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Record W4281755376 · doi:10.2196/37749

Pharmaceutical Payments to Authors of Dermatology Guidelines After Publication

2022· article· en· W4281755376 on OpenAlexvenueno aff
Torunn E Sivesind, Mindy D Szeto, Jarett Anderson, Jalal Maghfour, Maya Matheny, Quan Nguyen Minh Le, Michael Kamara, Robert P. Dellavalle

Bibliographic record

VenueJMIR Dermatology · 2022
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsDermatologyPaymentMedicineBusinessFinance

Abstract

fetched live from OpenAlex

Clinical practice guidelines (CPGs) play increasingly vital and influential roles in clinical decision-making, optimization of patient care, and establishment and assessment care quality standards, and can affect insurance coverage.Oftentimes, CPG author expertise is sought by insurance and pharmaceutical companies, creating industry-physician relationships that may influence physicians' professional decisions.This is known as a conflict of interest (COI).Previous studies [1,2] provide strategies for reducing COI impact on guideline development (eg, restricting voting on final recommendations by committee members with COIs [1], requiring conflict-free periods prior to participation in guideline development [2]).In a June 2020 statement, the American Academy of Dermatology (AAD) announced revisions to its guideline development process, specifying that at least 51% of those authoring guidelines be nonconflicted (ie, no relevant financial COIs) and requiring nonconflicted authors to remain so for the entire guideline development process (ie, no new relevant industry relationships initiated during development) [3].CPG development ends when the draft guideline is approved by the AAD's Board of Directors and submitted for publication [4].The AAD requires disclosure of financial interests occurring within the 2-year period prior to CPG authorship [5].Although a prior study [6] demonstrated that former Food and Drug Administration committee members frequently received payments from the industry after the approval of dermatologic drugs, to our knowledge, there exists no similar exploration of industry payments to authors of recently published AAD guidelines.Post hoc general industry payments to AAD guideline authors in the period shortly following guideline publication (defined as publication year and 1 subsequent year) were analyzed.We reviewed all current AAD CPGs, including acne vulgaris, atopic dermatitis, keratinocyte carcinoma (basal cell carcinoma and squamous cell carcinoma, same guideline authors), melanoma, psoriasis, and surgery, with publication dates spanning from 2013 to 2018.General payments made by companies to each CPG author were extracted and aggregated from publicly available data in the Centers for Medicare and Medicaid Services Open Payments database [7].The psoriasis guideline was excluded from further analysis because, unlike the other guidelines, it was published after the recent changes to the AAD's COI policy for guideline authors, and Open Payments data was only available through 2020.The Food and Drug Administration Orange [8] and Purple [9] Book databases were searched to identify companies (and subsidiaries, according to

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)0.010
metaresearch head score (Gemma)0.127
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.722

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.127
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0030.001
Scholarly communication0.0090.003
Open science0.0010.002
Research integrity0.0140.008
Insufficient payload (model declined to judge)0.2160.146

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 head0.444
GPT teacher head0.591
Teacher spread0.147 · 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
DomainIncentives
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

Citations2
Published2022
Admission routes1
Has abstractyes

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