Global mapping of randomised trials related articles published in high-impact-factor medical journals: a cross-sectional analysis
Notice bibliographique
Résumé
BACKGROUND: Randomised controlled trials (RCTs) provide the most reliable information to inform clinical practice and patient care. We aimed to map global clinical research publication activity through RCT-related articles in high-impact-factor medical journals over the past five decades. METHODS: We conducted a cross-sectional analysis of articles published in the highest ranked medical journals with an impact factor > 10 (according to Journal Citation Reports published in 2017). We searched PubMed/MEDLINE (from inception to December 31, 2017) for all RCT-related articles (e.g. primary RCTs, secondary analyses and methodology papers) published in high-impact-factor medical journals. For each included article, raw metadata were abstracted from the Web of Science. A process of standardization was conducted to unify the different terms and grammatical variants and to remove typographical, transcription and/or indexing errors. Descriptive analyses were conducted (including the number of articles, citations, most prolific authors, countries, journals, funding sources and keywords). Network analyses of collaborations between countries and co-words are presented. RESULTS: We included 39,305 articles (for the period 1965-2017) published in forty journals. The Lancet (n = 3593; 9.1%), the Journal of Clinical Oncology (n = 3343; 8.5%) and The New England Journal of Medicine (n = 3275 articles; 8.3%) published the largest number of RCTs. A total of 154 countries were involved in the production of articles. The global productivity ranking was led by the United States (n = 18,393 articles), followed by the United Kingdom (n = 8028 articles), Canada (n = 4548 articles) and Germany (n = 4415 articles). Seventeen authors who had published 100 or more articles were identified; the most prolific authors were affiliated with Duke University (United States), Harvard University (United States) and McMaster University (Canada). The main funding institutions were the National Institutes of Health (United States), Hoffmann-La Roche (Switzerland), Pfizer (United States), Merck Sharp & Dohme (United States) and Novartis (Switzerland). The 100 most cited RCTs were published in nine journals, led by The New England Journal of Medicine (n = 78 articles), The Lancet (n = 9 articles) and JAMA (n = 7 articles). These landmark contributions focused on novel methodological approaches (e.g. the "Bland-Altman method") and trials on the management of chronic conditions (e.g. diabetes control, hormone replacement therapy in postmenopausal women, multiple therapies for diverse cancers, cardiovascular therapies such as lipid-lowering statins, antihypertensive medications, and antiplatelet and antithrombotic therapy). CONCLUSIONS: Our analysis identified authors, countries, funding institutions, landmark contributions and high-impact-factor medical journals publishing RCTs. Over the last 50 years, publication production in leading medical journals has increased, with Western countries leading in research but with low- and middle-income countries showing very limited representation.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,607 | 0,807 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,018 | 0,011 |
| Bibliométrie | 0,001 | 0,013 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,237 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».