Central Adiposity and Visceral Fat in Long‐Term Survivors of Acute Lymphoblastic Leukemia in Childhood and Adolescence: Exploration of an Underappreciated Risk
Bibliographic record
Abstract
INTRODUCTION: Elevated visceral fat is associated with poor cardiovascular health but is not well characterized in survivors of childhood cancer. We examined central adiposity and associated risk factors in a pediatric acute lymphoblastic leukemia (ALL) survivorship cohort. METHODS: Visceral adipose tissue (VAT) mass and estimated waist circumference (WC) were extracted from dual energy x-ray absorptiometry (DXA) scans on 70 survivors of pediatric ALL >10 years from diagnosis. Waist-to-height ratios (WHtRs), a body shape index (ABSI), ABSI z scores, and descriptive statistics were calculated to examine central adiposity. We tested sensitivity/specificity of WHtR at established thresholds for identifying VAT ≥85th percentile (%le). RESULTS: VAT z scores were shifted positively relative to population norms with 25.7% ≥ 85th %le. Mean WHtR was 0.55 ± 0.06 with 82.9% above the "take action" threshold of 0.5. A WHtR ≥0.59 had a sensitivity of 90.2% (95% CI 82.0-98.4) and specificity of 68.4% (95% CI 47.5-89.3) for identifying individuals with VAT ≥85th %le. The mean ABSI z score was 1.88 ± 0.85; higher in women, in high risk ALL, and post-cranial radiation (p = 0.01-0.02). The ABSI z scores for 94.3% of survivors fell in the highest quintile of population values. CONCLUSION: Nearly the entire cohort of long-term survivors of pediatric ALL have an elevated WC relative to height, weight, and population norms, regardless of their body mass index (BMI) or visceral fat. This suggests that a broader screening approach, which considers waist indices, may be better able to detect those at increased cardiometabolic risk. Evaluation and confirmation in a larger prospective cohort is indicated.
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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 | 0.001 | 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".