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Cited by 746Pharmaceutical industry and healthcareStatistical Methods in Clinical TrialsMeta-analysis and systematic reviews

The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.

Association of Funding and Conclusions in Randomized Drug Trials: A Reflection of Treatment Effect or Adverse Events?

Als-Nielsen, Bodil, Chen, Wendong, Gluud, Christian, Kjaergard, Lise L.·2003·JAMA
DOI 10.1001/jama.290.7.921
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Abstract

CONTEXT: Previous studies indicate that industry-sponsored trials tend to draw proindustry conclusions. OBJECTIVE: To explore whether the association between funding and conclusions in randomized drug trials reflects treatment effects or adverse events. DESIGN: Observational study of 370 randomized drug trials included in meta-analyses from Cochrane reviews selected from the Cochrane Library, May 2001. From a random sample of 167 Cochrane reviews, 25 contained eligible meta-analyses (assessed a binary outcome; pooled at least 5 full-paper trials of which at least 1 reported adequate and 1 reported inadequate allocation concealment). The primary binary outcome from each meta-analysis was considered the primary outcome for all trials included in each meta-analysis. The association between funding and conclusions was analyzed by logistic regression with adjustment for treatment effect, adverse events, and additional confounding factors (methodological quality, control intervention, sample size, publication year, and place of publication). MAIN OUTCOME MEASURE: Conclusions in trials, classified into whether the experimental drug was recommended as the treatment of choice or not. RESULTS: The experimental drug was recommended as treatment of choice in 16% of trials funded by nonprofit organizations, 30% of trials not reporting funding, 35% of trials funded by both nonprofit and for-profit organizations, and 51% of trials funded by for-profit organizations (P<.001; chi2 test). Logistic regression analyses indicated that funding, treatment effect, and double blinding were the only significant predictors of conclusions. Adjusted analyses showed that trials funded by for-profit organizations were significantly more likely to recommend the experimental drug as treatment of choice (odds ratio, 5.3; 95% confidence interval, 2.0-14.4) compared with trials funded by nonprofit organizations. This association did not appear to reflect treatment effect or adverse events. CONCLUSIONS: Conclusions in trials funded by for-profit organizations may be more positive due to biased interpretation of trial results. Readers should carefully evaluate whether conclusions in randomized trials are supported by data.

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Crossref · 10.1001/jama.290.7.921

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Metadata

Authors
Als-Nielsen, B., Chen, W., Gluud, C., & Kjaergard, L. L.
Affiliations
Copenhagen University Hospital (DK)
ORCID
Venue
JAMA
Publisher
American Medical Association (AMA)
Published
2003-08-20
Volume
290
Issue
7
Pages
921
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
DOI
10.1001/jama.290.7.921
OpenAlex
W2142947341
Cited by
746
References
68
Citations by year
2026: 12 · 2025: 9 · 2024: 10 · 2023: 15 · 2022: 27 · 2021: 22 · 2020: 18 · 2019: 9 · 2018: 27 · 2017: 30 · 2016: 20 · 2015: 26 · 2014: 37 · 2013: 53 · 2012: 46
FWCI
34.42
Type
journal article
Language
en
Open access
closed
Locations
  • JAMA (publishedVersion)
  • PubMed (publishedVersion)
  • DigitalGeorgetown (Georgetown University Library) (submittedVersion)
Topics
  • Health Sciences › Nursing › Issues, ethics and legal aspects › Pharmaceutical industry and healthcare
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
industry funding, pharmaceutical industry funding, nonprofit funding, treatment guidelines, allocation concealment, double blinding, meta-analysis
MeSH terms
Drug Evaluation, Drug Industry, Organizations, Nonprofit, Research Support as Topic, Meta-Analysis as Topic, Bias, Logistic Models, Randomized Controlled Trials as Topic, Treatment Outcome

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