Intercontinental collaboration in clinical trials for children and adolescents with cancer—A systematic review by ACCELERATE
Bibliographic record
Abstract
BACKGROUND: Since pediatric cancer drug development is a global enterprise, we sought to provide an overview of the landscape of intercontinental clinical trials in pediatric oncology opened over the last decade. METHODS: ClinicalTrials.gov was systematically searched to identify all clinical therapeutic trials which opened between 2010 and 2020 and recruited pediatric patients (<18 years) with cancer. RESULTS: Over the last 10 years, 295 (8.7%) of 3383 therapeutic pediatric cancer trials were international and 182 (5.4%) were intercontinental. Most intercontinental trials were phase-1 or 2, with 25% late-phase, 65% were sponsored by industry, and North America was involved in 92%. Industry-sponsored proportionally more phase-1 trials than academia (41% vs. 25%); conversely, academia sponsored more phase-2 and late-phase trials (39% and 31% vs. 36% and 21%, respectively) (p = 0.020). North America-Europe collaboration was predominantly industry sponsored as opposed to North America-Oceania and Europe-Oceania collaboration, more frequently academic (p < 0.0001). Most late-phase trials (18/20, 90%) focusing on pediatric malignancies were conducted by academic sponsors and 10 of these were conducted by Children's Oncology Group (COG)/National Cancer Institute in the United States and Oceania. There was no significant increase over time of intercontinental trials and a trend for a reduction in academic trials. CONCLUSIONS: Despite the relative rarity of childhood malignancies, especially within molecular subtypes, only 5.4% of pediatric cancer trials were intercontinental. The number of intercontinental trials remains small, with no significant increase over the last decade. The ACCELERATE International Collaboration Working Group aims to identify existing hurdles and propose solutions to improve intercontinental collaboration in clinical research for the benefit of children and adolescents with cancer.
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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 | 0.058 | 0.194 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".