Landscape of paediatric oncology clinical trials in Asia
Bibliographic record
Abstract
In this second paper of a Series on childhood cancer in Asia, we provide an overview on the Paediatric Oncology Clinical Trials in Asia. Asia with a population of 4.7 billion constitutes about 60% of the world's population. The continent accounts for about half of the global paediatric cancer burden. Many Asian countries have consequently formed national professional societies in childhood cancer. Multicentre clinical trials are pivotal in advancing survival outcomes in paediatric oncology. The continent's diverse socioeconomic conditions may account for significant disparities in the development of such trials. However some countries with good financial resources are relatively deficient in developing clinical trials. In general, the countries show three distinct levels of clinical trials development: established, emerging and nascent. This article reports the landscape of multicentre clinical trials in Asia and the hurdles that clinicians face to actively engage in quality research and clinical trials. Although a ‘one-size-fits-all' approach is not feasible, the successful development of clinical trials systems in some countries can offer valuable lessons and insights for others. This is the second in a Series of three papers on childhood cancer in Asia (Paper 3 appears in The Lancet Child and Adolescence Health).
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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 | 0.059 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".