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Record W2016056732 · doi:10.1200/jco.2008.21.6606

Relationships Between Authorship Contributions and Authors' Industry Financial Ties Among Oncology Clinical Trials

2010· article· en· W2016056732 on OpenAlex
Susannah Rose, Monika K. Krzyzanowska, Steven Joffe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Oncology · 2010
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer Research
FundersNational Cancer Institute
KeywordsMedicineClinical trialTest (biology)Odds ratioOddsFamily medicineInternal medicineOncologyLogistic regression

Abstract

fetched live from OpenAlex

PURPOSE To test the hypothesis that authors who play key scientific roles in oncology clinical trials, and who therefore have increased influence over the design, analysis, interpretation or reporting of trials, are more likely than those who do not play such roles to have financial ties to industry. METHODS Data were abstracted from all trials (n = 235) of drugs or biologic agents published in the Journal of Clinical Oncology between January 1, 2006 and June 30, 2007. Article-level data included sponsorship, age group (adult v pediatric), phase, single versus multicenter, country (United States v other), and number of authors. Author-level data (n = 2,927) included financial ties (eg, employment, consulting) and performance of key scientific roles (ie, conception/design, analysis/interpretation, or manuscript writing). Associations between performance of key roles and financial ties, adjusting for article-level covariates, were examined using generalized linear mixed models. Results One thousand eight hundred eighty-one authors (64%) reported performing at least one key role, and 842 authors (29%) reported at least one financial tie. Authors who reported performing a key role were more likely than other authors to report financial ties to industry (adjusted odds ratio [OR], 4.3; 99% CI, 3.0 to 6.0; P < .0001). The association was stronger among trials with, compared with those without, industry funding (OR, 5.0 [99% CI, 3.4 to 7.5] v OR, 2.5 [99% CI, 1.3 to 4.8]), but was present regardless of sponsorship. CONCLUSION Authors who perform key roles in the conception and design, analysis, and interpretation, or reporting of oncology clinical trials are more likely than authors who do not perform such roles to have financial ties to industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Incentives · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptMetaresearchResearch integrity
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.225
metaresearch head score (Gemma)0.280
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2250.280
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0290.097
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.893
GPT teacher head0.745
Teacher spread0.148 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it