Design, reporting, and disparities of advanced non–small cell lung cancer phase 3 clinical trials in the era of immunotherapy.
Notice bibliographique
Résumé
e13616 Background: Lung cancer remains the main cause of cancer-related mortality globally, with non-small cell (NSCLC) accounting for the majority of cases. The advent of immunotherapy (IO) has expanded treatment options for advanced NSCLC. However, there are no bibliometric studies exploring NSCLC IO-based trials. We aimed to provide a systematic and comprehensive analysis of the design, reporting, population, and disparities of phase 3 trials investigating IO for advanced NSCLC. Methods: MEDLINE search was performed (last decade) for phase 3 trials reporting on patients with advanced (stage IIIA or higher) NSCLC. We assessed relationships between study outcomes, funding transparency, conflict of interest, journal impact factor (IF), region, gender of the first and last authors, population size, and ethnicity. Results: From 2012 to 2022, 2556 articles were screened and 81 were included. Overall survival (OS), followed by progression/disease-free survival (PFS) and overall/objective response (ORR) were the most commonly reported primary endpoints, representing 54%, 44%, and 15% respectively. The majority of the studies ( > 97%) had a funding sources statement and declared COI. Male first and last authorship represented 84% and 74% of studies, respectively. In 62% of trials reporting the patient’s ethnicity, white was the most common (65%). Regarding the source of funding, 74% of trials reported industry-only, 8% academia-only, 11% combined, 4% no funding received and 2.5% were not transparent. 98% of trials were from high-income countries (HIC), being the US (37%) and China (26%) the most reported. The mean number of authors with declared COI was 10.55 [0-25] and the mean total number of authors was 21.3 [5-76]. Publications journals' mean IF was 57.7 [2.1-202.7]. COI declaration was associated with publication in a journal with a higher IF compared to studies with no declared COI (p < 0.05). The journal IF was significantly higher in the US publications compared to China (p < 0.01). Trials assessing OS and PFS as their primary outcome were published with a higher IF in relation to assessing ORR only (p < 0.05). There was a significant association between the first and last authors' gender (p < 0.05), with a higher likelihood of matching genders (OR = 4,5 [1,3-14,4]). There was no association between the proportion of COI among authors, source of funding, and first author’s gender with journal IF. Conclusions: Phase 3 trials exploring IO for advanced NSCLC are majorly done in HIC, report industry funding and COI, and have males as the first and last authors. PFS is the primary outcome of almost 50% of the trials. We identified that among the primary outcomes studied, declaration of COI and author’s geographic affiliation may influence the publication’s IF. Sustained efforts are required to guarantee impartial reporting of clinical trial results and inclusive 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 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 | 0,342 | 0,609 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,008 | 0,010 |
| Bibliométrie | 0,020 | 0,025 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex 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 ».