title: 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).
abstract: 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
  The analysis will include individual patient data from published and unpublished prospective diagnostic accuracy studies comparing coronary computed tomography angiography with conventional coronary angiography.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.
  
  
  CONCLUSIONS
  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.
authors: Department of Radiology, Charité - Universitätsmedizin Berlin Campus Mitte, Humboldt-Universität zu Berlin, Freie Universität Berlin, Charitéplatz 1, Berlin 10117, Germany.
authors: Georg M
authors: GM
authors: Schuetz
authors: Peter
authors: P
authors: Schlattmann
authors: Stephan
authors: S
authors: Achenbach
authors: Matthew
authors: M
authors: Budoff
authors: Mario J
authors: MJ
authors: Garcia
authors: Robert
authors: R
authors: Roehle
authors: Gianluca
authors: G
authors: Pontone
authors: Willem Bob
authors: WB
authors: Meijboom
authors: Daniele
authors: D
authors: Andreini
authors: Hatem
authors: H
authors: Alkadhi
authors: Lily
authors: L
authors: Honoris
authors: Nuno
authors: N
authors: Bettencourt
authors: Jörg
authors: J
authors: Hausleiter
authors: Sebastian
authors: S
authors: Leschka
authors: Bernhard L
authors: BL
authors: Gerber
authors: Matthijs Fl
authors: MF
authors: Meijs
authors: Abbas Arjmand
authors: AA
authors: Shabestari
authors: Akira
authors: A
authors: Sato
authors: Elke
authors: E
authors: Zimmermann
authors: Uwe J
authors: UJ
authors: Schoepf
authors: Axel
authors: A
authors: Diederichsen
authors: David A
authors: DA
authors: Halon
authors: Vladimir
authors: V
authors: Mendoza-Rodriguez
authors: Ashraf
authors: A
authors: Hamdan
authors: Bjarne L
authors: BL
authors: Nørgaard
authors: Harald
authors: H
authors: Brodoefel
authors: Kristian A
authors: KA
authors: Ovrehus
authors: Shona Mm
authors: SM
authors: Jenkins
authors: Bjørn A
authors: BA
authors: Halvorsen
authors: Johannes
authors: J
authors: Rixe
authors: Mehraj
authors: M
authors: Sheikh
authors: Christoph
authors: C
authors: Langer
authors: Eugenio
authors: E
authors: Martuscelli
authors: Andrea
authors: A
authors: Romagnoli
authors: Arthur Jha
authors: AJ
authors: Scholte
authors: Roy P
authors: RP
authors: Marcus
authors: Geir R
authors: GR
authors: Ulimoen
authors: Koen
authors: K
authors: Nieman
authors: Hans
authors: H
authors: Mickley
authors: Konstantin
authors: K
authors: Nikolaou
authors: Jean-Claude
authors: JC
authors: Tardif
authors: Thorsten Rc
authors: TR
authors: Johnson
authors: Simone
authors: S
authors: Muraglia
authors: Benjamin Jw
authors: BJ
authors: Chow
authors: David
authors: D
authors: Maintz
authors: Michael
authors: M
authors: Laule
authors: Marc
authors: M
authors: Dewey
mesh_terms: D000367:Age Factors; D000368:Aged; D017023:Coronary Angiography / Q000379:methods* / Q000592:standards; D003327:Coronary Disease / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008297:Male; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D012737:Sex Factors; D014057:Tomography, X-Ray Computed / Q000379:methods* / Q000592:standards; D015201:Meta-Analysis as Topic