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)

Autor: Marc Dewey, Geir R. Ulimoen, Matthew J. Budoff, David A. Halon, Jean-Claude Tardif, Shona M.M. Jenkins, Akira Sato, Bjarne L. Nørgaard, Konstantin Nikolaou, Thorsten R. C. Johnson, David Maintz, Andrea Romagnoli, Willem B. Meijboom, Benjamin Jw Chow, Sebastian Leschka, Elke Zimmermann, Bjørn Arild Halvorsen, Daniele Andreini, Vladimir Mendoza-Rodriguez, Harald Brodoefel, Lily Honoris, Abbas Arjmand Shabestari, Robert Roehle, Ashraf Hamdan, Michael Laule, Bernhard Gerber, Matthijs F.L. Meijs, Georg M. Schuetz, Hans Mickley, Mehraj Sheikh, Johannes Rixe, Uwe Joseph Schoepf, Arthur J.H.A. Scholte, Mario J. Garcia, Simone Muraglia, Kristian A. Øvrehus, Eugenio Martuscelli, Christoph Langer, Koen Nieman, Axel Cosmus Pyndt Diederichsen, Gianluca Pontone, Jörg Hausleiter, Roy P. Marcus, Peter Schlattmann, Stephan Achenbach, Hatem Alkadhi, Nuno Bettencourt
Přispěvatelé: UCL - SSS/IREC/CARD - Pôle de recherche cardiovasculaire, UCL - (SLuc) Service de pathologie cardiovasculaire, Radiology & Nuclear Medicine
Rok vydání: 2013
Předmět:
Male
medicine.medical_specialty
Pretest likelihood
Individual patient data meta-analysis
Tomography
X-Ray Computed/methods
Medicine (miscellaneous)
lcsh:Medicine
Settore MED/11 - Malattie dell'Apparato Cardiovascolare
Coronary Disease
CoMe-CCT
Coronary Angiography
Sensitivity and Specificity
Coronary artery disease
Sex Factors
Medizinische Fakultät
Predictive Value of Tests
Study protocol
medicine
Protocol
Humans
ddc:610
Coronary CT angiography
Tomography
Aged
Coronary Angiography/methods
Age Factors
Female
Tomography
X-Ray Computed
Positive and negative predictive value
business.industry
lcsh:R
Coronary Disease/diagnostic imaging
medicine.disease
X-Ray Computed
Coronary arteries
Collaborative meta-analysis on cardiac CT
IPD
Stenosis
medicine.anatomical_structure
Systematic review
Sensitivity and specificity
Meta-analysis
Predictive value of tests
Radiology
business
Artery
Zdroj: Systematic Reviews, Vol 2, Iss 1, p 13 (2013)
Schuetz, G M, Schlattmann, P, Achenbach, S, Budoff, M, Garcia, M J, Roehle, R, Pontone, G, Meijboom, W B, Andreini, D, Alkadhi, H, Honoris, L, Bettencourt, N, Hausleiter, J, Leschka, S, Gerber, B L, Meijs, M F, Shabestari, A A, Sato, A, Zimmermann, E, Schoepf, U J, Diederichsen, A C P, Halon, D A, Mendoza-Rodriguez, V, Hamdan, A, Nørgaard, B L, Brodoefel, H, Ovrehus, K A, Jenkins, S M, Halvorsen, B A, Rixe, J, Sheikh, M, Langer, C, Martuscelli, E, Romagnoli, A, Scholte, A J, Marcus, R P, Ulimoen, G R, Nieman, K, Mickley, H, Nikolaou, K, Tardif, J-C, Johnson, T R, Muraglia, S, Chow, B J, Maintz, D, Laule, M & Dewey, M 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) ', Systematic Reviews, vol. 2, pp. 13 . https://doi.org/10.1186/2046-4053-2-13
Schuetz, Georg M; Schlattmann, Peter; Achenbach, Stephan; Budoff, Matthew; Garcia, Mario J; Roehle, Robert; 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). Systematic Reviews, 2(1), 13. doi: http://dx.doi.org/10.1186/2046-4053-2-13. Retrieved from: http://www.escholarship.org/uc/item/6vh7h6xc
Schuetz, G M, Schlattmann, P, Achenbach, S, Budoff, M, Garcia, M J, Roehle, R, Pontone, G, Meijboom, W B, Andreini, D, Alkadhi, H, Honoris, L, Bettencourt, N, Hausleiter, J, Leschka, S, Gerber, B L, Meijs, M F, Shabestari, A A, Sato, A, Zimmermann, E, Schoepf, U J, Diederichsen, A C P, Halon, D A, Mendoza-Rodriguez, V, Hamdan, A, Nørgaard, B L, Brodoefel, H, Ovrehus, K A, Jenkins, S M, Halvorsen, B A, Rixe, J, Sheikh, M, Langer, C, Martuscelli, E, Romagnoli, A, Scholte, A J, Marcus, R P, Ulimoen, G R, Nieman, K, Mickley, H, Nikolaou, K, Tardif, J-C, Johnson, T R, Muraglia, S, Chow, B J, Maintz, D, Laule, M & Dewey, M 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) ', Systematic Reviews, vol. 2, no. 1, 13, pp. 13 . https://doi.org/10.1186/2046-4053-2-13
Systematic Reviews
Systematic reviews, Vol. 2, no. 1, p. 13 (2013)
Systematic Reviews, 2:13. BioMed Central Ltd.
ISSN: 2046-4053
DOI: 10.1186/2046-4053-2-13
Popis: Background 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). Methods/Design 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. Discussion 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.
Databáze: OpenAIRE
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