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

Viktoria Wieske; Mario Walther; Mahmoud Mohamed; Benjamin Weickert; Simon Andrzejewski; Benjamin Dubourg; Daniele Andreini; Gianluca Pontone; Hatem Alkadhi; Jörg Hausleiter; Mario J. Garcia; Sebastian Leschka; Willem B. Meijboom; Elke Zimmermann; Bernhard Gerber; U. Joseph Schoepf; Abbas A. Shabestari; Bjarne L. Nørgaard; Matthijs FL Meijs; Akira Sato; Kristian A. Øvrehus; Axel CP Diederichsen; Shona M. Jenkins; Juhani Knuuti; Ashraf Hamdan; Bjørn A. Halvorsen; Vladimir Mendoza Rodriguez; Carlos Rochitte; Johannes Rixe; Yung Liang Wan; Christoph Langer; Nuno Bettencourt; Eugenio Martuscelli; Said Ghostine; Ronny R. Buechel; Konstantin Nikolaou; Hans Mickley; Lin Yang; Zhaqoi Zhang; Marcus Y. Chen; David A. Halon; Matthias Rief; Kai Sun; Hiroyuki Niinuma; Roy P. Marcus; Simone Muraglia; Réda Jakamy; Benjamin JW Chow; Philipp A. Kaufmann; Bernhard A. Herzog

doi:10.1016/j.jacadv.2025.102014

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

Viktoria Wieske, Mario Walther, Mahmoud Mohamed, Benjamin Weickert, Simon Andrzejewski, Benjamin Dubourg, Daniele Andreini, Gianluca Pontone, Hatem Alkadhi, Jörg Hausleiter, Mario J. Garcia, Sebastian Leschka, Willem B. Meijboom, Elke Zimmermann, Bernhard Gerber, U. Joseph Schoepf, Abbas A. Shabestari, Bjarne L. Nørgaard, Matthijs FL Meijs, Akira SatoKristian A. Øvrehus, Axel CP Diederichsen, Shona M. Jenkins, Juhani Knuuti, Ashraf Hamdan, Bjørn A. Halvorsen, Vladimir Mendoza Rodriguez, Carlos Rochitte, Johannes Rixe, Yung Liang Wan, Christoph Langer, Nuno Bettencourt, Eugenio Martuscelli, Said Ghostine, Ronny R. Buechel, Konstantin Nikolaou, Hans Mickley, Lin Yang, Zhaqoi Zhang, Marcus Y. Chen, David A. Halon, Matthias Rief, Kai Sun, Hiroyuki Niinuma, Roy P. Marcus, Simone Muraglia, Réda Jakamy, Benjamin JW Chow, Philipp A. Kaufmann, Bernhard A. Herzog,

Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Article number	102014
Journal	JACC: Advances
Volume	4
Issue number	8
DOIs	https://doi.org/10.1016/j.jacadv.2025.102014
Publication status	Published - Aug 2025

Keywords

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

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Wieske, V., Walther, M., Mohamed, M., Weickert, B., Andrzejewski, S., Dubourg, B., Andreini, D., Pontone, G., Alkadhi, H., Hausleiter, J., Garcia, M. J., Leschka, S., Meijboom, W. B., Zimmermann, E., Gerber, B., Schoepf, U. J., Shabestari, A. A., Nørgaard, B. L., Meijs, M. FL. (2025). Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT. JACC: Advances, 4(8), Article 102014. https://doi.org/10.1016/j.jacadv.2025.102014

@article{5854b17311eb45db8fc50194b0f51983,

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

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",

author = "Viktoria Wieske and Mario Walther and Mahmoud Mohamed and Benjamin Weickert and Simon Andrzejewski and Benjamin Dubourg and Daniele Andreini and Gianluca Pontone and Hatem Alkadhi and J{\"o}rg Hausleiter and Garcia, \{Mario J.\} and Sebastian Leschka and Meijboom, \{Willem B.\} and Elke Zimmermann and Bernhard Gerber and Schoepf, \{U. Joseph\} and Shabestari, \{Abbas A.\} and N{\o}rgaard, \{Bjarne L.\} and Meijs, \{Matthijs FL\} and Akira Sato and {\O}vrehus, \{Kristian A.\} and Diederichsen, \{Axel CP\} and Jenkins, \{Shona M.\} and Juhani Knuuti and Ashraf Hamdan and Halvorsen, \{Bj{\o}rn A.\} and \{Mendoza Rodriguez\}, Vladimir and Carlos Rochitte and Johannes Rixe and Wan, \{Yung Liang\} and Christoph Langer and Nuno Bettencourt and Eugenio Martuscelli and Said Ghostine and Buechel, \{Ronny R.\} and Konstantin Nikolaou and Hans Mickley and Lin Yang and Zhaqoi Zhang and Chen, \{Marcus Y.\} and Halon, \{David A.\} and Matthias Rief and Kai Sun and Hiroyuki Niinuma and Marcus, \{Roy P.\} and Simone Muraglia and R{\'e}da Jakamy and Chow, \{Benjamin JW\} and Kaufmann, \{Philipp A.\} and Herzog, \{Bernhard A.\}",

note = "Publisher Copyright: {\textcopyright} 2025 The Authors",

year = "2025",

month = aug,

doi = "10.1016/j.jacadv.2025.102014",

language = "English",

volume = "4",

journal = "JACC: Advances",

issn = "2772-963X",

publisher = "Elsevier",

number = "8",

}

Wieske, V, Walther, M, Mohamed, M, Weickert, B, Andrzejewski, S, Dubourg, B, Andreini, D, Pontone, G, Alkadhi, H, Hausleiter, J, Garcia, MJ, Leschka, S, Meijboom, WB, Zimmermann, E, Gerber, B, Schoepf, UJ, Shabestari, AA, Nørgaard, BL, Meijs, MFL, Sato, A, Øvrehus, KA, Diederichsen, ACP, Jenkins, SM, Knuuti, J, Hamdan, A, Halvorsen, BA, Mendoza Rodriguez, V, Rochitte, C, Rixe, J, Wan, YL, Langer, C, Bettencourt, N, Martuscelli, E, Ghostine, S, Buechel, RR, Nikolaou, K, Mickley, H, Yang, L, Zhang, Z, Chen, MY, Halon, DA, Rief, M, Sun, K, Niinuma, H, Marcus, RP, Muraglia, S, Jakamy, R, Chow, BJW, Kaufmann, PA, Herzog, BA 2025, 'Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT', JACC: Advances, vol. 4, no. 8, 102014. https://doi.org/10.1016/j.jacadv.2025.102014

TY - JOUR

T1 - Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT

AU - Wieske, Viktoria

AU - Walther, Mario

AU - Mohamed, Mahmoud

AU - Weickert, Benjamin

AU - Andrzejewski, Simon

AU - Dubourg, Benjamin

AU - Andreini, Daniele

AU - Pontone, Gianluca

AU - Alkadhi, Hatem

AU - Hausleiter, Jörg

AU - Garcia, Mario J.

AU - Leschka, Sebastian

AU - Meijboom, Willem B.

AU - Zimmermann, Elke

AU - Gerber, Bernhard

AU - Schoepf, U. Joseph

AU - Shabestari, Abbas A.

AU - Nørgaard, Bjarne L.

AU - Meijs, Matthijs FL

AU - Sato, Akira

AU - Øvrehus, Kristian A.

AU - Diederichsen, Axel CP

AU - Jenkins, Shona M.

AU - Knuuti, Juhani

AU - Hamdan, Ashraf

AU - Halvorsen, Bjørn A.

AU - Mendoza Rodriguez, Vladimir

AU - Rochitte, Carlos

AU - Rixe, Johannes

AU - Wan, Yung Liang

AU - Langer, Christoph

AU - Bettencourt, Nuno

AU - Martuscelli, Eugenio

AU - Ghostine, Said

AU - Buechel, Ronny R.

AU - Nikolaou, Konstantin

AU - Mickley, Hans

AU - Yang, Lin

AU - Zhang, Zhaqoi

AU - Chen, Marcus Y.

AU - Halon, David A.

AU - Rief, Matthias

AU - Sun, Kai

AU - Niinuma, Hiroyuki

AU - Marcus, Roy P.

AU - Muraglia, Simone

AU - Jakamy, Réda

AU - Chow, Benjamin JW

AU - Kaufmann, Philipp A.

AU - Herzog, Bernhard A.

PY - 2025/8

Y1 - 2025/8

N2 - 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.

AB - 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.

KW - computed tomography angiography

KW - coronary artery disease

KW - disease probability

KW - individual patient data meta-analysis

KW - stable chest pain

UR - https://www.scopus.com/pages/publications/105011680964

U2 - 10.1016/j.jacadv.2025.102014

DO - 10.1016/j.jacadv.2025.102014

M3 - Article

AN - SCOPUS:105011680964

SN - 2772-963X

VL - 4

JO - JACC: Advances

JF - JACC: Advances

IS - 8

M1 - 102014

ER -

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

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