Young Survivors at KSA: registry for standardised assessment of long-term and late-onset health events in survivors of childhood and adolescent cancer—a study protocol
Bibliographic record
Abstract
Introduction A high proportion of survivors of childhood and adolescent cancer experience chronic medical conditions — late effects. Most studies on late effects have a retrospective or questionnaire-based design, which leads to unavoidable limitations such as missing data or different severity coding and grading of late effects. We, therefore, need prospective data, including standardised severity coding and grading. ‘Young Survivors at KSA’ aims to close this gap by assessing frequency, severity, risk factors and longitudinal changes of late effects in childhood cancer survivors prospectively and in a standardised way. Methods and analysis Within the ‘Young Survivors at KSA’ registry, we collect data from regular follow-up visits in a comprehensive database prospectively and repeatedly from start of the study and retrospectively at most until January 2016. We classify and grade the severity of late effects according to the Common Terminology Criteria for Adverse Events version 4.0 modified by Hudson et al . The outcome variables correspond to results from risk-stratified organ examinations, performed according to the Children’s Oncology Group guidelines version 5.0 and the recommendations by the International Guideline Harmonization Group. We collect the exposure variables from the patients’ medical history, including detailed information on cancer diagnosis and treatment. We analyse the data in an exposure-driven and organ system-driven approach. We start recruitment with patients treated at the Kantonsspital Aarau, Switzerland. However, our design allows the inclusion of additional national centres later. Ethics and dissemination ‘Young Survivors at KSA’ is approved by the Ethikkommission Nordwest- und Zentralschweiz, reference number AO_2020–00012. The results of this study will be presented at scientific meetings, including meetings with childhood cancer survivors and published in peer-reviewed and if possible open access journals. New insights gained from the study will be used directly in clinical practice. Trial registration number ClinicalTrials.gov NCT04811794 ; https://clinicaltrials.gov/ct2/show/study/NCT04811794
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".