TY - JOUR
T1 - Individual patient data meta-analysis for the clinical assessment of coronary computed tomography angiography
T2 - protocol of the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT).
AU - Schuetz, Georg M.
AU - Schlattmann, Peter
AU - Achenbach, Stephan
AU - Budoff, Matthew
AU - Garcia, Mario J.
AU - Roehle, Robert
AU - Pontone, Gianluca
AU - Meijboom, Willem Bob
AU - Andreini, Daniele
AU - Alkadhi, Hatem
AU - Honoris, Lily
AU - Bettencourt, Nuno
AU - Hausleiter, Jörg
AU - Leschka, Sebastian
AU - Gerber, Bernhard L.
AU - Meijs, Matthijs Fl
AU - Shabestari, Abbas Arjmand
AU - Sato, Akira
AU - Zimmermann, Elke
AU - Schoepf, Uwe J.
AU - Diederichsen, Axel
AU - Halon, David A.
AU - Mendoza-Rodriguez, Vladimir
AU - Hamdan, Ashraf
AU - Nørgaard, Bjarne L.
AU - Brodoefel, Harald
AU - Ovrehus, Kristian A.
AU - Jenkins, Shona Mm
AU - Halvorsen, Bjørn A.
AU - Rixe, Johannes
AU - Sheikh, Mehraj
AU - Langer, Christoph
AU - Martuscelli, Eugenio
AU - Romagnoli, Andrea
AU - Scholte, Arthur Jha
AU - Marcus, Roy P.
AU - Ulimoen, Geir R.
AU - Nieman, Koen
AU - Mickley, Hans
AU - Nikolaou, Konstantin
AU - Tardif, Jean Claude
AU - Johnson, Thorsten Rc
AU - Muraglia, Simone
AU - Chow, Benjamin Jw
AU - Maintz, David
AU - Laule, Michael
AU - Dewey, Marc
N1 - Funding Information:
This collaborative meta-analysis based on individual patient data is funded by a grant of the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung – BMBF) (FKZ: 01KG1110) for meta-analyses as part of the joint program ‘clinical trials’ of the BMBF and the DFG. We thank all collaborating authors who have already provided patient data for this IPD meta-analysis project at the time of writing.
Funding Information:
PS and MD are supported by a grant of the German Federal Ministry of Education and Research (BMBF) for meta-analyses as part of the joint program "clinical trials" of the BMBF and the German Research Foundation (DFG). PS is also supported by another grant of the DFG (Schl 3–1) and has received lecture fees from Bayer-Schering. MD has received grant support from Heisenberg Program of the DFG for a professorship (DE 1361/14-1), European Regional Development Fund (20072013 2/05, 20072013 2/48), German Heart Foundation/German Foundation of Heart Research (F/23/08, F/27/10), Joint program from the DFG and the BMBF for meta-analyses (01KG1013, 01KG1110), GE Healthcare, Bracco, Guerbet, and Toshiba Medical Systems and 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 multi-center 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 (http://www.ct-kurs.de). Institutional master research agreements exist between Charité and Siemens Medical Solutions, Philips Medical Systems, and Toshiba Medical Systems. GMS is a physician working as a research assistant in MD's working group. His salary is financed by a grant from the BMBF for meta-analyses granted to MD. RR is a research assistant in MD's working group; his salary is also paid by a grant from the BMBF for meta-analyses granted to MD. SA is Speaker Honoraria and receives grant support from Siemens AG; he is a consultant for Servier and Guerbet. MB receives grant support from GE. GP has received a grant from GE Healthcare as speaker's bureau. JH received research grants from Siemens Medical Solutions. UJS is a consultant for and receives research support from Bayer, Bracco, GE, Medrad, and Siemens. AD and HM have received grants from Region Syddanmark (grant number 08–17862 and 09–13526). DAH reports institutional research and development agreements with Philips Medical Systems. KAØ has received grant support from Vejle Hospital Research Foundation and a PhD scholarship from the Faculty of Health Sciences at Aarhus University. GRU has received lecture fees from Siemens Medical Solutions and Philips Medical Systems, but has no other conflicts of interest. KN is supported by an Erasmus MC Fellowship, receives unrestricted research support from Siemens Medical Solution and Bayer Scheering, and lecture fees from Siemens Medical Solutions, Bayer Scheering and Abbott Vascular. KN receives royalties for lectures including service on speakers' bureaus from Bayer Healthcare and Siemens Healthcare. TRCJ is supported by research grants and receives lecture fees from Siemens Healthcare and Bayer Healthcare. BJWC receives research support from GE Healthcare and educational support from TeraRecon. MJG, WBM, DA, HA, LH, SL, BLG, AAS, AS, EZ, VMR, AH, BLN, HB, SMMJ, BAH, JR, MS, CL, EM, AR, AJHAS, RPM, JCT, SM, DM and ML have no competing interests to declare. NB certifies that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript. MFLM declares that there are no conflicts of interest for himself (or for any other Utrecht authors (Prokop, Cramer, Doevendans and De Vos) in the study described in Meijboom, Meijs, JACC 2008).
PY - 2013
Y1 - 2013
N2 - Coronary computed tomography angiography has become the foremost noninvasive imaging modality of the coronary arteries and is used as an alternative to the reference standard, conventional coronary angiography, for direct visualization and detection of coronary artery stenoses in patients with suspected coronary artery disease. Nevertheless, there is considerable debate regarding the optimal target population to maximize clinical performance and patient benefit. The most obvious indication for noninvasive coronary computed tomography angiography in patients with suspected coronary artery disease would be to reliably exclude significant stenosis and, thus, avoid unnecessary invasive conventional coronary angiography. To do this, a test should have, at clinically appropriate pretest likelihoods, minimal false-negative outcomes resulting in a high negative predictive value. However, little is known about the influence of patient characteristics on the clinical predictive values of coronary computed tomography angiography. Previous regular systematic reviews and meta-analyses had to rely on limited summary patient cohort data offered by primary studies. Performing an individual patient data meta-analysis will enable a much more detailed and powerful analysis and thus increase representativeness and generalizability of the results. The individual patient data meta-analysis is registered with the PROSPERO database (CoMe-CCT, CRD42012002780). The analysis will include individual patient data from published and unpublished prospective diagnostic accuracy studies comparing coronary computed tomography angiography with conventional coronary angiography. These studies will be identified performing a systematic search in several electronic databases. Corresponding authors will be contacted and asked to provide obligatory and additional data. Risk factors, previous test results and symptoms of individual patients will be used to estimate the pretest likelihood of coronary artery disease. A bivariate random-effects model will be used to calculate pooled mean negative and positive predictive values as well as sensitivity and specificity. The primary outcome of interest will be positive and negative predictive values of coronary computed tomography angiography for the presence of coronary artery disease as a function of pretest likelihood of coronary artery disease, analyzed by meta-regression. As a secondary endpoint, factors that may influence the diagnostic performance and clinical value of computed tomography, such as heart rate and body mass index of patients, number of detector rows, and administration of beta blockade and nitroglycerin, will be investigated by integrating them as further covariates into the bivariate random-effects model. This collaborative individual patient data meta-analysis should provide answers to the pivotal question of which patients benefit most from noninvasive coronary computed tomography angiography and thus help to adequately select the right patients for this test.
AB - Coronary computed tomography angiography has become the foremost noninvasive imaging modality of the coronary arteries and is used as an alternative to the reference standard, conventional coronary angiography, for direct visualization and detection of coronary artery stenoses in patients with suspected coronary artery disease. Nevertheless, there is considerable debate regarding the optimal target population to maximize clinical performance and patient benefit. The most obvious indication for noninvasive coronary computed tomography angiography in patients with suspected coronary artery disease would be to reliably exclude significant stenosis and, thus, avoid unnecessary invasive conventional coronary angiography. To do this, a test should have, at clinically appropriate pretest likelihoods, minimal false-negative outcomes resulting in a high negative predictive value. However, little is known about the influence of patient characteristics on the clinical predictive values of coronary computed tomography angiography. Previous regular systematic reviews and meta-analyses had to rely on limited summary patient cohort data offered by primary studies. Performing an individual patient data meta-analysis will enable a much more detailed and powerful analysis and thus increase representativeness and generalizability of the results. The individual patient data meta-analysis is registered with the PROSPERO database (CoMe-CCT, CRD42012002780). The analysis will include individual patient data from published and unpublished prospective diagnostic accuracy studies comparing coronary computed tomography angiography with conventional coronary angiography. These studies will be identified performing a systematic search in several electronic databases. Corresponding authors will be contacted and asked to provide obligatory and additional data. Risk factors, previous test results and symptoms of individual patients will be used to estimate the pretest likelihood of coronary artery disease. A bivariate random-effects model will be used to calculate pooled mean negative and positive predictive values as well as sensitivity and specificity. The primary outcome of interest will be positive and negative predictive values of coronary computed tomography angiography for the presence of coronary artery disease as a function of pretest likelihood of coronary artery disease, analyzed by meta-regression. As a secondary endpoint, factors that may influence the diagnostic performance and clinical value of computed tomography, such as heart rate and body mass index of patients, number of detector rows, and administration of beta blockade and nitroglycerin, will be investigated by integrating them as further covariates into the bivariate random-effects model. This collaborative individual patient data meta-analysis should provide answers to the pivotal question of which patients benefit most from noninvasive coronary computed tomography angiography and thus help to adequately select the right patients for this test.
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U2 - 10.1186/2046-4053-2-13
DO - 10.1186/2046-4053-2-13
M3 - Article
C2 - 23414575
AN - SCOPUS:84878040162
VL - 2
SP - 13
JO - Journal of Trace Elements in Medicine and Biology
JF - Journal of Trace Elements in Medicine and Biology
SN - 0946-672X
M1 - 13
ER -