Systematic review of cost-effectiveness of myocardial perfusion scintigraphy in patients with ischaemic heart disease: A report from the cardiovascular committee of the European Association of Nuclear Medicine. Endorsed by the European Association of Cardiovascular Imaging. (26th May 2017)

• Record Type: Journal Article
• Authors: Trägårdh, Elin; Tan, Siok Swan; Bucerius, Jan; Gimelli, Alessia; Gaemperli, Oliver; Lindner, Oliver; Agostini, Denis; Übleis, Christopher; Sciagrà, Roberto; Slart, Riemer H.; Underwood, S. Richard; Hyafil, Fabien; Hacker, Marcus; Verberne, Hein J.
• Is Part Of: European heart journal. Volume 18:Number 8(2017:Aug.)
• Page Start: 825
• Page End: 832
• Publication Date: 2017-05-26
• Subjects: cost effectiveness -- myocardial perfusion scintigraphy -- ischaemic heart disease; Cardiovascular system -- Imaging -- Periodicals; Heart -- Imaging -- Periodicals; 616.10754
• DOI: 10.1093/ehjci/jex095
• Languages: English
• ISSNs: 2047-2404

Abstract

Abstract: Coronary artery disease (CAD) is a major cause of death and disability. Several diagnostic tests, such as myocardial perfusion scintigraphy (MPS), are accurate for the detection of CAD, as well as having prognostic value for the prediction of cardiovascular events. Nevertheless, the diagnostic and prognostic value of these tests should be cost-effective and should lead to improved clinical outcome. We have reviewed the literature on the cost-effectiveness of MPS in different circumstances: (i) the diagnosis and management of CAD; (ii) comparison with exercise electrocardiography (ECG) and other imaging tests; (iii) as gatekeeper to invasive coronary angiography (ICA), (iv) the impact of appropriate use criteria; (v) acute chest pain, and (vi) screening of asymptomatic patients with type-2 diabetes. In total 57 reports were included. Although most non-invasive imaging tests are cost-effective compared with alternatives, the data conflict on which non-invasive strategy is the most cost-effective. Different definitions of cost-effectiveness further confound the subject. Computer simulations of clinical diagnosis and management are influenced by the assumptions made. For instance, diagnostic accuracy is often defined against an anatomical standard that is wrongly assumed to be perfect. Conflicting data arise most commonly from these incorrect or differing assumptions.