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Cited by 730Meta-analysis and systematic reviewsDelphi Technique in ResearchClinical practice guidelines implementation

The DOI matches its Crossref record; 60 of the 62 references it cites were found in a registry or an index.

Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program

Fu, Rongwei, Gartlehner, Gerald, Grant, Mark, Shamliyan, Tatyana, Sedrakyan, Art, Wilt, Timothy J., Griffith, Lauren, Oremus, Mark, Raina, Parminder, Ismaila, Afisi, Santaguida, Pasqualina, Lau, Joseph, Trikalinos, Thomas A.·2011·Journal of Clinical Epidemiology
DOI 10.1016/j.jclinepi.2010.08.010
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Abstract

Objective This article is to establish recommendations for conducting quantitative synthesis, or meta-analysis, using study-level data in comparative effectiveness reviews (CERs) for the Evidence-based Practice Center (EPC) program of the Agency for Healthcare Research and Quality.Study design and setting We focused on recurrent issues in the EPC program and the recommendations were developed using group discussion and consensus based on current knowledge in the literature.Results We first discussed considerations for deciding whether to combine studies, followed by discussions on indirect comparison and incorporation of indirect evidence. Then, we described our recommendations on choosing effect measures and statistical models, giving special attention to combining studies with rare events; and on testing and exploring heterogeneity. Finally, we briefly presented recommendations on combining studies of mixed design and on sensitivity analysis.Conclusion Quantitative synthesis should be conducted in a transparent and consistent way. Inclusion of multiple alternative interventions in CERs increases the complexity of quantitative synthesis, whereas the basic issues in quantitative synthesis remain crucial considerations in quantitative synthesis for a CER. We will cover more issues in future versions and update and improve recommendations with the accumulation of new research to advance the goal for transparency and consistency.

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Metadata

Authors
Fu, R., Gartlehner, G., Grant, M., Shamliyan, T., Sedrakyan, A., Wilt, T. J., Griffith, L., Oremus, M., Raina, P., Ismaila, A., Santaguida, P., Lau, J., & Trikalinos, T. A.
Affiliations
  • Oregon Health & Science University (US)
  • Universität für Weiterbildung Krems (AT)
  • Blue Cross Blue Shield Association (US)
  • University of Minnesota (US)
  • Agency for Healthcare Research and Quality (US)
  • McMaster University (CA)
  • Tufts Medical Center (US)
Corresponding author
Fu, Rongwei
ORCID
Venue
Journal of Clinical Epidemiology
Publisher
Elsevier BV
Published
2011-11
Volume
64
Issue
11
Pages
1187-1197
ISSN
0895-4356 (ISSN-L)
DOI
10.1016/j.jclinepi.2010.08.010
OpenAlex
W2145171366
Cited by
730
References
62
Citations by year
2026: 46 · 2025: 64 · 2024: 88 · 2023: 75 · 2022: 99 · 2021: 92 · 2020: 56 · 2019: 50 · 2018: 29 · 2017: 27 · 2016: 33 · 2015: 26 · 2014: 18 · 2013: 13 · 2012: 10
FWCI
14.89
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Journal of Clinical Epidemiology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Agency for Healthcare Research and Quality
  • H2020 European Research Council
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Social Sciences › Sociology and Political Science › Delphi Technique in Research
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
Keywords
meta-analysis, comparative effectiveness research, evidence-based practice centers, Agency for Healthcare Research and Quality, indirect comparison, effect measures, rare events, heterogeneity, sensitivity analysis
MeSH terms
Data Interpretation, Statistical, Humans, Review Literature as Topic, Statistics as Topic, United States, Meta-Analysis as Topic, Models, Statistical, Bias, United States Agency for Healthcare Research and Quality, Outcome Assessment, Health Care, Evidence-Based Medicine, Consensus, Comparative Effectiveness Research

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