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Clinical pre-test probability for obstructive coronary artery disease: insights from the European DISCHARGE pilot study

S. Feger, P. Ibes, AE. Napp, A. Lembcke, M. Laule, H. Dreger, B. Bokelmann, GK. Davis, G. Roditi, I. Diez, S. Schröder, F. Plank, P. Maurovich-Horvat, R. Vidakovic, J. Veselka, M. Ilnicka-Suckiel, A. Erglis, T. Benedek, J. Rodriguez-Palomares, L....

. 2021 ; 31 (3) : 1471-1481. [pub] 20200909

Language English Country Germany

Document type Clinical Trial, Journal Article

Grant support
EC-GA 603266 FP7 Ideas: European Research Council

OBJECTIVES: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting. METHODS: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA. RESULTS: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001). CONCLUSIONS: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed. TRIAL REGISTRATION: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.

Berlin School of Public Health Berlin Berlin Germany

Centro de Investigación Biomédica en Red CV CIBER CV Barcelona Spain

Charité Universitätsmedizin Berlin Department of Radiology Berlin Institute of Health Berlin Germany

Charité Universitätsmedizin Berlin Humboldt Universität and Freie Universität zu Berlin Berlin Germany

Department of Cardiology Aintree University Hospital Liverpool UK

Department of Cardiology ALB FILS KLINIKEN Goeppingen Germany

Department of Cardiology and Radiology Rigshospitalet University of Copenhagen Copenhagen Denmark

Department of Cardiology Basurto University Hospital Bilbao Bilbao Spain

Department of Cardiology Cardio Med Medical Center Targu Mures Târgu Mureș Romania

Department of Cardiology Centro Hospitalar de Vila Nova de Gaia Vila Nova de Gaia Portugal

Department of Cardiology Clinical Hospital Center Zemun Faculty of Medicine University of Belgrade Zemun Belgrade Serbia

Department of Cardiology Institute for Cardiovascular Diseases of Vojvodina Faculty of Medicine University of Novi Sad Novi Sad Serbia

Department of Cardiology Lithuanian University of Health Sciences Kaunas Lithuania

Department of Cardiology Motol University Hospital and 2nd School of Medicine Charles University Prague Czech Republic

Department of Cardiology Southeastern Health and Social Care Trust Belfast Ireland

Department of Cardiology Wojewodzki Szpital Specjalistyczny We Wroclawiu Wrocław Poland

Department of Diagnostic and Interventional Radiology UNIVERSITY LEIPZIG Heart Center Leipzig Leipzig Germany

Department of Radiological Pathological and Oncological Sciences Sapienza University of Rome Rome Italy

Department of Radiology and Department of Cardiology Medical University Innsbruck Innsbruck Austria

Department of Radiology Azienda Ospedaliero Universitaria di Cagliari Cagliari Italy

Department of Radiology Medical Imaging Centre Semmelweis University Budapest Hungary

Department of Radiology St Vincent's University hospital School of Medicine University College Dublin Dublin Ireland

Dept of Coronary and Structural Heart Diseases Institute of Cardiology Warsaw Poland

DZHK partner site Berlin Germany

Hospital Universitari Vall d´Hebron Department of Cardiology Vall d'Hebron Institut de Recerca Universitat Autònoma de Barcelona Barcelona Spain

Institut für Statistik Medizinische Informatik Datenwissenschaften Universitätsklinikum Jena Leipzig Germany

Institute of Cardiovascular and Medical Sciences Glasgow University Glasgow UK

Latvian Centre of Cardiology Pauls Stradins Clinical University Hospital Riga Latvia

Royal Liverpool and Broadgreen University Hospital Liverpool UK

Turku PET Centre and Heart Centre Turku University Hospital Turku Finland

University of Central Lancashire Liverpool UK

References provided by Crossref.org

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$a OBJECTIVES: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting. METHODS: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA. RESULTS: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001). CONCLUSIONS: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed. TRIAL REGISTRATION: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.
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$a Ibes, Paolo $u Charité - Universitätsmedizin Berlin, Humboldt-Universität and Freie Universität zu Berlin, Berlin, Germany
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$a Napp, Adriane E $u Charité - Universitätsmedizin Berlin, Humboldt-Universität and Freie Universität zu Berlin, Berlin, Germany
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$a Davis, Gershan K $u Department of Cardiology, Aintree University Hospital, Liverpool, UK $u University of Central Lancashire, Liverpool, UK
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$a Roditi, Giles $u Institute of Cardiovascular and Medical Sciences, Glasgow University, Glasgow, UK
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