Identifying and addressing a new barrier to community-based patients accessing cancer clinical trials
Bibliographic record
Abstract
Participation in clinical trials is a recommended component of cancer patient care, yet patient accrual is poor, especially in community-based hospitals, which account for up to 70% of beds in Ontario, Canada. Moreover, the lack of clinical trials at smaller centres adds a unique challenge to community-based oncologists who must look outside their centres for patient access to clinical trials. To address these challenges, the Clinical Trials Navigator program (CTN) is being piloted at a large community hospital and used to identify eligible clinical trials for patients outside of their treating centre.This current study compared physician and patient perceptions of clinical trial barriers and influencing factors in a community-based hospital setting. Through this work, we discovered a novel barrier to community-based patients entering clinical trials.Cancer patients and physicians were recruited to participate in online surveys related to barriers to clinical trial accrual and their use of the CTN. Participant survey responses were analyzed and compared.We found that physicians rated the CTN very likely to increase accrual to clinical trials. However, physicians had a significantly different attitude toward factors that most likely affected patient referral to a clinical trial outside of their primary treatment site: patient time and out of pocket cost. Physicians felt these were significant barriers, but patients did not. This discrepancy uncovers a critical barrier in improving clinical trials accrual, as physicians would be less likely to refer patients, even though an appropriate clinical trial was identified and the patient may be willing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.127 | 0.456 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.013 | 0.031 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".