Guidelines for Identification of, Advocacy for, and Intervention in Neurocognitive Problems in Survivors of Childhood Cancer
Bibliographic record
Abstract
With modern therapies and supportive care, survival of childhood cancer has increased considerably. Patients who have survived cancers involving the central nervous system or who have received therapy toxic to the developing brain are at risk of long-term neurocognitive sequelae. Negative outcomes are observed most frequently in survivors of acute lymphoblastic leukemia and brain tumors. The Children's Oncology Group Long-term Follow-up Guidelines Task Force on Neurocognitive/Behavioral Complications After Childhood Cancer has generated risk-based, exposure-related guidelines designed to direct the follow-up care of survivors of pediatric malignancies based on a comprehensive literature review and expert opinion. This article expands on these guidelines by reviewing the risk factors for the development of neurocognitive sequelae and describing the expected pattern of these disabilities. We herein present recommendations for the screening and management of neurocognitive late effects and outline important areas of school and legal advocacy for survivors with disabilities. Finally, we list resources that can guide patients, their parents, and their medical caregivers as they face the long-term neurocognitive consequences of cancer therapy.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".