ReCAP: Clinical Trial Assessment of Infrastructure Matrix Tool to Improve the Quality of Research Conduct in the Community
Notice bibliographique
Résumé
QUESTION ASKED: Is there a tool for sites engaged in cancer clinical research to use to assess their infrastructure and improve their research conduct toward exemplary levels of performance beyond the standard of Good Clinical Practice (GCP)? SUMMARY ANSWER: The NCI Community Cancer Center Program (NCCCP) sites, with NCI Clinical Trial advisor input, created a “Clinical Trials Best Practice Matrix” self-assessment tool to assess research infrastructure. The tool identified nine attributes (eg, physician engagement in clinical trials, accrual activity, clinical trial portfolio diversity), each with three progressive levels (I – III) for sites to score infrastructural elements from less (I) to more (III) exemplary. For example, a level-one site might have active Phase III treatment trials in two to three disease sites and review their portfolio diversity once a year, whereas a level-three site has active Phase II and also Phase I or I/II trials across five or more disease sites and reviews their portfolio quarterly. The tool also provided a road map toward more exemplary practices. METHODS: From 2011 to 2013, 21 NCCCP sites self-assessed their programs with the tool annually. Sites reported significant increases in level III (more exemplary) scores across the original nine attributes combined (P < .001 [see Figure 1 ]). During 2013 to 2014, NCI collaborators conducted a five-step formative evaluation of the tool resulting in expansion of attributes from nine to 11 and a new name: the Clinical Trials Assessment of Infrastructure Matrix, or CT AIM, tool which is described and fully presented in the manuscript. BIAS, CONFOUNDING FACTOR(S), DRAWBACKS: Tool scores are self-reported which are subject to potential bias. The tool was developed by community hospital based cancer centers and has not been psychometrically validated. Use of scores for ranking between programs is not recommended at this time. The attributes and indicators in the tool may need to be adapted for other settings (eg, academic or private practice settings), and over time as research practice evolves. Not all sites can, or want to, move beyond the provision of GCP in their research programs. Adherence to GCPs meets the minimum criteria for clinical trial conduct and some of the attributes in the CT AIM can be both fiscally and administratively challenging to implement. REAL-LIFE IMPLICATIONS: The CT AIM tool gives community programs a tool to assess their research infrastructure as they strive to move beyond the basics of GCP to more exemplary performance. Experience within the NCCCP program suggests the CT AIM tool may be useful for improving programmatic quality, benchmarking research performance, reporting progress, and communicating program needs with institutional leaders. The tool may also be a companion to existing clinical trial education and program resources. Although used in a small group of community cancer centers, the tool may be adapted as a model in other disease disciplines. [Figure: see text]
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 | 0,342 | 0,598 |
| 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 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,014 |
| 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 ».