Applicability and accuracy of pretest probability calculations implemented in the NICE clinical guideline for decision making about imaging in patients with chest pain of recent onset
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To analyse the implementation, applicability and accuracy of the pretest probability calculation provided by NICE clinical guideline 95 for decision making about imaging in patients with chest pain of recent onset.
The definitions for pretest probability calculation in the original Duke clinical score and the NICE guideline were compared. We also calculated the agreement and disagreement in pretest probability and the resulting imaging and management groups based on individual patient data from the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT).
4,673 individual patient data from the CoMe-CCT Consortium were analysed. Major differences in definitions in the Duke clinical score and NICE guideline were found for the predictors age and number of risk factors. Pretest probability calculation using guideline criteria was only possible for 30.8 % (1,439/4,673) of patients despite availability of all required data due to ambiguity in guideline definitions for risk factors and age groups. Agreement regarding patient management groups was found in only 70 % (366/523) of patients in whom pretest probability calculation was possible according to both models.
Our results suggest that pretest probability calculation for clinical decision making about cardiac imaging as implemented in the NICE clinical guideline for patients has relevant limitations.
• Duke clinical score is not implemented correctly in NICE guideline 95.
• Pretest probability assessment in NICE guideline 95 is impossible for most patients.
• Improved clinical decision making requires accurate pretest probability calculation.
• These refinements are essential for appropriate use of cardiac CT.
KeywordsCoronary artery disease Multidetector computed tomography NICE clinical guideline Duke clinical score Pretest probability
Coronary artery calcium score
Coronary artery disease
Collaborative Meta-Analysis of Cardiac CT
Computed tomography angiography
Invasive coronary angiography
National Institute for Health and Care Excellence
Patient management group
The authors of this manuscript state that the CoMe-CCT project received funding from the joint program of the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (BMBF) for meta-analyses.
Compliance with ethical standards
The scientific guarantor of this publication is Marc Dewey.
Conflict of interest
All authors have completed the Unified Competing Interest form at www.icmje.org/disclosure.pdf (available on request from the corresponding author) and declare: RR, VW, PG, WBM, MG, HA, LH, NB, EZ, SL, BG, CR, AAS, BN, AS, MFLM, HB, SMMJ, KAØ, ACPD, AH, BAH, VMR, YLW, JR, MS, CL, SG, EM, HN, AS, KN, GU, ZZ, HM, MC, DAH, DB, RJ, KS, LY, TJ, JPL, RM, SM, JCT, DM, AdR and ML have nothing to disclose. GMS reports grants from German Federal Ministry of Education and Research (BMBF), during the conduct of the study. DA reports other from GE Healthcare, during the conduct of the study; other from GE Healthcare, outside the submitted work. GP reports other from General Electric, other from Bayer, other from Medtronic, other from Heartflow, outside the submitted work. JH reports grants from Siemens Medical Solutions, outside the submitted work. UJS reports grants from Bayer, grants from Bracco, grants from GE, grants from Medrad, grants from Siemens Healthcare, outside the submitted work. JK reports personal fees from Lantheus Inc, grants from Orion Pharma, outside the submitted work. KN reports non-financial support from Siemens Medical Solutions, grants from GE Healthcare, other from Toshiba Medical Systems, non-financial support from Abbott Vascular, grants from Bayer healthcare, outside the submitted work. PK, RRB, and BH report that the University Hospital Zurich holds a research contract with GE Healthcare. JL reports personal fees from GE Healthcare, personal fees from Heartflow, outside the submitted work. BC reports research grants from GE healthcare and educational support from TeraRecon, outside the submitted work. NP reports grants from Toshiba Medical System, outside the submitted work. JH reports grants and personal fees from Toshiba Medical Systems, during the conduct of the study. RH reports grants from Toshiba, outside the submitted work. PS reports grants from Ministry of Education and Research (BMBF) for meta-analyses as part of the joint programme "clinical trials" of the BMBF and the German Science Foundation (DFG), during the conduct of the study; grants from German Science Foundation (DFG), grants from European Union, outside the submitted work. MD has received grant support from the Heisenberg Program of the DFG for a professorship (DE 1361/14-1), the FP7 Program of the European Commission for the randomized multicentre DISCHARGE trial (603266-2, HEALTH-2012.2.4.-2), the European Regional Development Fund (20072013 2/05, 20072013 2/48), the German Heart Foundation/German Foundation of Heart Research (F/23/08, F/27/10), the Joint Program from the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (BMBF) for meta-analyses (01KG1013, 01KG1110, 01KG1110), GE Healthcare, Bracco, Guerbet, and Toshiba Medical Systems. MD has also received lecture fees from Toshiba Medical Systems, Guerbet, Cardiac MR Academy Berlin, and Bayer (Schering-Berlex). MD is a consultant to Guerbet and one of the principal investigators of multicentre studies (CORE-64 and 320) on coronary CT angiography sponsored by Toshiba Medical Systems. He is also the editor of Coronary CT Angiography and Cardiac CT, both published by Springer, and offers hands-on workshops on cardiovascular imaging (www.ct-kurs.de). MD is an associate editor of Radiology and European Radiology. Institutional master research agreements exist with Siemens Medical Solutions, Philips Medical Systems, and Toshiba Medical Systems. The terms of these arrangements are managed by the legal department of Charité – Universitätsmedizin Berlin.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was not required for this study because of the retrospective study design (meta-analysis).
Institutional Review Board approval was not required because of the retrospective study design (meta-analysis).
• diagnostic study
• individual patient data meta-analysis
• multicentre study
- 1.Fihn SD, Gardin JM, Abrams J et al (2012) ACCF/AHA/ACP/AATS/PCNA/SCAI/STS guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology Foundation/American Heart Association task force on practice guidelines, and the American College of Physicians, American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. Circulation 126(25):e354–e471Google Scholar
- 2.Nichols M, Townsend N, Luengo-Fernandez R et al (2012) European Cardiovascular Disease Statistics 2012. Brussels European Heart Network, Brussels, European Society of Cardiology, Sophia AntipolisGoogle Scholar
- 3.Go AS, Mozaffarian D, Roger VL et al (2013) Heart disease and stroke statistics--2013 update: a report from the American Heart Association. Circulation 127(1):e6–e245Google Scholar
- 5.Patel MR, Dai D, Hernandez AF et al (2014) Prevalence and predictors of nonobstructive coronary artery disease identified with coronary angiography in contemporary clinical practice. Am Heart J 167(6):846–52.e2Google Scholar
- 6.Montalescot G, Sechtem U, Achenbach S et al (2013) ESC guidelines on the management of stable coronary artery disease: the Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J 34(38):2949–3003Google Scholar
- 7.Leber AW, Johnson T, Becker A et al (2007) Diagnostic accuracy of dual-source multi-slice CT-coronary angiography in patients with an intermediate pretest likelihood for coronary artery disease. Eur Heart J 28(19):2354–2360Google Scholar
- 9.Meijboom WB,Meijs MF, Schuijf JD et al (2008) Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study. J Am Coll Cardiol 52(25):2135–2144Google Scholar
- 12.Cooper A, Calvert N, Skinner J et al (2010) Chest pain of recent onset: assessment and diagnosis of recent onset chest pain or discomfort of suspected cardiac origin. London: National Clinical Guideline Centre for Acute and Chronic ConditionsGoogle Scholar
- 13.Pryor DB, Shaw L, McCants CB et al (1993) Value of the history and physical in identifying patients at increased risk for coronary artery disease. Ann Intern Med 118(2):81–90Google Scholar
- 14.Schuetz GM, Schlattmann P, Achenbach S et al (2013) Individual patient data meta-analysis for the clinical assessment of coronary computed tomography angiography: protocol of the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT). Syst Rev 2:13Google Scholar
- 16.Diamond GA, Forrester JS (1979) Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N Engl J Med 300(24):1350–1358Google Scholar
- 17.Genders TS, Steyerberg EW, Hunink MG et al (2012) Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts. BMJ 344:e3485Google Scholar
- 18.Cheng VY, Berman DS, Rozanski A et al (2011) Performance of the traditional age, sex, and angina typicality-based approach for estimating pretest probability of angiographically significant coronary artery disease in patients undergoing coronary computed tomographic angiography: results from the multinational coronary CT angiography evaluation for clinical outcomes: an international multicenter registry (CONFIRM). Circulation 124(22):2423–2432 1-8Google Scholar
- 20.Kelly D, Cole S, Rossiter F, Mallinson K, Smith A, Simpson I (2011) Implementation of the new NICE guidelines for stable chest pain: likely impact on chest pain services in the UK. Br J Cardiol 18(4):185–188Google Scholar
- 21.Patterson C, Nicol E, Bryan L et al (2011) The effect of applying NICE guidelines for the investigation of stable chest pain on out-patient cardiac services in the UK. QJM 104(7):581–588Google Scholar
- 23.Patterson CM,Nair A, Ahmed N, Bryan L, Bell D, Nicol ED (2015) Clinical outcomes when applying NICE guidance for the investigation of recent-onset chest pain to a rapid-access chest pain clinic population. Heart 101(2):113–118Google Scholar
- 24.McKavanagh P, Lusk L, Ball PA, Trinick TR, Duly E, Walls GM (2013) A comparison of Diamond Forrester and coronary calcium scores as gatekeepers for investigations of stable chest pain. Int J Card Imaging 29(7):1547–1555Google Scholar
- 25.Pavitt CW, Harron K, Lindsay AC et al (2014) 147 Deriving Coronary Artery Calcium Scores from CT Coronary Angiography: A Potential for Change to the UK Nice Guidelines on Stable Chest Pain. Heart 100(Suppl 3):A85–A86Google Scholar
- 26.Genders TS, Steyerberg EW, Alkadhi H et al (2011) A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension. Eur Heart J 32(11):1316–1330Google Scholar
- 29.Zylka-Menhorn V (2013) Kurswechel löst heftigen Streit aus. Deutsches Ärzteblatt 110(50):A2425–A2426Google Scholar
- 30.Goff DC Jr, Lloyd-Jones DM, Bennett G et al (2014) 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation 129(suppl 2):S49–S73Google Scholar