CoChat
Sign Up
Cited by 1,049Meta-analysis and systematic reviewsStatistical Methods in Clinical TrialsAdvanced Causal Inference Techniques

The DOI matches its Crossref record; 40 of the 41 references it cites were found in a registry or an index.

Influence of Reported Study Design Characteristics on Intervention Effect Estimates From Randomized, Controlled Trials

Savović, Jelena, Jones, Hayley E., Altman, Douglas G., Harris, Ross J., Jüni, Peter, Pildal, Julie, Als-Nielsen, Bodil, Balk, Ethan M., Gluud, Christian, Gluud, Lise Lotte, Ioannidis, John P.A., Schulz, Kenneth F., Beynon, Rebecca, Welton, Nicky J., Wood, Lesley, Moher, David, Deeks, Jonathan J., Sterne, Jonathan A.C.·2012·Annals of Internal Medicine
DOI 10.7326/0003-4819-157-6-201209180-00537
Open this paper in CoChat — free account

Abstract

Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as "mortality," "other objective," "or subjective," and Bayesian hierarchical models were used to estimate associations of trial characteristics with average bias and between-trial heterogeneity. Intervention effect estimates seemed to be exaggerated in trials with inadequate or unclear (vs. adequate) random-sequence generation (ratio of odds ratios, 0.89 [95% credible interval {CrI}, 0.82 to 0.96]) and with inadequate or unclear (vs. adequate) allocation concealment (ratio of odds ratios, 0.93 [CrI, 0.87 to 0.99]). Lack of or unclear double-blinding (vs. double-blinding) was associated with an average of 13% exaggeration of intervention effects (ratio of odds ratios, 0.87 [CrI, 0.79 to 0.96]), and between-trial heterogeneity was increased for such studies (SD increase in heterogeneity, 0.14 [CrI, 0.02 to 0.30]). For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes.

Overview

Integrity signals

Registry

Crossref · 10.7326/0003-4819-157-6-201209180-00537

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 41 references

Cited by

Sorted by citations

Items 801–900 of 999

Related

See all

Metadata

Authors
Savović, J., Jones, H. E., Altman, D. G., Harris, R. J., Jüni, P., Pildal, J., Als-Nielsen, B., Balk, E. M., Gluud, C., Gluud, L. L., Ioannidis, J. P. A., Schulz, K. F., Beynon, R., Welton, N. J., Wood, L., Moher, D., Deeks, J. J., & Sterne, J. A. C.
Affiliations
University of Bern (CH)
ORCID
Venue
Annals of Internal Medicine
Publisher
American College of Physicians
Published
2012-09-18
Volume
157
Issue
6
Pages
429-438
ISSN
  • 0003-4819 (ISSN-L)
  • 1539-3704
DOI
10.7326/0003-4819-157-6-201209180-00537
OpenAlex
W1964502734
Semantic Scholar
5667b851bbf788508a249be0a5243029fcf25bdd
Cited by
1,049
References
41
Citations by year
2026: 21 · 2025: 44 · 2024: 51 · 2023: 44 · 2022: 50 · 2021: 68 · 2020: 67 · 2019: 84 · 2018: 99 · 2017: 100 · 2016: 93 · 2015: 112 · 2014: 113 · 2013: 87 · 2012: 9
FWCI
115.35
Type
journal article
Language
en
Open access
closed
Licence
www.acpjournals.org/journal/aim/text-and-data-mining (tdm)
Locations
  • Annals of Internal Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • BORIS (University Library Bern) (submittedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
  • Bristol Research (University of Bristol) (submittedVersion)
Funders
National Institute for Health and Care Research (NF-SI-0611-10168)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords
trial design bias, random sequence generation, allocation concealment, double blinding, between-trial heterogeneity, meta-epidemiology, subjective outcomes, mortality, trial reporting quality
MeSH terms
Bayes Theorem, Double-Blind Method, Humans, Research Design, Meta-Analysis as Topic, Bias, Odds Ratio, Randomized Controlled Trials as Topic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review