Professor Julian Higgins explains why he believes the systematic review and meta-analysis methods described in many highly cited papers are routinely misunderstood or misused. Julian Higgins is Professor of Evidence Synthesis at the Bristol Evidence Synthesis, Appraisal and Modelling (BEAM) Centre at the University of Bristol. His research has focussed on the methodology of systematic review and meta-analysis and he has been senior editor of the Cochrane Handbook for Systematic Reviews of Interventions since 2003. He is an NIHR Senior Investigator and currently co-directs the NIHR Bristol Evidence Synthesis Group.
Systematic reviews and meta-analyses have become influential and popular. Papers describing aspects of the systematic review and meta-analysis toolkit have become some of the most highly cited papers. I will review those that appear at the top of the most-cited list and explain why I believe the methods described are routinely misunderstood or misused. These include a test for asymmetry in a funnel plot, the I-squared statistic for measuring inconsistency across studies, the random-effects meta-analysis model and the PRIMSA reporting guideline.
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Professor Julian Higgins explains why he believes the systematic review and meta-analysis methods described in many highly cited papers are routinely misunderstood or misused. Julian Higgins is Professor of Evidence Synthesis at the Bristol Evidence Synthesis, Appraisal and Modelling (BEAM) Centre at the University of Bristol. His research has focussed on the methodology of systematic review and meta-analysis and he has been senior editor of the Cochrane Handbook for Systematic Reviews of Interventions since 2003. He is an NIHR Senior Investigator and currently co-directs the NIHR Bristol Evidence Synthesis Group.
Systematic reviews and meta-analyses have become influential and popular. Papers describing aspects of the systematic review and meta-analysis toolkit have become some of the most highly cited papers. I will review those that appear at the top of the most-cited list and explain why I believe the methods described are routinely misunderstood or misused. These include a test for asymmetry in a funnel plot, the I-squared statistic for measuring inconsistency across studies, the random-effects meta-analysis model and the PRIMSA reporting guideline.
How should we teach evidence-based medicine in the 21st century?
Evidence-Based Health Care
21 minutes
3 years ago
How should we teach evidence-based medicine in the 21st century?
Dr Gordon Guyatt provides a guest talk on how we should teach evidence-based medicine in the 21st century This free guest lecture is part of the Teaching Evidence-Based Practice module, part of the Oxford University Evidence-Based Health Care (EBHC) programme.
About the speaker: Dr Gordon Guyatt is a Distinguished Professor in the Department of Clinical Epidemiology and Biostatistics, McMaster University and one of the founders of Evidence-Based Medicine. He has played a key role in over 30 major clinical studies (including both large-scale observational and randomized trials) and has extensive expertise in study methodology. As co-founder and co-chair of the GRADE working group, he has been intimately involved in the development and evolution of the GRADE approach.
Questions?
Please contact the Evidence-Based Health Care (EBHC) team by emailing: cpdhealth@conted.ox.ac.uk
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Evidence-Based Health Care
Professor Julian Higgins explains why he believes the systematic review and meta-analysis methods described in many highly cited papers are routinely misunderstood or misused. Julian Higgins is Professor of Evidence Synthesis at the Bristol Evidence Synthesis, Appraisal and Modelling (BEAM) Centre at the University of Bristol. His research has focussed on the methodology of systematic review and meta-analysis and he has been senior editor of the Cochrane Handbook for Systematic Reviews of Interventions since 2003. He is an NIHR Senior Investigator and currently co-directs the NIHR Bristol Evidence Synthesis Group.
Systematic reviews and meta-analyses have become influential and popular. Papers describing aspects of the systematic review and meta-analysis toolkit have become some of the most highly cited papers. I will review those that appear at the top of the most-cited list and explain why I believe the methods described are routinely misunderstood or misused. These include a test for asymmetry in a funnel plot, the I-squared statistic for measuring inconsistency across studies, the random-effects meta-analysis model and the PRIMSA reporting guideline.
