MétaCan
Menu
Retour à la cohorte
Enregistrement W2409159770 · doi:10.1371/journal.pmed.1002029

Financial Relationships between Organizations That Produce Clinical Practice Guidelines and the Biomedical Industry: A Cross-Sectional Study

2016· article· en· W2409159770 sur OpenAlexafffund
P. Campsall, Kate Colizza, Sharon E. Straus, Henry T. Stelfox

Notice bibliographique

RevuePLoS Medicine · 2016
Typearticle
Langueen
DomainePharmacology, Toxicology and Pharmaceutics
ThématiquePharmaceutical industry and healthcare
Établissements canadiensAlberta Health ServicesUniversity of TorontoSt. Michael's HospitalUniversity of Calgary
Organismes subventionnairesAgency for Healthcare Research and QualityAlberta InnovatesAlberta Innovates - Health Solutions
Mots-clésGuidelineConflict of interestCross-sectional studyClinical PracticeBusinessAccountingProfessional associationFinancePublic relationsMedicineFamily medicinePolitical science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Financial relationships between organizations that produce clinical practice guidelines and biomedical companies are vulnerable to conflicts of interest. We sought to determine whether organizations that produce clinical practice guidelines have financial relationships with biomedical companies and whether there are associations between organizations' conflict of interest policies and recommendations and disclosures provided in guidelines. METHODS AND FINDINGS: We conducted a cross-sectional survey and review of websites of 95 national/international medical organizations that produced 290 clinical practice guidelines published on the National Guideline Clearinghouse website from January 1 to December 31, 2012. Survey responses were available for 68% (65/95) of organizations (167/290 guidelines, 58%), and websites were reviewed for 100% (95/95) of organizations (290/290 guidelines, 100%). In all, 63% (60/95) of organizations producing clinical practice guidelines reported receiving funds from a biomedical company; 80% (76/95) of organizations reported having a policy for managing conflicts of interest. Disclosure statements (disclosing presence or absence of financial relationships with biomedical companies) were available in 65% (188/290) of clinical practice guidelines for direct funding sources to produce the guideline, 51% (147/290) for financial relationships of the guideline committee members, and 1% (4/290) for financial relationships of the organizations producing the guidelines. Among all guidelines, 6% (18/290) disclosed direct funding by biomedical companies, 40% (117/290) disclosed financial relationships between committee members and biomedical companies (38% of guideline committee members, 773/2,043), and 1% (4/290) disclosed financial relationships between the organizations producing the guidelines and biomedical companies. In the survey responses, 60 organizations reported the procedures that they included in their conflict of interest policies (158 guidelines): guidelines produced by organizations reporting more comprehensive conflict of interest policies (per additional procedure, range 5-17) included fewer positive (rate ratio [RR] 0.91, 95% CI 0.86-0.95) and more negative (RR 1.32, 95% CI 1.09-1.60) recommendations regarding patented biomedical products. The clinical practice guidelines produced by organizations reporting more comprehensive conflict of interest policies were also more likely to include disclosure statements for direct funding sources (odds ratio [OR] 1.31, 95% CI 1.10-1.56) and financial relationships of guideline committee members (OR 1.36, 95% CI 1.09-1.79), but not financial relationships of the organizations (0 disclosures). Limitations of the study include the use of the National Guideline Clearinghouse as the single source of clinical practice guidelines and the self-report of survey responses and organizations' website postings. CONCLUSIONS: Financial relationships between organizations that produce clinical practice guidelines and biomedical companies are common and infrequently disclosed in guidelines. Our study highlights the need for an effective policy to manage organizational conflicts of interest and disclosure of financial relationships.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,095
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,251
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0110,095
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,002
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,004
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,773
Tête enseignante GPT0,645
Écart entre enseignants0,128 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations65
Publié2016
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revuePLoS MedicineMême sujetPharmaceutical industry and healthcareTravaux en français237 207