Bone health in long‐term survivors of pediatric acute lymphoblastic leukemia. An assessment by peripheral quantitative computed tomography
Bibliographic record
Abstract
BACKGROUND: Loss of bone mineral is a common concomitant of the treatment of acute lymphoblastic leukemia (ALL) due mainly to chemotherapy, especially with corticosteroids. Osteopenia/osteoporosis may be encountered long into survivorship. Measurement of bone mineral density (BMD) by dual-energy X-ray absorptiometry is limited to two-dimensionality and cannot distinguish trabecular from cortical bone. METHODS: A sample of 74 subjects, ages 13.5-38.3 years more than 10 years from diagnosis, underwent peripheral quantitative computed tomography (pQCT) at metaphyseal (trabecular bone) and diaphyseal (cortical bone) sites in the radius and tibia. pQCT provides three-dimensional assessment of bone geometry, density, and architecture. RESULTS: Average values in multiple metrics were similar to those in healthy individuals, but deficits in both trabecular and cortical bones were revealed by lower Z scores using an ethnically comparable sample of healthy individuals. Connectivity, a measure of bone architecture and a surrogate measure of bone strength, was lower in females than males. Survivors of standard-risk ALL had greater connectivity in and more compact trabecular bone than high-risk survivors who had received more intensive osteotoxic chemotherapy. There were no statistically significant differences in any of the metrics at any of the sites between subjects who had or had not a history of fracture, cranial irradiation, or use of a bisphosphonate. CONCLUSIONS: These long-term survivors of ALL have somewhat compromised bone health, but data in comparable healthy populations are limited. Longitudinal studies in larger and more ethnically diverse cohorts will provide greater insight into bone health in this vulnerable population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".