Bibliographic record
Abstract
Bone morbidity in children with cancer, both during and after completion of therapy, is increasingly recognized as both a short term and a long term problem. This is especially so for those children who receive large cumulative doses of glucocorticoids for the treatment of acute lymphoblastic leukemia (ALL) or non-Hodgkin lymphoma (NHL). Sue Kaste identified the problems in definition, characterization and prospective monitoring of the two major skeletal toxicities of osteoporosis and osteonecrosis. The World Health Organization defines osteoporosis currently as a bone mineral density T-score of less than minus 2.5. This definition may not be appropriate for children in whom there is a paucity of standardization and normative data. There is also variability between the techniques for measuring bone mineral density. Similarly, the classification of osteonecrosis needs to be improved relevant to this population group. The relationship between a specific classification, subsequent outcome and when to intervene requires clarification. Inge Van der sluis reviewed the prevalence of bone mineral loss in children with a variety of malignant diseases. The determinants of bone mineral density and the risk factors for osteopenia associated with cancer in childhood were elucidated. The relationship between decreased physical activity, nutritional disorders of calcium and vitamin D deficiency and genetic factors or polymorphisms (e.g., the vitamin D receptor gene) were described. A controversial topic is the role of biphosphonates for the prevention or treatment of bone mineral density deficits in this patient population and concerns about the adverse effects of these drugs. Stephanie Atkinson reviewed the complex physiology and pathophysiology of bone metabolism and the use of biomarkers for the assessment of bone morbidity. The importance of vitamin D status was highlighted. Though vitamin D status may be normal or low, serum concentrations of the active hormone are often subnormal, perhaps reflecting a direct effect of tumor cells on vitamin D receptor number and mRNA. In many children with cancer, biomarkers of bone formation were observed to be suppressed, while markers of bone resorption were elevated. Insulin-like growth factor 1, which stimulates bone formation, may be suppressed indirectly, indicating a growth hormone insufficiency. Leptin may also play a role in bone remodeling as hyperleptinemia has been observed in association with acute lymphoblastic leukemia. Biomarkers may be useful early indicators of disturbances in bone metabolism secondary to the disease process, drug therapy or cranial radiation, but clinical application must await the availability of suitable assays in the hospital setting. An overview of osteonecrosis, especially in ALL and NHL, was given by Ronald Barr (presenting for Alessandra Sala). A third of children may be affected, likely reflecting the cumulative exposure to glucocorticoid therapy. The pathogenesis is complex and includes suppression of bone formation, expansion of the intra-medullary lipocyte compartment, and a direct effect on nutrient arteries. Risk factors were described. The long term management, especially surgical options, is of concern in young growing children. The natural history of this disease is variable and hasty interventions are not always warranted. The pathogenesis of osteonecrosis in children with cancer who were treated with glucocorticoids may not be the same as in the disorder associated with other similar entities such as Perthes disease. These four presentations documented the considerable morbidity associated with osteoporosis and osteonecrosis. The current standard of care is that patients with ALL and NHL should be monitored prospectively for these two forms of bony morbidity. Comprehensive guidelines are required. We need to understand the natural history of these disorders and then evaluate interventions to decrease the attendant morbidities in the context of long term prospective studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".