01 Adolescent and Young Adult Central Nervous System Tumour Survivors: Documentation of late-effects risks and screening recommendations in British Columbia, Canada
Bibliographic record
Abstract
Survivors of adolescent and young adult (AYA) central nervous system (CNS) neoplasms are at risk for late effects (LE) - treatment-related health problems occurring more than 5 years after therapy). Since, in Canada, AYA survivors are usually followed in the community, information must be conveyed to primary care providers to guide risk-based follow-up care. Objective: To assess documentation of LE risks and screening recommendations (SR) in medical records of AYA CNS tumor survivors treated with radiation therapy. Methods: The medical records of all patients diagnosed with a CNS neoplasm (benign or malignant) at ages 15-39 years, treated between 1985 and 2010 in the province of British Columbia, surviving >5 years and discharged to the community were assessed. Documentation of LE and SR were extracted, and analyzed descriptively. Results: Among 132 survivors (52% female), treated with radiation therapy (95% partial brain, 10% craniospinal, 8% partial spine, and 4% whole brain) and chemotherapy (17%), 19% of charts included no documentation of LE risks, 26% included only non-specific documentation, and 55% had minimal documentation (1 or 2 LE). Documentation of at least one specific LE increased from 24% in 1980-1989, to 54% in 1990-1999, to 86% in 2000 – 2010. Based on treatment information, all survivors were at high-risk for LE, such as radiation induced neoplasm, meningioma and cerebrovascular events. Yet, SR were documented in only 25% of charts. Conclusions: The documentation of LE risks and screening recommendations has been limited, highlighting the need to improve written communication with primary care providers.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".