Skip to main content
Log in

Conducting and interpreting high-quality systematic reviews and meta-analyses

  • Review Article
  • Published:
Journal of Nuclear Cardiology Aims and scope

Abstract

Systematic reviews and meta-analyses are powerful tools for summarizing existing literature and combining evidence from multiple studies. These methods employ complex searches, statistical techniques, and presentation techniques with which the clinical audience may not be very familiar. This review article aims to familiarize the clinical audience with the various techniques employed to conduct a high-quality systematic review and meta-analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1

The y axis depicts the number of results in response to the search query ‘meta-analysis’ on PubMed

Figure 2

Adapted with permissions from: J Am Heart Assoc 2015 Dec 14;4(12)

Figure 3

Adapted with permissions from: J Am Heart Assoc 2015 Dec 14;4(12)

Figure 4
Figure 5

Adapted with permissions from: J Am Heart Assoc 2015 Dec 14;4(12)

Figure 6

In the first study group, entitled ‘Low Heterogeneity’, the reader can see that the studies are closely clustered in a vertical fashion. The second study set, entitled ‘High Heterogeneity’, has a wide dispersion of study effect size estimates, indicating a greater degree of heterogeneity. The blue circles highlight the I 2 figures and their statistical significance

Figure 7

The authors performed meta-regression with Logit event rate as the dependent variable. A demonstrates that there is an increase in Logit event rate as the proportion of the independent variable increases in individual studies increases. B there is no relationship between Logit event rate and the proportion of the independent variable in individual studies

Figure 8

Adapted with permissions from: J Am Heart Assoc 2015 Dec 14;4(12)

Figure 9

Similar content being viewed by others

Abbreviations

MA:

Meta-analysis (analyses)

MACE:

Major adverse cardiac events

NMA:

Network meta-analysis (analyses)

SR:

Systematic review(s)

References

  1. Meta-analysis under scrutiny. Lancet 1997;350:675.

  2. Lip GY, Lane DA. Stroke prevention in atrial fibrillation: A systematic review. JAMA 2015;313:1950-62.

    Article  PubMed  Google Scholar 

  3. O’Rourke K. An historical perspective on meta-analysis: Dealing quantitatively with varying study results. J R Soc Med 2007;100:579-82.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Haidich AB. Meta-analysis in medical research. Hippokratia 2010;14:29-37.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Egger M, Smith GD. Meta-analysis: Potentials and promise. BMJ 1997;315:1371-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Patsopoulos NA, Analatos AA, Ioannidis JA. Relative citation impact of various study designs in the health sciences. JAMA 2005;293:2362-6.

    Article  CAS  PubMed  Google Scholar 

  7. Jacobs AK, Anderson JL, Halperin JL. The Evolution and Future of ACC/AHA Clinical Practice Guidelines: A 30-Year Journey A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014;64:1373-84.

    Article  PubMed  Google Scholar 

  8. Bajaj NS, Kalra R, Aggarwal H, Ather S, Gaba S, Arora G, et al. Comparison of approaches to revascularization in patients with multivessel coronary artery disease presenting with ST-segment elevation myocardial infarction: Meta-analyses of randomized control trials. J Am Heart Assoc. 2015;4:e002540.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Olivo SA, Macedo LG, Gadotti IC, Fuentes J, Stanton T, Magee DJ. Scales to assess the quality of randomized controlled trials: A systematic review. Phys Ther 2008;88:156-75.

    Article  PubMed  Google Scholar 

  10. Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJM, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: Is blinding necessary? Control Clin Trials 1996;17:1-12.

    Article  CAS  PubMed  Google Scholar 

  11. Deeks JJ, Dinnes J, D’Amico R, Sowden AJ, Sakarovitch C, Song F, et al. Evaluating non-randomised intervention studies. Health Technol Assess 2003;7:1-173.

    Article  Google Scholar 

  12. Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses [cited 24 March 2016]. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.

  13. Berlin JA, Laird NM, Sacks HS, Chalmers TC. A comparison of statistical methods for combining event rates from clinical trials. Stat Med 1989;8:141-51.

    Article  CAS  PubMed  Google Scholar 

  14. Borenstein M, Hedges L, Rothstein H. Meta-analysis fixed effects vs. random effects [cited 25 March 2016]. Available from: https://www.meta-analysis.com/downloads/Meta-analysis%20fixed%20effect%20vs%20random%20effects.pdf.

  15. Cochrane Handbook for Systematic Reviews of Interventions: The Cochrane Collaboration; 2011 [cited 23 March 2016], Version 5.1.0. Available from: www.cochrane-handbook.org.

  16. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629-34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mills EJ, Thorlund K, Ioannidis JPA. Demystifying trial networks and network meta-analysis. BMJ 2013;346:f3914.

    Article  Google Scholar 

  19. Davey Smith G, Egger M, Phillips AN. Meta-analysis. Beyond the grand mean? BMJ 1997;315:1610-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 2004;23:3105-24.

    Article  CAS  PubMed  Google Scholar 

  21. IBM. SPSS Software 2016 [cited 26 March 2016]. Available from: http://www-01.ibm.com/software/analytics/spss/.

  22. Comprehensive Meta-Analysis (CMA) 2016 [cited 26 March 2016]. Available from: https://www.meta-analysis.com/.

  23. Cochrane Collaboration. RevMan Cochrane Informatics and Knowledge Management Department: Cochrane Informatics and Knowledge Management Department; 2016 [cited 26 March 2016]. Available from: http://tech.cochrane.org/revman.

  24. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: Explanation and elaboration. BMJ 2009;339:b2700.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hutton B, Salanti G, Caldwell DM, Chaimani A, Schmid CH, Cameron C, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: Checklist and explanations. Ann Intern Med 2015;162:777-84.

    Article  PubMed  Google Scholar 

  26. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: A proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283:2008-12.

    Article  CAS  PubMed  Google Scholar 

  27. Flather MD, Farkouh ME, Pogue JM, Yusuf S. Strengths and limitations of meta-analysis: Larger studies may be more reliable. Control Clin Trials 1997;18:568-79.

    Article  CAS  PubMed  Google Scholar 

  28. Greco T, Zangrillo A, Biondi-Zoccai G, Landoni G. Meta-analysis: Pitfalls and hints. Heart Lung Vessels 2013;5:219-25.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Egger M, Smith GD. Bias in location and selection of studies. BMJ 1998;316:61-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629-34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Disclosures

None of the authors had any conflicts of interests or financial disclosures to declare.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Navkaranbir S. Bajaj MD.

Additional information

The authors of this article have provided a PowerPoint file, available for download at SpringerLink, which summarises the contents of the paper and is free for re-use at meetings and presentations. Search for the article DOI on SpringerLink.com.

Funding

None.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PPTX 282 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kalra, R., Arora, P., Morgan, C. et al. Conducting and interpreting high-quality systematic reviews and meta-analyses. J. Nucl. Cardiol. 24, 471–481 (2017). https://doi.org/10.1007/s12350-016-0598-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-016-0598-9

Keywords

Navigation