The Resource Detection of associations between trial quality and effect sizes, prepared for, Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by, Southern California Evidence-based Practice Center, RAND Corporation ; investigators, Susanne Hempel ... [et al.], (electronic resource)

Detection of associations between trial quality and effect sizes, prepared for, Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by, Southern California Evidence-based Practice Center, RAND Corporation ; investigators, Susanne Hempel ... [et al.], (electronic resource)

Label
Detection of associations between trial quality and effect sizes
Title
Detection of associations between trial quality and effect sizes
Statement of responsibility
prepared for, Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by, Southern California Evidence-based Practice Center, RAND Corporation ; investigators, Susanne Hempel ... [et al.]
Contributor
Subject
Language
  • eng
  • eng
Summary
OBJECTIVES: To examine associations between a set of trial quality criteria and effect sizes and to explore factors influencing the detection of associations in meta-epidemiological datasets. DATA SOURCES: The analyses are based on four meta-epidemiological datasets. These datasets consist of a number of meta-analyses; each contained between 100 and 216 controlled trials. These datasets have "known" qualities, as they were used in published research to investigate associations between quality and effect sizes. In addition, we created datasets using Monte Carlo simulation methods to examine their properties. REVIEW METHODS: We identified treatment effect meta-analyses and included trials and extracted treatment effects for four meta-epidemiological datasets. We assessed quality and risk of bias indicators with 11 Cochrane Back Review Group (CBRG) criteria. In addition, we applied the Jadad criteria, criteria proposed by Schulz (e.g., allocation concealment), and the Cochrane Risk of Bias tool. We investigated the effect of individual criteria and quantitative summary scores on the reported treatment effect sizes. We explored potential reasons for differences in associations across different meta-epidemiological datasets, clinical fields and individual meta-analyses. We investigated factors that influence the power to detect associations between quality and effect sizes in Monte Carlo simulations. RESULTS: Associations between quality and effect sizes were small, e.g. the ratio of odds ratios (ROR) for unconcealed (vs. concealed) trials was 0.89 (95% CI: 0.73, 1.09, n.s.), but consistent across the CBRG criteria. Based on a quantitative summary score, a cut-off of six or more criteria met (out of 11) differentiated low- and high-quality trials best with lower quality trials reporting larger treatment effects (ROR 0.86, 95% CI: 0.70, 1.06, n.s.). Results for evidence of bias varied between datasets, clinical fields, and individual meta-analyses. The simulations showed that the power to detect quality effects is, to a large extent, determined by the degree of residual heterogeneity present in the dataset. CONCLUSIONS: Although trial quality may explain some amount of heterogeneity across trial results in meta-analyses, the amount of additional heterogeneity in effect sizes is a crucial factor in determining when associations between quality and effect sizes can be detected. Detecting quality moderator effects requires more statistically powerful analyses than are employed in most investigations
Member of
Cataloging source
DNLM
Funding information
Prepared for: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services,540 Gaither Road, Rockville, MD 20850; www.ahrq.gov Contract No. HHSA 290-2007-10056-I. Prepared by: Southern California Evidence-based Practice CenterRAND Corporation, 1776 Main Street, Santa Monica, CA 90407
Government publication
federal national government publication
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
NLM call number
WA 950
http://library.link/vocab/relatedWorkOrContributorName
  • Hempel, Susanne
  • United States
  • Southern California Evidence-Based Practice Center/RAND
Series statement
  • Methods research report
  • AHRQ publication
Series volume
no. 12-EHC010-EF
http://library.link/vocab/subjectName
  • Meta-Analysis as Topic
  • Randomized Controlled Trials as Topic
  • Bias
  • Effect Modifier, Epidemiologic
  • Research Design
Label
Detection of associations between trial quality and effect sizes, prepared for, Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by, Southern California Evidence-based Practice Center, RAND Corporation ; investigators, Susanne Hempel ... [et al.], (electronic resource)
Instantiates
Publication
Note
  • "January 2012."
  • "Contract No. HHSA 290-2007-10056-I."
Bibliography note
Includes bibliographical references
Dimensions
unknown
Form of item
online
Specific material designation
remote
System control number
  • 1581854
  • (DNLM)BKSHLF:NBK84249
Label
Detection of associations between trial quality and effect sizes, prepared for, Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by, Southern California Evidence-based Practice Center, RAND Corporation ; investigators, Susanne Hempel ... [et al.], (electronic resource)
Publication
Note
  • "January 2012."
  • "Contract No. HHSA 290-2007-10056-I."
Bibliography note
Includes bibliographical references
Dimensions
unknown
Form of item
online
Specific material designation
remote
System control number
  • 1581854
  • (DNLM)BKSHLF:NBK84249

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