Gender representation in authorship in later-phase systemic clinical trials in biliary tract cancer (BTC).
Notice bibliographique
Résumé
348 Background: The proportion of females in medicine is increasing (approx. 50% in medical school/workforce), but disparities in female authorship in oncology research publications exist; female corresponding authorship reportedly ranges from 7.2-39.1% in oncology clinical trials (Ludmir et al 2019). This study aimed to describe and assess factors associated with female first and senior authorship in later phase systemic clinical trials in BTC and to identify any changes over time. Methods: Embase/Medline were used to identify final primary trial publications in BTC (2000-2020) (excluding phase I (PI) (expected to move to later phase), mixed tumour site trials, reviews, editorials and trial-in-progress publications). Gender was determined by inspection of names, google search and author communication. Chi-square tests and log regression were used to assess factors associated with female first and senior authorship, including changes over time (STATA16). Results: Of 501 publications, 163 met inclusion criteria; 80% single-arm PII and 15% and 5% randomised PII and PIII respectively; 73% enrolled ≤50 patients. Tumour primary sites were all BTC: 86%, cholangiocarcinoma: 8%, gallbladder cancer: 6%; 80% involved chemotherapy, 13% targeted therapy and 5% localised/systemic combinations; 65% were in first-line (1L) advanced setting, 17% post 1L, 13% advanced non-specified and 5% neo-adjuvant/adjuvant. Forty-eight percent received industry funding and 65% met primary end-point. Sixty-four percent were published post ABC-02 (Valle et al 2010). Publication impact factor (IF) was ≤5 in 50% and >20 in 12%. Median number of authors in all publications was 11. Geographic location of all first and senior authors were Asia (42%/42%), Europe (29%/29%), USA (24%/22%) and other (4%/6%), respectively. Median individual trial female author representation was 25%; there were no female authors in 12% of trials. Overall, female first and senior author representation was 21% and 11%, respectively. Median position of first female author was second. In publications with IF ≤20 and >20, there were 22% and 16% female first and 13% and 0% female senior authors, respectively. The phase of trial, journal IF, industry funding, or whether met primary end-point did not impact female first or senior author representation (all P>.05). There were more female senior authors associated with “other” geographic locations (40% in 10 trials) (P=.016) vs Asia (7%), Europe (8%) and USA (14%). There were no significant changes in female first or senior author representation over time (‘00-05: 21%/18%, ‘06-10: 27%/5%, ‘11-15: 15%/15%, ‘16-20: 22%/9%, P=.738, and P=.508 respectively). Conclusions: Female first and senior author representation in later phase systemic clinical trial publications in BTC is low and has not changed significantly over time. The underlying reasons for this imbalance need to be better understood and addressed.
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 | 0,038 | 0,163 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,008 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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; 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 ».