The Roadmap to Integrate Diversity, Equity, and Inclusion in Hematology Clinical Trials: An ASH Initiative Submitted on Behalf of the Entire Roadmap to Improve DEI in Clinical Trials Working Group
Notice bibliographique
Résumé
Background: Many classical hematologic diseases are considered rare or orphan diseases because they impact less than 6.5-10 per 10,000 people according to the World Health Organization. The small population size, poorly understood natural history, biases in healthcare, lack of inclusion of underrepresented populations, patient's limited access to research, and lack of defined clinically meaningful outcomes make enrollment of diverse patient populations in trials for these diseases challenging. These characteristics also pose unique hurdles to feasible, scientifically sound and efficient trial implementation. Furthermore, clinical trials for these rare diseases are encumbered by methodological limitations, warranting novel approaches for trial design and statistical analysis. As a result, integrating diversity, equity, and inclusion principles (DEI) in trials with small patient populations requires special consideration and innovative solutions for trial conduct and patient recruitment. Currently, there are no efforts that outline, from a multi-stakeholder perspective, the barriers to DEI in classical hematology clinical trials. To that end, The American Society of Hematology (ASH) embarked on an initiative to explore these barriers and outline opportunities to integrate DEI into trial design and conduct. Methods: ASH leveraged its convening power to conduct a systematic assessment of DEI in classical hematology clinical trials using a combination of surveys and focus group sessions. A total of 191 ASH members who self-identified as treating people with classical hematologic diseases, responded to the survey. Their feedback then informed five international focus group discussions that engaged individuals who are responsible for, or involved in, the conduct of clinical trials from inception to conclusion and in a position to enact change. These focus groups were comprised of leaders in 1) Academia; 2) Industry; 3) Lived Experience Experts (LEEs); 4) Government Agencies; and 5) Clinical and Academic Research Organizations. Each group was made up of approximately 10 individuals who participated in independent virtual sessions that generated a list of priority topics, including recommendations for integrating DEI in hematology clinical trials. One of the initial recommendations was to engage non-academic physicians, primarily those working in community settings given their role in the clinical trial ecosystem. To that end, ASH surveyed 900 ASH physicians who devote over 75% of their time to clinical practice and care primarily for people living with classical hematologic diseases. The information gathered from this survey informed subsequent focus group discussions and final recommendations. Results: Key barriers and recommendations that the focus groups identified include: 1) Harmonization of demographic terminology; 2) Engagement of LEEs across the entire study timeline; 3) Improved awareness of how implicit biases impede patient enrollment; 4) The need for institutional review boards to uphold the justice principle of clinical trial enrollment; 5) Broadening of eligibility criteria so fewer people are excluded from trial participation; 6) Expanding access using decentralized trial design; 7) Improving access to clinical trial information; and 8) Increasing involvement of community physicians in the clinical trial ecosystem. Conclusion: ASH recognizes that the opportunity to participate in clinical trials should be universal, and as is often the case with strategies to improve representation, the key issues identified also apply to all hematology trials. By addressing these issues, the hematology community can promote accessible and inclusive trials that will better inform research, clinical decision making and care for patients.
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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 | 0,067 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,011 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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; 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 ».