Intended for healthcare professionals

CCBYNC Open access
Research

Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts

BMJ 2012; 344 doi: https://doi.org/10.1136/bmj.e3485 (Published 12 June 2012) Cite this as: BMJ 2012;344:e3485
  1. Tessa S S Genders, clinical epidemiologist12,
  2. Ewout W Steyerberg, professor of medical decision making3,
  3. M G Myriam Hunink, professor of radiology and clinical epidemiology (Erasmus) and adjunct professor of health decision sciences (Harvard)1227,
  4. Koen Nieman, cardiologist, medical coordinator of ICCU, and assistant professor24,
  5. Tjebbe W Galema, cardiologist4,
  6. Nico R Mollet, staff radiologist24,
  7. Pim J de Feyter, professor of non-invasive cardiac imaging24,
  8. Gabriel P Krestin, professor and chairman of department of radiology2,
  9. Hatem Alkadhi, senior radiologist5,
  10. Sebastian Leschka, associate professor, senior staff radiologist, section head of computed tomography, and section head of emergency radiology512,
  11. Lotus Desbiolles, staff cardiologist512,
  12. Matthijs F L Meijs, resident in cardiology67,
  13. Maarten J Cramer, associate professor of cardiology6,
  14. Juhani Knuuti, professor, consultant, and director of centre8,
  15. Sami Kajander, consultant radiologist8,
  16. Jan Bogaert, adjunct chair of department of radiology9,
  17. Kaatje Goetschalckx, cardiologist9,
  18. Filippo Cademartiri, associate professor and head of cardiovascular imaging unit21011,
  19. Erica Maffei, staff radiologist1011,
  20. Chiara Martini, staff radiologist1011,
  21. Sara Seitun, radiologist10,
  22. Annachiara Aldrovandi, staff cardiologist10,
  23. Simon Wildermuth, professor of radiology and chairman of institute of radiology12,
  24. Björn Stinn, staff radiologist12,
  25. Jürgen Fornaro, staff radiologist12,
  26. Gudrun Feuchtner, associate professor of radiology13,
  27. Tobias De Zordo, resident in radiology13,
  28. Thomas Auer, resident in radiology13,
  29. Fabian Plank, research fellow13,
  30. Guy Friedrich, professor of medicine14,
  31. Francesca Pugliese, senior clinical lecturer and consultant15,
  32. Steffen E Petersen, reader in advanced cardiovascular imaging and honorary consultant cardiologist15,
  33. L Ceri Davies, reader in advanced cardiovascular imaging and honorary consultant cardiologist15,
  34. U Joseph Schoepf, professor of radiology, medicine, and pediatrics and director of cardiovascular imaging16,
  35. Garrett W Rowe, program coordinator16,
  36. Carlos A G van Mieghem, staff cardiologist17,
  37. Luc van Driessche, associate director of cardiology and consultant in interventional cardiology18,
  38. Valentin Sinitsyn, head of radiology department19,
  39. Deepa Gopalan, consultant cardiovascular radiologist20,
  40. Konstantin Nikolaou, professor of radiology and vice chair of department of clinical radiology21,
  41. Fabian Bamberg, fellow in radiology21,
  42. Ricardo C Cury, chairman of department of radiology and director of cardiac imaging22,
  43. Juan Battle, radiologist22,
  44. Pál Maurovich-Horvat, chairman of department of radiology and director of cardiac imaging23,
  45. Andrea Bartykowszki, resident in cardiology23,
  46. Bela Merkely, professor of cardiology and director of heart centre23,
  47. Dávid Becker, associate professor and deputy director heart centre23,
  48. Martin Hadamitzky, director of cardiac magnetic resonance imaging24,
  49. Jörg Hausleiter, assistant medical director24,
  50. Marc Dewey, chief consultant radiologist25,
  51. Elke Zimmermann, specialist in radiology25,
  52. Michael Laule, senior physician and deputy director of cardiac catheterisation laboratory26
  1. 1Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, Netherlands
  2. 2Department of Radiology, Erasmus University Medical Centre
  3. 3Department of Public Health, Erasmus University Medical Centre
  4. 4Department of Cardiology, Erasmus University Medical Centre
  5. 5Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
  6. 6Department of Cardiology, University Medical Centre Utrecht, Utrecht, Netherlands
  7. 7Department of Radiology, University Medical Centre Utrecht
  8. 8Turku PET Centre, Turku University Hospital, Turku, Finland
  9. 9Department of Cardiovascular Diseases, University Hospital Leuven, Leuven, Belgium
  10. 10Department of Radiology and Cardiology, Azienda Ospedaliero-Universitaria, Parma, Italy
  11. 11Department of Radiology, Giovanni XXIII Clinic, Monastier, Treviso, Italy
  12. 12Institute of Radiology, Kantonsspital St Gallen, St Gallen, Switzerland
  13. 13Department of Radiology, Innsbruck Medical University, Innsbruck, Austria
  14. 14Department of Cardiology, Innsbruck Medical University
  15. 15Centre for Advanced Cardiovascular Imaging, Barts and The London NIHR Cardiovascular Biomedical Research Unit, Barts and the London School of Medicine and Dentistry, Barts and the London NHS Trust, London, UK
  16. 16Department of Radiology, Medical University of South Carolina, Charleston, SC, USA
  17. 17Department of Cardiology, Onze-Lieve-Vrouwziekenhuis Hospital Aalst, Aalst, Belgium
  18. 18Department of Cardiology, St Blasius Hospital Dendermonde, Belgium
  19. 19Department of Radiology, Federal Centre of Medicine and Rehabilitation, Moscow, Russia
  20. 20Department of Radiology, Papworth Hospital NHS Trust, Cambridge, UK
  21. 21Department of Clinical Radiology, University Hospitals Munich, Munich, Germany
  22. 22Department of Radiology, Baptist Hospital of Miami and Baptist Cardiac and Vascular Institute, Miami, FL, USA
  23. 23Heart Centre, Semmelweis University, Budapest, Hungary
  24. 24Department of Cardiology, German Heart Centre, Munich, Germany
  25. 25Department of Radiology, Charité, Medical School, Humboldt University, Berlin, Germany
  26. 26Department of Cardiology, Charité, Medical School
  27. 27Department of Health Policy and Management, Harvard School of Public Health, Harvard University, Boston, MA, USA
  1. Correspondence to: M G M Hunink, Departments of Epidemiology and Radiology, Erasmus University Medical Centre, PO Box 2040, 3000 CA Rotterdam, Netherlands m.hunink{at}erasmusmc.nl
  • Accepted 14 April 2012

Abstract

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations.

Design Retrospective pooled analysis of individual patient data.

Setting 18 hospitals in Europe and the United States.

Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively).

Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined.

Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory.

Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates.

Footnotes

  • We thank C Greg Hagerty and Michael W Kattan from the Cleveland Clinic Lerner Research Institute (Cleveland, OH, USA) for developing, customising, and improving the Cleveland clinic risk calculator constructor (http://rcc.simpal.com/).

  • Funding: This research was supported by a healthcare efficiency grant from the Erasmus University Medical Centre. The authors’ work was independent of the funding sources. The funding organisations had no involvement in design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript; and in the decision to publish the manuscript.

  • Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: support from the Erasmus University Medical Centre; FP, SEP, and LCD’s work contributes to the translational research portfolio of Barts and the London Cardiovascular Biomedical Research Unit, which is supported and funded by the National Institute for Health Research; UJS is a consultant for Bayer and Siemens and provides research support to Bayer, Bracco, General Electric, and Siemens; MD holds research grants (European Regional Development Fund, German Heart Foundation/German Foundation of Heart Research, GE Healthcare (Amersham), Bracco, Guerbet, and Toshiba Medical Systems), receives speaker fees (Toshiba Medical Systems, Guerbet, and Bayer-Schering), runs cardiac CT workshops at Charité (www.ct-kurs.de), has written the book Coronary CT Angiography (Springer, 2008), and is involved in institutional research collaborations (Siemens Medical Solutions, Philips Medical Systems, and Toshiba Medical Systems); FC is a consultant for Servier, received speaker fees (Bracco Imaging), and holds a research grant with HE Healthcare; EM is a consultant for Servier and holds a research grants with HE Healthcare; FB has received speakers fees from Siemens Healthcare; all other authors have no financial relationships with any organisations that might have an interest in the submitted work in the previous 3 years and no other relationships or activities that could appear to have influenced the submitted work.

  • Ethical approval: Not required.

  • Contributors: MGMH, EWS, and TSSG participated in the study concept and design, analysis and interpretation of data, and drafting of the manuscript. All authors apart from MGMH, EWS, and TSSG were involved in the acquisition of data. All authors contributed to the critical revision of the manuscript for important intellectual content and final approval of the published version. MGMH, the principal investigator and guarantor, had full access to all the data in the study and takes responsibility for the integrity of the data and accuracy of the data analysis, and was responsible for manuscript preparation and decision to submit the manuscript for publication.

  • Data sharing: No additional data available.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

View Full Text