Bone Mineral Density Deficits in Survivors of Childhood Cancer: Long-term Follow-up Guidelines and Review of the Literature
Bibliographic record
Abstract
The development of curative therapy for most pediatric malignancies has produced a growing population of childhood cancer survivors who are at increased risk for a variety of health problems resulting from their cancer or its treatment. Because of the fact that many treatment-related sequelae may not become clinically apparent until the survivor attains maturity or begins to age, the ability of primary care providers to anticipate late effects of treatment is essential for providing timely interventions that prevent or correct these sequelae and their adverse effects on quality of life. Altered bone metabolism during treatment for childhood cancer may interfere with attainment of peak bone mass, potentially predisposing to premature onset of and more severe complications related to osteopenia and osteoporosis. Bone mineral deficits have been reported after treatment for a variety of pediatric malignancies and represent morbidity that can be reduced or prevented through lifestyle changes and attention to other common cancer-related sequelae such as hypogonadism. The Children's Oncology Group long-term follow-up guidelines for survivors of childhood, adolescent, and young adult cancers provide risk-based surveillance recommendations that are based on expert opinion and review of the scientific literature for potential late effects of pediatric cancer therapy including osteopenia. This review summarizes the existing literature that has defined characteristics of cancer survivors at risk for bone mineral deficits and contributed to the surveillance and counseling recommendations outlined in the Children's Oncology group long-term follow-up guidelines.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".