Hypothalamic-Pituitary and Other Endocrine Surveillance Among Childhood Cancer Survivors
Bibliographic record
Abstract
Endocrine disorders in survivors of childhood, adolescent, and young adult (CAYA) cancers are associated with substantial adverse physical and psychosocial effects. To improve appropriate and timely endocrine screening and referral to a specialist, the International Late Effects of Childhood Cancer Guideline Harmonization Group (IGHG) aims to develop evidence and expert consensus-based guidelines for healthcare providers that harmonize recommendations for surveillance of endocrine disorders in CAYA cancer survivors. Existing IGHG surveillance recommendations for premature ovarian insufficiency, gonadotoxicity in males, fertility preservation, and thyroid cancer are summarized. For hypothalamic-pituitary (HP) dysfunction, new surveillance recommendations were formulated by a guideline panel consisting of 42 interdisciplinary international experts. A systematic literature search was performed in MEDLINE (through PubMed) for clinically relevant questions concerning HP dysfunction. Literature was screened for eligibility. Recommendations were formulated by drawing conclusions from quality assessment of all evidence, considering the potential benefits of early detection and appropriate management. Healthcare providers should be aware that CAYA cancer survivors have an increased risk for endocrine disorders, including HP dysfunction. Regular surveillance with clinical history, anthropomorphic measures, physical examination, and laboratory measurements is recommended in at-risk survivors. When endocrine disorders are suspected, healthcare providers should proceed with timely referrals to specialized services. These international evidence-based recommendations for surveillance of endocrine disorders in CAYA cancer survivors inform healthcare providers and highlight the need for long-term endocrine follow-up care in subgroups of survivors and elucidate opportunities for further research.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".