  2020-11-02

4.  Clinical chemistry score versus high-sensitivity cardiac troponin I and T tests alone to identify patients at low or high risk for myocardial infarction or death at presentation to the emergency department.

Authors:  Peter A Kavsak; Johannes T Neumann; Louise Cullen; Martin Than; Colleen Shortt; Jaimi H Greenslade; John W Pickering; Francisco Ojeda; Jinhui Ma; Natasha Clayton; Jonathan Sherbino; Stephen A Hill; Matthew McQueen; Dirk Westermann; Nils A Sörensen; William A Parsonage; Lauren Griffith; Shamir R Mehta; P J Devereaux; Mark Richards; Richard Troughton; Chris Pemberton; Sally Aldous; Stefan Blankenberg; Andrew Worster
Journal:  CMAJ       Date:  2018-08-20       Impact factor: 8.262

Review 5.  Association of High-Sensitivity Cardiac Troponin I Concentration With Cardiac Outcomes in Patients With Suspected Acute Coronary Syndrome.

Authors:  Andrew R Chapman; Kuan Ken Lee; David A McAllister; Louise Cullen; Jaimi H Greenslade; William Parsonage; Andrew Worster; Peter A Kavsak; Stefan Blankenberg; Johannes Neumann; Nils A Sörensen; Dirk Westermann; Madelon M Buijs; Gerard J E Verdel; John W Pickering; Martin P Than; Raphael Twerenbold; Patrick Badertscher; Zaid Sabti; Christian Mueller; Atul Anand; Philip Adamson; Fiona E Strachan; Amy Ferry; Dennis Sandeman; Alasdair Gray; Richard Body; Brian Keevil; Edward Carlton; Kim Greaves; Frederick K Korley; Thomas S Metkus; Yader Sandoval; Fred S Apple; David E Newby; Anoop S V Shah; Nicholas L Mills
Journal:  JAMA       Date:  2017-11-21       Impact factor: 56.272

6.  The Role of Measurement Uncertainty in Health Technology Assessments (HTAs) of In Vitro Tests.

Authors:  Alison F Smith; Mike Messenger; Peter Hall; Claire Hulme
Journal:  Pharmacoeconomics       Date:  2018-07       Impact factor: 4.981

7.  Undetectable Concentrations of a Food and Drug Administration-approved High-sensitivity Cardiac Troponin T Assay to Rule Out Acute Myocardial Infarction at Emergency Department Arrival.

Authors:  Andrew D McRae; Grant Innes; Michelle Graham; Eddy Lang; James E Andruchow; Yunqi Ji; Shabnam Vatanpour; Tasnima Abedin; Hong Yang; Danielle A Southern; Dongmei Wang; Isolde Seiden-Long; Lawrence DeKoning; Peter Kavsak
Journal:  Acad Emerg Med       Date:  2017-08-11       Impact factor: 3.451

Review 8.  Biological variation: Understanding why it is so important?

Authors:  Tony Badrick
Journal:  Pract Lab Med       Date:  2021-01-04

9.  Myocardial Infarction Can Be Safely Excluded by High-sensitivity Troponin I Testing 3 Hours After Emergency Department Presentation.

Authors:  W Frank Peacock; Robert Christenson; Deborah B Diercks; Christian Fromm; Gary F Headden; Christopher J Hogan; Erik B Kulstad; Frank LoVecchio; Richard M Nowak; Jon W Schrock; Adam J Singer; Alan B Storrow; Joely Straseski; Alan H B Wu; Daniel P Zelinski
Journal:  Acad Emerg Med       Date:  2020-03-27       Impact factor: 3.451

  9 in total

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