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)

Publication

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)

Journal Paper/Review - Feb 15, 2013

Dewey Marc, Romagnoli Andrea, Martuscelli Eugenio, Langer Christoph, Sheikh Mehraj, Rixe Johannes, Halvorsen Bjørn A, Jenkins Shona Mm, Ovrehus Kristian A, Brodoefel Harald, Scholte Arthur Jha, Marcus Roy P, Ulimoen Geir R, Laule Michael, Maintz David, Chow Benjamin Jw, Muraglia Simone, Johnson Thorsten Rc, Tardif Jean-Claude, Nikolaou Konstantin, Mickley Hans, Nieman Koen, Nørgaard Bjarne L, Hamdan Ashraf, Mendoza-Rodriguez Vladimir, Alkadhi Hatem, Andreini Daniele, Meijboom Willem Bob, Pontone Gianluca, Roehle Robert, Garcia Mario J, Budoff Matthew, Achenbach Stephan, Schlattmann Peter, Honoris Lily, Bettencourt Nuno, Hausleiter Jörg, Halon David A, Diederichsen Axel, Schoepf Uwe J, Zimmermann Elke, Sato Akira, Shabestari Abbas Arjmand, Meijs Matthijs Fl, Gerber Bernhard L, Leschka Sebastian, Schuetz Georg M

Citation

Dewey M, Romagnoli A, Martuscelli E, Langer C, Sheikh M, Rixe J, Halvorsen B, Jenkins S, Ovrehus K, Brodoefel H, Scholte A, Marcus R, Ulimoen G, Laule M, Maintz D, Chow B, Muraglia S, Johnson T, Tardif J, Nikolaou K, Mickley H, Nieman K, Nørgaard B, Hamdan A, Mendoza-Rodriguez V, Alkadhi H, Andreini D, Meijboom W, Pontone G, Roehle R, Garcia M, Budoff M, Achenbach S, Schlattmann P, Honoris L, Bettencourt N, Hausleiter J, Halon D, Diederichsen A, Schoepf U, Zimmermann E, Sato A, Shabestari A, Meijs M, Gerber B, Leschka S, Schuetz G. 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). Syst Rev 2013; 2:13.

Type

Journal Paper/Review (English)

Journal

Syst Rev 2013; 2

Publication Date

Feb 15, 2013

Issn Electronic

2046-4053

Brief description/objective

UNLABELLED

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.