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. 2025 Aug;4(8):102014.
doi: 10.1016/j.jacadv.2025.102014. Epub 2025 Jul 28.

Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT

Viktoria Wieske  1 , Mario Walther  2 , Mahmoud Mohamed  1 , Benjamin Weickert  1 , Simon Andrzejewski  1 , Benjamin Dubourg  3 , Daniele Andreini  4 , Gianluca Pontone  4 , Hatem Alkadhi  5 , Jörg Hausleiter  6 , Mario J Garcia  7 , Sebastian Leschka  8 , Willem B Meijboom  9 , Elke Zimmermann  1 , Bernhard Gerber  10 , U Joseph Schoepf  11 , Abbas A Shabestari  12 , Bjarne L Nørgaard  13 , Matthijs Fl Meijs  14 , Akira Sato  15 , Kristian A Øvrehus  16 , Axel Cp Diederichsen  16 , Shona M Jenkins  17 , Juhani Knuuti  18 , Ashraf Hamdan  19 , Bjørn A Halvorsen  20 , Vladimir Mendoza Rodriguez  21 , Carlos Rochitte  22 , Johannes Rixe  23 , Yung-Liang Wan  24 , Christoph Langer  25 , Nuno Bettencourt  26 , Eugenio Martuscelli  27 , Said Ghostine  28 , Ronny R Buechel  29 , Konstantin Nikolaou  30 , Hans Mickley  16 , Lin Yang  31 , Zhaqoi Zhang  31 , Marcus Y Chen  32 , David A Halon  33 , Matthias Rief  1 , Kai Sun  34 , Hiroyuki Niinuma  35 , Roy P Marcus  36 , Simone Muraglia  37 , Réda Jakamy  38 , Benjamin Jw Chow  39 , Philipp A Kaufmann  29 , Bernhard A Herzog  40 , Jean-Claude Tardif  41 , Cesar Nomura  42 , Klaus F Kofoed  43 , Jean-Pierre Laissy  44 , Armin Arbab-Zadeh  45 , Kakuya Kitagawa  46 , Roger Laham  47 , Masahiro Jinzaki  48 , John Hoe  49 , Frank J Rybicki  50 , Arthur Scholte  51 , Narinder Paul  52 , Swee Yaw Tan  53 , Kunihiro Yoshioka  54 , Robert Roehle  1 , Georg M Schuetz  1 , Michael Laule  55 , David E Newby  56 , Stephan Achenbach  57 , Matthew Budoff  58 , Robert Haase  1 , Jonathan D Dodd  59 , Marc Dewey  60 , Peter Schlattmann  61 ; COME-CCT Consortium
Affiliations

Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT

Viktoria Wieske et al. JACC Adv. 2025 Aug.

Abstract

Background: Combining pretest probability (PTP) with computed tomography angiography (CTA) for diagnosing obstructive coronary artery disease (CAD) has not yet been determined.

Objectives: The purpose of this study was to evaluate the accuracy of PTP calculation alone and with CTA for diagnosing CAD.

Methods: A total of 65 prospective diagnostic accuracy studies of patients clinically referred to invasive coronary angiography with stable chest pain were included in this international collaborative individual patient data Collaborative Meta-Analysis of Cardiac CT (COME-CCT) meta-analysis. Mixed-effects logistic regression with a data set-specific random intercept for clustering was applied to 4 models: the traditional Diamond-Forrester models, a PTP model based on the COME-CCT data (termed COME-CCT-PTP calculator), a CTA alone model, and a combined COME-CCT-PTP with CTA model.

Results: Individual patient data from 5,332 patients with clinically indicated invasive coronary angiography from 22 countries were included. The COME-CCT-PTP calculator was more accurate than the original Diamond-Forrester model (AUC: 0.68; 95% CI: 0.66-0.69 vs 0.63; 95% CI: 0.62-0.65). The COME-CCT-PTP with CTA model significantly improved accuracy compared with either model alone (AUC: 0.86; 95% CI: 0.85-0.87 vs 0.81; 95% CI: 0.80-0.82). The improved prediction was consistent in decision curve analysis with an increased net benefit for all chest pain subtypes and was almost equally seen in patients with typical or atypical angina (0.85; 95% CI: 0.84-0.86) and nonanginal or other chest discomfort (0.88; 95% CI: 0.86-0.89).

Conclusions: Combining the COME-CCT-PTP calculator with CTA provides more accurate prediction than the PTP or CTA alone for the diagnosis of obstructive CAD, for all chest pain subtypes.

Keywords: computed tomography angiography; coronary artery disease; disease probability; individual patient data meta-analysis; stable chest pain.

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Conflict of interest statement

Funding support and author disclosures The COME-CCT Consortium is funded by a joint program of the German Research Foundation and the German Federal Ministry of Education and Research (01KG1110) and the Digital Health Accelerator of the Berlin Institute of Health to Dr Dewey. All researchers are independent of the funding bodies. The funding bodies had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the manuscript for publication. Dr Wieske has received grant support from the FP7 Program of the European Commission for the randomized multicenter DISCHARGE trial (603266-2, HEALTH-2012.2.4.-2). Dr Pontone has received other grants from General Electric, grants from General Electric, other from Medtronic, other from Bracco, outside the submitted work. Dr Hoe is on the Speakers Bureau for Abbott Vascular and Edwards Lifesciences. Dr Gerber reports that the Cliniques St Luc UCL holds a master research agreement with Philips Medical Systems. Dr Schoepf has received institutional grants, personal fees, and nonfinancial support from Astellas, Bayer, General Electric, Guerbet, HeartFlow, and Siemens. Dr Nørgaard has received grants from Siemens and HeartFlow. AS has received personal fees from General Electric and Toshiba. Dr Knuuti has received grants from CardiRad and personal fees from GE Healthcare. Dr Buechel reports that the University Hospital Zurich holds a research contract with GE Healthcare. Dr Nikolaou reports collaborations with and project funding from Siemens Healthineers, Bayer Healthcare, GE Healthcare, and Speakers Bureau: Siemens Healthineers, Bayer Healthcare. Dr Chen has received an institutional research agreement with Canon Medical, formerly Toshiba Medical (no financial support/funding). Dr Halon has received other grant from Philips Healthcare, Cleveland, Ohio, during the conduct of the primary study. Dr Chow holds the Saul and Edna Goldfarb Chair in Cardiac Imaging Research; has received research support from GE Healthcare and educational support from TeraRecon Inc during the conduct of the study. Dr Kaufmann reports that the University Hospital Zurich holds a research agreement with GE Healthcare. Dr Arbab-Zadeh has received grant support from Canon Medical Systems. Dr Paul is on the Speakers Bureau for Toshiba Medical Systems; and has received grants from Toshiba Medical Systems, outside the submitted work. Dr Schuetz has received grants support for his salary from German Federal Ministry of Education and Research (BMBF) during the conduct of the study. Dr Dewey has received grant support from the FP7 Program of the European Commission for the randomized multicenter DISCHARGE trial (603266-2, HEALTH-2012.2.4.-2); also has received grant support from German Research Foundation (DFG) in the Heisenberg Program (DE 1361/14-1), graduate program on quantitative biomedical imaging (BIOQIC, GRK 2260/1), for fractal analysis of myocardial perfusion (DE 1361/18-1), the Priority Programme Radiomics for the investigation of coronary plaque and coronary flow (DE 1361/19-1 [428222922] and 20-1 [428223139] in SPP 2177/1); and also received funding from the Berlin University Alliance (GC_SC_PC 27) and from the Digital Health Accelerator of the Berlin Institute of Health. Dr Dewey has received lecture fees from Canon, Guerbet. Prof Dodd has received grant support from the Irish Lung Foundation, the St. Vincent’s Hospital Group Foundation, University College Dublin, and the FP7 Program of the European Commission for the randomized multicenter DISCHARGE trial (603266-2, HEALTH-2012.2.4.-2); is an associate editor of Radiology, Respirology, and the Quarterly Journal of Medicine; is an Editorial Board member of Radiology Cardiothoracic Imaging; and is an author in the Stat-Dx book Series Diagnostic Imaging – Cardiovascular and the textbook CT and MRI in Cardiology, Elsevier and the opinions expressed in this article are the author’s own and do not represent the view of ESR. Per the guiding principles of ESR, the work as Research Chair is on a voluntary basis and only remuneration of travel expenses occurs. Dr Dewey is also the editor of Cardiac CT, published by Springer Nature, and offers hands-on courses on CT imaging (www.ct-kurs.de). Institutional master research agreements exist with Siemens, General Electric, Philips, and Canon. The terms of these arrangements are managed by the legal department of Charité–Universitätsmedizin Berlin. Dr Dewey holds a joint patent with Florian Michallek on dynamic perfusion analysis using fractal analysis (PCT/EP2016/071551). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

None
Graphical abstract
Figure 1
Figure 1
Eligibility Assessment and Inclusion Patients with stable chest pain, complete information on age, sex, and chest pain symptom, without known CAD and information on ICA and CTA were available for inclusion. CAD = coronary artery disease; CTA = computed tomography angiography; ICA = invasive coronary angiography.
Figure 2
Figure 2
Discriminative Ability of Prediction Models Panel (A) shows the receiver-operating characteristic (ROC) curves of the clinical probability prediction (PTP) models. The COME-CCT-PTP calculator (red) and updated Diamond-Forrester model (gray) resulted in significantly improved discrimination compared to the original Diamond-Forrester model (black). Panel (B) shows the significantly improved discriminative ability using the combination of the COME-CCT-PTP calculator with CTA (solid blue) compared to CTA alone (dashed blue). COME-CCT = Collaborative Meta-Analysis of Cardiac CT; DICAD = updated Diamond-Forrester model; other abbreviation as in Figure 1.
Figure 3
Figure 3
Decision Curves of the COME-CCT-PTP Calculator Alone, CTA Alone, and Combined COME-CCT-PTP Calculator and CTA The figure shows the net benefit of the COME-CCT-PTP calculator alone (red), combined with CTA (blue) and CTA alone (dashed blue) as a function of threshold probability. Patients are classified as test-positive (diagnosed with obstructive CAD) or test-negative (no CAD) based on their CAD probability. The net benefit based on the CTA alone model performed better than the COME-CCT-PTP calculator, and further improved by the combination. The black line represents the net benefit of considering all patients as having no CAD; the gray line represents the net benefit of considering all patients to have obstructive CAD. The intersection of the black with the gray line indicates the prevalence of obstructive CAD (48.3%) in our patient sample. PTP = pretest probability; other abbreviations as in Figure 1, Figure 2.
Central Illustration
Central Illustration
Combining Pretest Probability Calculator With Cardiac CT Abbreviations as in Figure 1, Figure 2.
See this image and copyright information in PMC

References

    1. Mensah G.A., Fuster V., Murray C.J.L., Roth G.A. Global burden of cardiovascular diseases and risks, 1990-2022. J Am Coll Cardiol. 2023;82:2350–2473. - PMC - PubMed
    1. Lampe F.C., Morris R.W., Walker M., Shaper A.G., Whincup P.H. Trends in rates of different forms of diagnosed coronary heart disease, 1978 to 2000: prospective, population based study of British men. BMJ. 2005;330:1046. - PMC - PubMed
    1. George J., Rapsomaniki E., Pujades-Rodriguez M., et al. How does cardiovascular disease first present in women and men? Incidence of 12 cardiovascular diseases in a contemporary cohort of 1,937,360 people. Circulation. 2015;132:1320–1328. - PMC - PubMed
    1. Hemingway H., McCallum A., Shipley M., Manderbacka K., Martikainen P., Keskimäki I. Incidence and prognostic implications of stable angina pectoris among women and men. JAMA. 2006;295:1404–1411. - PubMed
    1. Buckley B., Murphy A.W. Do patients with angina alone have a more benign prognosis than patients with a history of acute myocardial infarction, revascularisation or both? Findings from a community cohort study. Heart. 2009;95:461–467. - PubMed