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Record W3187036481 · doi:10.6004/jnccn.2021.7016

Do Editorialists With Industry-Related Conflicts of Interest Write Unduly Favorable Editorials for Cancer Drugs in Top Journals?

2021· article· en· W3187036481 on OpenAlexaff
Shubham Sharma, Christopher M. Booth, Elizabeth A. Eisenhauer, Bishal Gyawali

Bibliographic record

VenueJournal of the National Comprehensive Cancer Network · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineConflict of interestClinical trialInternal medicineClinical OncologyAlternative medicinePublicationOncologyFamily medicineCancerPathologyLaw

Abstract

fetched live from OpenAlex

BACKGROUND: Editorials accompanying the publication of trials in major oncology journals can have a substantial influence on clinical practice. We describe the prevalence of financial conflicts of interest (FCOIs) of authors writing such editorials and the extent to which FCOIs may shape the interpretation of clinical trials. METHODS: We examined editorials published in 2018 alongside trial reports in the top 5 journals that publish cancer drug trials (New England Journal of Medicine, Lancet, Lancet Oncology, JAMA Oncology, and Journal of Clinical Oncology). An editorial was considered to have an FCOI if at least one of the editorialists had any disclosed FCOI. An FCOI with the same company whose drug was being discussed in the editorial was classified as a direct FCOI. Editorials were reviewed for their content and classified as being unduly favorable (defined as the presence of a positive spin without discussion of limitations) or not. Association of an FCOI and a direct FCOI with writing an unduly favorable editorial was assessed. RESULTS: Of the 90 editorials assessed, 74% (n=67) were classified as having an FCOI with the pharmaceutical industry, and 39% (n=35) had an FCOI with the same company whose product was being discussed in the editorial (direct FCOI). Editorials were classified as being unduly favorable toward the study drug in 12% (8 of 67) and 13% (3 of 23) (P=1.0) of those with and without FCOIs, respectively; corresponding rates with and without direct FCOI were 23% (8 of 35) and 5% (3 of 55), respectively (P=.009). CONCLUSIONS: Editorials in top oncology journals were frequently authored by experts with FCOIs, including direct FCOIs. Authoring an unduly favorable editorial for a new cancer drug was significantly associated with the author having a direct FCOI with the same company. These findings support the call for journals to ensure that authors of editorials have no direct FCOIs.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.125
metaresearch head score (Gemma)0.609
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.661

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1250.609
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.010
Science and technology studies0.0040.004
Scholarly communication0.0100.005
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.496
GPT teacher head0.562
Teacher spread0.066 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

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".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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