Accrual of adolescents and young adults (AYA) into cancer clinical trials in Canada.
Bibliographic record
Abstract
e13598 Background: Historically, accrual rates of AYA (aged 16-39) to cancer clinical trials have been low. This is suggested to contribute to lesser improvements in their outcomes compared with older and younger populations. We sought to describe the impact of collaborative initiatives launched by the Canadian Cancer Trials Group (CCTG), NCTN and C17 to address this. Methods: All CCTG trials open to accrual from 01/01/2004 to 31/12/2022 were evaluated. Trials with eligibility criteria limited to age > 39, or for which CCTG did not have access to individual patient data on age, were excluded. Accrual rates were assessed by age (<30, 30-39, >40 yrs), cancer type, and compared with 2022 Canadian Cancer Society (CCS) prevalence data. Results: 379 studies were open to accrual. 21 trials were excluded as they had no patients aged 16-39 within their inclusion criteria. 2 trials were excluded as they were either COVID related or a trial sub-study. 230 trials were excluded owing to patient age data being unavailable to CCTG. 126 CCTG and NCTN led trials were included. They involved the following disease sites: brain (3), breast (13), GI (12), GU (11), gynecology (6), head & neck (3), hematology (10), lung (11), melanoma (4), sarcoma (2) novel investigational agents (45) and symptom control (6) – the latter two spanned multiple tumor types. Patients aged 16-18 were excluded from many trials limiting accrual opportunities in this subgroup. AYA patients were recruited into trials at a higher level than expected by prevalence data except for brain, lung and head & neck patients. This may be due to younger, fitter patients being recruited onto trials. GU trials, hematology and sarcoma trials recruited better than expected as there were trials geared to diseases common in younger individuals (e.g. germ cell cancers) and incorporating intensive therapy e.g. stem cell transplantation in lymphoma. 3.5% of patients accrued on trials were <40 in 2004-2013 c.f. 8.7% of patients 2014-2022. Conclusions: Limited data is available on AYA aged 16-18 due to trial entry criteria. Currently, most CCTG trials include patients aged ≥14. Trial accrual in the AYA population was higher than predicted by CCS data indicating that clinical trials are acceptable to AYA patients. This supports ongoing efforts to improve trial access to AYA. [Table: see text]
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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 | 0.073 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".