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Financial Disclosures Reported by Industry Among Authors of the American Academy of Ophthalmology Clinical Practice Guidelines

2023· article· en· W4327576396 on OpenAlexaff
Anne Xuan-Lan Nguyen, Maxine Joly-Chevrier, David‐Dan Nguyen, Albert Y. Wu

Bibliographic record

VenueJAMA Ophthalmology · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of TorontoUniversité de MontréalMcGill University Health Centre
FundersNational Eye InstituteResearch to Prevent Blindness
KeywordsGuidelineMedicinePaymentMedicaidFamily medicineClinical PracticeMEDLINEAccountingFinanceHealth careBusinessLaw

Abstract

fetched live from OpenAlex

Importance: Recommendations of clinical guidelines affect physicians' care delivery. Potential bias and undeclared conflicts of interests (COIs) among guideline authors can impact clinical practice decisions. Objective: To assess financial disclosures reported by physician authors of the American Academy of Ophthalmology (AAO) Practice Pattern Guidelines compared with those reported by industry to evaluate the disclosures' accuracy. Design, Setting, and Participants: In this cross-sectional study, all clinical guidelines in the AAO Preferred Practice Patterns (PPP) since 2013 (first year with publicly available industry payment reports) were reviewed on May 1, 2022. Guideline physician authors' name and their reported COI disclosure were extracted from the guideline publication. Payments to physician authors reported by industry were retrieved from the US Centers for Medicare & Medicaid Open Payments database. Physician authors serving on the AAO guideline committee were included. Main Outcomes and Measures: The primary outcome measure was the accuracy of authors' COIs disclosure. Secondary outcome measures were payments to physician authors reported by industry, the types of payments, and authors' gender. Results: A total of 24 AAO guidelines released between 2016 and 2020 were included. Per guideline, there was a mean (SD) of 7.83 (2.24) physician authors. After removing 14 nonphysician authors, 188 physician author names remained, including 83 names assigned as women (44.1%) and 105 names assigned as men (55.9%). Authors could be counted multiple times in these 188 names. According to the Open Payments database, industry reported that 112 of 188 physician authors (59.6%) had at least received 1 payment while serving on the guideline committee, with a payment mean (SD) of $29 849.35 ($54 131.56). According to AAO guidelines, 149 authors (79.3%) had no financial disclosures while serving on the guideline committee. Among these 149 authors, most authors (81 [54.4%]) had payments reported by industry on the Open Payments database not disclosed within the guideline reports. Women physicians were paid significantly more than men for total payments (median [IQR] payments, $15 265 [$598.47-$41 104.67] vs $301.48 [$218.85-$14 615.09]; difference, $14 963.52; P = .003). Conclusions and Relevance: Industry reported physician guideline authors to have received significant industry payments, some of which were not disclosed within information of the guidelines. To strengthen author transparency regarding these reported disclosures, the authors may want to review and resolve such potential discrepancies during the review and subsequent publication of guidelines.

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)0.045
metaresearch head score (Gemma)0.284
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 score0.999
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.284
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.595
GPT teacher head0.651
Teacher spread0.055 · 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

Citations15
Published2023
Admission routes1
Has abstractyes

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