Abstract A11: Recruitment Monitoring Report of a Pan-Canadian Multi-center Study, the COOLS Trial.
Notice bibliographique
Résumé
Abstract Screening logs are used for clinical trials to maintain the representativeness and validity of patient recruitment. It is especially critical in the active enrolment phase of a trial. The objectives of this study are: 1) To update the screening and recruitment status and 2) To discuss the challenges in patient recruitment and benefit in using screening log in a multi-centre trial. Methods: Using Microsoft Office Excel (2007), the Central Management Team (CMT) designed a screening log template with fields based on the 2010 Consolidated Standards of Reporting Trials (CONSORT). Data were collected with respect to patient information (Screening Date, Last Initial, First Initial, Referral Sources), lesion information (Anatomical Site, Diagnosis), recruitment (Recruitment Status - eligible, ineligible, refusal or not approached; Reasons to each unsuccessful recruitment status), Consent Date, and Baseline CT neck/chest (CT Date, CT Results). Built-in features such as customized dropdown lists with predetermined values were designed to maintain data consistency and text fields were used for detail explanations of scenario encountered. For patient confidentiality, the screening log was anonymous and without any patient identifiers. Screening logs were introduced, distributed, and explained to each Site Coordinator (SC) via Cisco WebEx teleconferencing tool, and were reviewed weekly by the CMT. Descriptive analysis was used for patient recruitment status. Results: From September 2010 to July 2012, six COOLS study sites (Vancouver, London, Toronto (Sunny Brook Hospital), Calgary, Halifax, Winnipeg) have been actively using the screening log. A total of 420 patients are screened with 167 (40%) were identified as ineligible according to the enrollment criteria, including anatomic site, the visibility of the margin of lesions, diagnosis, and tumor size. Among 253 eligible patients, 175 (69%) were consented, 59 (23%) refused to participate, and 19 (8%) are not approached. The main reasons for patient refusal were compliance for scheduled follow-up visits (29, 49%) and unwillingness to fill study forms (8, 14%). The main reasons for patients not been approached were history of not compliance from previous study participation (7, 37%) and scheduling conflict and failure in study referral (4, 21%). Eight consented patients failed to receive assigned treatment due to unavailability of the FV specialists. Issues are identified and communicated with PI and SC in a timely fashion for better solutions. Conclusions: The COOLS trial screening log is implemented to help monitor recruitment activity and quality of the subject screening. It is also a source to examine patient acceptance to the trial and new technology. The tool can be used as a communication channel to bridge a strong network between the CMT and SCs and to understand the strength and weakness of site referral and recruitment. Through early identification of recruitment issues, site-specific strategies can be developed and recruitment goal can be reached. (Supported by the Terry Fox Research Institute (2009-24) and the Canadian Cancer Society Research Institute (CCS-20336). Citation Format: Yi Ping Kelly Liu, Shane X. Duan, Alisa Kami, Sylvia F. Lam, Catherine F. Poh. Recruitment monitoring report of a pan-Canadian multicenter study, the COOLS Trial. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr A11.
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 | 0,013 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 ».