Barriers and Facilitators to Adolescent and Young Adult Cancer Trial Enrollment: NCORP Site Perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Although it is well documented that adolescents and young adults (AYAs) with cancer have low participation in cancer clinical trials (CCTs), the underlying reasons are not well understood. We used the National Cancer Institute Community Oncology Research Program (NCORP) network to identify barriers and facilitators to AYA CCT enrollment, and strategies to improve enrollment at community-based and minority and/or underserved sites. Methods: We performed one-on-one semistructured qualitative interviews with stakeholders (NCORP site principle investigators, NCORP administrators, physicians involved in enrollment, lead clinical research associates or clinical research nurses, nurse navigators, regulatory research associates, patient advocates) in the AYA CCT enrollment process. NCORP sites that included high and low AYA-enrolling affiliate sites and were diverse in geography and department representation (eg, pediatrics, medical oncology) were invited to participate. All interviews were recorded and transcribed. Themes related to barriers and facilitators and strategies to improve enrollment were identified. Results: We conducted 43 interviews across 10 NCORP sites. Eleven barriers and 13 facilitators to AYA enrollment were identified. Main barriers included perceived limited trial availability and eligibility, physician gatekeeping, lack of provider and research staff time, and financial constraints. Main facilitators and strategies to improve AYA enrollment included having a patient screening process, physician endorsement of trials, an "AYA champion" on site, and strong communication between medical and pediatric oncology. Conclusions: Stakeholders identified several opportunities to address barriers contributing to low AYA CCT enrollment at community-based and minority and/or underserved sites. Results of this study will inform development and implementation of targeted interventions to increase AYA CCT enrollment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it