BACKGROUND: Current practice for suspected acute coronary syndrome (ACS) involves troponin testing 10-12 hours after symptom onset to diagnose myocardial infarction (MI). Patients with a negative troponin can be investigated further with computed tomographic coronary angiography (CTCA) or exercise electrocardiography (ECG). OBJECTIVES: We aimed to estimate the diagnostic accuracy of early biomarkers for MI, the prognostic accuracy of biomarkers for major adverse cardiac adverse events (MACEs) in troponin-negative patients, the diagnostic accuracy of CTCA and exercise ECG for coronary artery disease (CAD) and the prognostic accuracy of CTCA and exercise ECG for MACEs in patients with suspected ACS. We then aimed to estimate the cost-effectiveness of using alternative biomarker strategies to diagnose MI, and using biomarkers, CTCA and exercise ECG to risk-stratify troponin-negative patients. DATA SOURCES: We searched MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations; Cumulative Index of Nursing and Allied Health Literature (CINAHL), EMBASE, Web of Science, Cochrane Central Database of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews (CDSR), NHS Database of Abstracts of Reviews of Effects (DARE) and the Health Technology Assessment database from 1985 (CTCA review) or 1995 (biomarkers review) to November 2010, reviewed citation lists and contacted experts to identify relevant studies. REVIEW METHODS: Diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool and prognostic studies using a framework adapted for the project. Meta-analysis was conducted using bayesian Markov chain Monte Carlo simulation. We developed a decision-analysis model to evaluate the cost-effectiveness of alternative biomarker strategies to diagnose MI, and the cost-effectiveness of biomarkers, CTCA or exercise ECG to risk-stratify patients with a negative troponin. Strategies were applied to a theoretical cohort of patients with suspected ACS. Cost-effectiveness was estimated as the incremental cost per quality-adjusted life-year (QALY) of each strategy compared with the next most effective, taking a health-service perspective and a lifetime horizon. RESULTS: Sensitivity and specificity (95% predictive interval) were 77% (29-96%) and 93% (46-100%) for troponin I, 80% (33-97%) and 91% (53-99%) for troponin T (99th percentile threshold), 81% (50-95%) and 80% (26-98%) for quantitative heart-type fatty acid-binding protein (H-FABP), 68% (11-97%) and 92% (20-100%) for qualitative H-FABP, 77% (19-98%) and 39% (2-95%) for ischaemia-modified albumin and 62% (35-83%) and 83% (35-98%) for myoglobin. CTCA had 94% (61-99%) sensitivity and 87% (16-100%) specificity for CAD. Positive CTCA and positive-exercise ECG had relative risks of 5.8 (0.6-24.5) and 8.0 (2.3-22.7) for MACEs. In most scenarios in the economic analysis presentation, high-sensitivity troponin measurement was the most effective strategy with an incremental cost-effectiveness ratio (ICER) of less than the £20,000-30,000/QALY threshold (ICER £7487-17,191/QALY). CTCA appeared to be the most cost-effective strategy for patients with a negative troponin, with an ICER of £11,041/QALY. However, when a lower MACE rate was assumed, CTCA had a high ICER (£262,061/QALY) and the no-testing strategy was optimal. LIMITATIONS: There was substantial variation between the primary studies and heterogeneity in their results. Findings of the economic model were dependent on assumptions regarding the value of detecting and treating positive cases. CONCLUSIONS: Although presentation troponin has suboptimal sensitivity, measurement of a 10-hour troponin level is unlikely to be cost-effective in most scenarios compared with a high-sensitivity presentation troponin. CTCA may be a cost-effective strategy for troponin-negative patients, but further research is required to estimate the effect of CTCA on event rates and health-care costs. FUNDING: The National Institute for Health Research Health Technology Assessment programme.
BACKGROUND: Current practice for suspected acute coronary syndrome (ACS) involves troponin testing 10-12 hours after symptom onset to diagnose myocardial infarction (MI). Patients with a negative troponin can be investigated further with computed tomographic coronary angiography (CTCA) or exercise electrocardiography (ECG). OBJECTIVES: We aimed to estimate the diagnostic accuracy of early biomarkers for MI, the prognostic accuracy of biomarkers for major adverse cardiac adverse events (MACEs) in troponin-negative patients, the diagnostic accuracy of CTCA and exercise ECG for coronary artery disease (CAD) and the prognostic accuracy of CTCA and exercise ECG for MACEs in patients with suspected ACS. We then aimed to estimate the cost-effectiveness of using alternative biomarker strategies to diagnose MI, and using biomarkers, CTCA and exercise ECG to risk-stratify troponin-negative patients. DATA SOURCES: We searched MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations; Cumulative Index of Nursing and Allied Health Literature (CINAHL), EMBASE, Web of Science, Cochrane Central Database of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews (CDSR), NHS Database of Abstracts of Reviews of Effects (DARE) and the Health Technology Assessment database from 1985 (CTCA review) or 1995 (biomarkers review) to November 2010, reviewed citation lists and contacted experts to identify relevant studies. REVIEW METHODS: Diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool and prognostic studies using a framework adapted for the project. Meta-analysis was conducted using bayesian Markov chain Monte Carlo simulation. We developed a decision-analysis model to evaluate the cost-effectiveness of alternative biomarker strategies to diagnose MI, and the cost-effectiveness of biomarkers, CTCA or exercise ECG to risk-stratify patients with a negative troponin. Strategies were applied to a theoretical cohort of patients with suspected ACS. Cost-effectiveness was estimated as the incremental cost per quality-adjusted life-year (QALY) of each strategy compared with the next most effective, taking a health-service perspective and a lifetime horizon. RESULTS: Sensitivity and specificity (95% predictive interval) were 77% (29-96%) and 93% (46-100%) for troponin I, 80% (33-97%) and 91% (53-99%) for troponin T (99th percentile threshold), 81% (50-95%) and 80% (26-98%) for quantitative heart-type fatty acid-binding protein (H-FABP), 68% (11-97%) and 92% (20-100%) for qualitative H-FABP, 77% (19-98%) and 39% (2-95%) for ischaemia-modified albumin and 62% (35-83%) and 83% (35-98%) for myoglobin. CTCA had 94% (61-99%) sensitivity and 87% (16-100%) specificity for CAD. Positive CTCA and positive-exercise ECG had relative risks of 5.8 (0.6-24.5) and 8.0 (2.3-22.7) for MACEs. In most scenarios in the economic analysis presentation, high-sensitivity troponin measurement was the most effective strategy with an incremental cost-effectiveness ratio (ICER) of less than the £20,000-30,000/QALY threshold (ICER £7487-17,191/QALY). CTCA appeared to be the most cost-effective strategy for patients with a negative troponin, with an ICER of £11,041/QALY. However, when a lower MACE rate was assumed, CTCA had a high ICER (£262,061/QALY) and the no-testing strategy was optimal. LIMITATIONS: There was substantial variation between the primary studies and heterogeneity in their results. Findings of the economic model were dependent on assumptions regarding the value of detecting and treating positive cases. CONCLUSIONS: Although presentation troponin has suboptimal sensitivity, measurement of a 10-hour troponin level is unlikely to be cost-effective in most scenarios compared with a high-sensitivity presentation troponin. CTCA may be a cost-effective strategy for troponin-negative patients, but further research is required to estimate the effect of CTCA on event rates and health-care costs. FUNDING: The National Institute for Health Research Health Technology Assessment programme.
Authors: Christopher Layfield; John Rose; Aaron Alford; Susan R Snyder; Fred S Apple; Farah M Chowdhury; Michael C Kontos; L Kristin Newby; Alan B Storrow; Milenko Tanasijevic; Elizabeth Leibach; Edward B Liebow; Robert H Christenson Journal: Clin Biochem Date: 2015-02-07 Impact factor: 3.281
Authors: Dirk Westermann; Johannes Tobias Neumann; Nils Arne Sörensen; Stefan Blankenberg Journal: Nat Rev Cardiol Date: 2017-04-06 Impact factor: 32.419
Authors: Leslee J Shaw; Ron Blankstein; Jill E Jacobs; Jonathon A Leipsic; Raymond Y Kwong; Viviany R Taqueti; Rob S B Beanlands; Jennifer H Mieres; Scott D Flamm; Thomas C Gerber; John Spertus; Marcelo F Di Carli Journal: Circ Cardiovasc Imaging Date: 2017-12 Impact factor: 7.792