P404 Underrepresentation of minorities and lack of race reporting in ulcerative colitis drug development clinical trials
Notice bibliographique
Résumé
Abstract Background Historically, inflammatory bowel disease (IBD) trials report high enrollment rates for white-caucasian patients. To promote initiatives towards diversifying patients enrolled in clinical trials, we assessed the reporting of race/ethnicity of patients enrolled in pharmaceutical clinical trials for ulcerative colitis (UC). Methods A previous systematic review of all placebo-controlled trials in adult patients with UC examining different therapeutic drug classes was performed from inception to December 2020. Trial and patient characteristics were summarized according to the type of variable. Categorical variables were summarized by displaying the number and percentage of trials or participants for each category. Continuous variables were summarized by displaying the weighted mean, weighted standard deviation, and range. Means and standard deviations (SD) were weighted by the number of participants in each trial. Results Descriptive statistics of trial and patient characteristics for, 95 induction trials and, 29 maintenance trials are summarized in Table, 1. Race was reported in, 37.9% (36/95) of induction studies, with most participants being White (86.3%;, 8610/9976). Furthermore, 21/36 (58.3%) studies reported race as White vs. non-White participants; and, 15/36 (41.7%) studies provided further breakdown, including Black (115/3414 patients [3.4%]), Asian (448/4136 patients [10.8%]), and “Other” (127/4136 patients [3.1%]). Moreover, 3/36 studies misreported race as ethnicity and, only, 3/36 studies reported ethnicities correctly, classifying patients as Hispanic/Latinx vs. Non-Hispanic/Latinx. For maintenance trials, 34.5% (10/29) studies reported race, with majority of participants being White (85.6%;, 2778/3246). Additionally, 6/10 studies reported only a White vs. non-White participants comparison, while, 4/10 reported other races, including Black (45/1145 patients [3.9%]), Asian (40/888 patients [4.5%]), and “Other” (26/1145 patients [2.3%]). No studies reported ethnicity. Conclusion Given the increasing burden of IBD in developing countries, differences amongst racial and ethnic groups are important to understand since they can influence disease phenotype, response to therapy, and safety outcomes.1 We found poor race reporting in UC clinical trials and observed that the vast majority of participants enrolled were White. These findings suggest that the population prevalence of UC amongst different racial groups is not reflected in clinical trial populations, being important to raise awareness of the existing barriers that prevent patients from accessing clinical trials. Reporting of race and ethnicity in UC clinical trials should be mandatory, and a requirement to enroll a certain percentage of non-White patients should be considered.2
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 | 0,009 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».