Abstract LB148: Perspectives of clinical trial staff on recruitment barriers to a multicenter randomized controlled colorectal polyp prevention trial
Notice bibliographique
Résumé
Abstract Background: Participant recruitment remains a pervasive issue in clinical trial management. Colorectal cancer (CRC) is a growing cause of cancer-related morbidity and mortality globally, making CRC prevention crucial. COLO-PREVENT is a 10-year multicenter randomized controlled trial platform assessing the efficacy of aspirin versus aspirin plus metformin in a phase 3 study, alongside a phase 2 study of resveratrol compared to placebo for the prevention of colorectal polyps in high-risk individuals identified via the Bowel Cancer Screening Program (BCSP) in the United Kingdom. It aims to recruit 1300 participants. While the extended trial duration may affect recruitment, additional barriers within a prevention trial population have not been studied. Methods: A questionnaire was distributed to clinical trial staff (research nurses, site coordinators) across 14 sites. The questionnaire focused on recruitment processes, the recruitment barriers noted, as well as strategies to overcome these barriers. Data was thematically analyzed by 2 researchers (FF, MS). Common themes were identified regarding recruitment barriers, as well as strategies to address recruitment barriers. Recruitment strategies were correlated with site randomization numbers to assess effectiveness. Results: There were four key common themes identified by site research teams as participant barriers to recruitment: Logistical requirements of the trial (36.8%), medication concerns (36.8%), ambiguity in the study processes (15.8%), and unclear benefit to participation (10.5%). Sites with higher randomization numbers worked closely with their local BCSP teams to ensuring they had accurate lists of potential participants. Subsequently, multiple follow-up strategies using various mediums (e.g. phone calls, emails, and in-person contact) were felt to be beneficial. Additionally, blood tests required for screening prior to recruitment were used for health monitoring and reassurance regarding medication side effects leading to a more personalized experience for participants. Conclusion: This study highlights key reasons why participants may decline to join prevention trials, including logistical difficulties, medication concerns, and unclear perceived benefits. Additional factors requiring further exploration include: the inclusion of a symptomatically healthy population which is a known recruitment barrier. Strategies such as strong integration with the local BCSP team, personalized participant engagement, and participant reassurance with blood tests may improve recruitment outcomes in CRC prevention trials. Future research should focus on understanding participant perspectives first-hand, examining other cancer prevention disease areas, and developing targeted solutions to ensure more effective prevention clinical trial design. Citation Format: Frankie Fan, Moiz Shakeel, Nafisa Boota, Hilary Adamson, Ajay Verma, Karen Brown. Perspectives of clinical trial staff on recruitment barriers to a multicenter randomized controlled colorectal polyp prevention trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB148.
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 | 0,609 | 0,732 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,012 | 0,008 |
| Communication savante | 0,014 | 0,008 |
| Science ouverte | 0,006 | 0,010 |
| Intégrité de la recherche | 0,008 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,002 |
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 ».