Systematic assessment of decision-analytic models evaluating diagnostic tests for acute myocardial infarction based on cardiac troponin assays. (2nd November 2018)

• Record Type: Journal Article
• Authors: Veličković, Vladica M.; Rochau, Ursula; Conrads-Frank, Annette; Kee, Frank; Blankenberg, Stefan; Siebert, Uwe
• Is Part Of: Expert review of pharmacoeconomics & outcomes research. Volume 18:Number 6(2018)
• Page Start: 619
• Page End: 640
• Publication Date: 2018-11-02
• Subjects: Cardiac troponin assays -- cost-effectiveness analysis -- decision-analytic models -- NSTEMI -- systematic assessment; Pharmacology -- Economic aspects -- Periodicals; 338.47615105
• DOI: 10.1080/14737167.2018.1512857
• Languages: English
• ISSNs: 1473-7167

Abstract

ABSTRACT: Introduction : Despite the emphasis on the clinical importance of cardiac troponin assays (cTn), there are insufficient cost-effectiveness comparisons of various troponin test protocols for the diagnosis of myocardial infarction (MI). Therefore, the purpose of the review was to identify and systematically assess published economic evaluations using decision-analytic models for diagnostic testing strategies based on cTn and to make recommendations for the development of future models. Areas covered : MEDLINE, Science Direct, Cochrane Database, CRD Database, and gray literature were screened for full economic evaluation studies with relevant clinical outcomes over a defined time horizon addressing a population with suspected MI and comparison of different diagnostic test strategies. Standardized forms for data extraction and evidence tables were used for the summary of study design, methodological framework and data sources. Studies were assessed for quality using the CHEERS and the BMJ checklists. Expert commentary : Although there are 11 identified studies and several well-designed models, there remains a need for decision-analytic models including differential diagnosis for acute MI, different health facility configurations, clinician preferences, and behavioral components, and in the top of the subgroup analyses additional important personalized medicine aspects.