Characterization of industry relationships in oncology
Notice bibliographique
Résumé
BACKGROUND: Collaborative relationships between academic oncology and industry (pharmaceutical, biotechnology, "omic," and medical device companies) are essential for therapeutic development in oncology; however, limited research on engagement in and perceptions of these relationships has been done. METHODS: Survey questions were developed to evaluate relationships between academic oncology and industry. An electronic survey was delivered to 1000 randomly selected members of the American Society of Clinical Oncology, a professional organization for oncologists, eliciting respondents' views around oncology-industry collaborations. The responses were analyzed according to prespecified plans. RESULTS: There were 225 survey respondents. Most were from the United States (70.0%), worked at an academic institution (60.1%), worked in medical oncology (81.2%), and had an active relationship with industry (85.8%). One quarter (26.7%) of respondents reported difficulty establishing a relationship with industry collaborators, and most respondents (75%) did not report having had mentorship in developing these relationships. The majority (85.3%) of respondents considered these collaborations important to their careers. Respondents generally thought that scientific integrity was preserved (92%), and most respondents (95%) had little concern over the quality of the collaborative product. Many (60%) shared concerns over potential conflict of interest if an individual with a compensated relationship promoted an industry product for clinical care/research, yet most respondents (67%) stated these relationships did not shape their interactions with patients. CONCLUSIONS: This study provides novel data characterizing the nature of collaborative relationships between clinicians, researchers, and industry in oncology. Although respondents considered these collaborations an important part of clinical and academic oncology, formal education or mentorship around these relationships was rare. Conflicting findings around conflict of interest highlight the importance of more dedicated research in this area. PLAIN LANGUAGE SUMMARY: Business enterprises in health care play a central role in cancer research and care, driving the development of new medical testing, drugs, and devices. Effective working relationships among clinicians, researchers, and these industry partners can promote innovative research and enhance patient care. Study of these collaborations has been limited to date. Through distribution of a questionnaire to cancer clinicians and researchers, we found that most participants consider these relationships valuable, though they find establishing such relationships challenging partly because of gaps in educational programs in this area. Our findings also highlight the need for further policy around the potential bias these relationships can introduce.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».