The Effect of Funding Source on Outcome Reporting Among Drug Trials
Bibliographic record
Abstract
Letters18 January 2011The Effect of Funding Source on Outcome Reporting Among Drug TrialsFlorence T. Bourgeois, MD, MPH, Kenneth D. Mandl, MD, MPH, and Srinivas Murthy, MDFlorence T. Bourgeois, MD, MPHFrom Children's Hospital Boston, Boston, MA 02115, and Hospital for Sick Children, Toronto, Ontario M5G 1X9, Canada.Search for more papers by this author, Kenneth D. Mandl, MD, MPHFrom Children's Hospital Boston, Boston, MA 02115, and Hospital for Sick Children, Toronto, Ontario M5G 1X9, Canada.Search for more papers by this author, and Srinivas Murthy, MDFrom Children's Hospital Boston, Boston, MA 02115, and Hospital for Sick Children, Toronto, Ontario M5G 1X9, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-154-2-201101180-00021 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We appreciate the opinions and comments on our article, which reflect an important debate over explanations for the higher rate of favorable findings reported among industry-funded trials. Dr. Turner points out that the median anticipated sample sizes were larger among trials funded by industry than among those funded by noncommercial sources and questions whether the increased statistical power alone explains our finding of more favorable results among industry-funded trials. Dr. Turner is correct that in general, larger, more adequately powered trials are more likely to yield statistically significant results. Our multivariate model demonstrated an effect of primary funding ...Reference1. U.S. Food and Drug Administration Amendments Act of 2007. Pub. L. No. 105-185 (2007). Google Scholar Author, Article, and Disclosure InformationAffiliations: From Children's Hospital Boston, Boston, MA 02115, and Hospital for Sick Children, Toronto, Ontario M5G 1X9, Canada.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M10-0087. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoOutcome Reporting Among Drug Trials Registered in ClinicalTrials.gov Florence T. Bourgeois , Srinivas Murthy , and Kenneth D. Mandl The Effect of Funding Source on Outcome Reporting Among Drug Trials Erick H. Turner The Effect of Funding Source on Outcome Reporting Among Drug Trials Adam Jacobs The Effect of Funding Source on Outcome Reporting Among Drug Trials Deborah A. Zarin and Tony Tse Metrics 18 January 2011Volume 154, Issue 2Page: 138KeywordsConflicts of interestDisclosureDrugsFactor analysisMultivariate analysis ePublished: 18 January 2011 Issue Published: 18 January 2011 CopyrightCopyright © 2011 by American College of Physicians. All Rights Reserved.PDF DownloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.806 | 0.950 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.019 | 0.026 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".