Hypoalbuminemia and Nutritional Status in Children With Cancer
Bibliographic record
Abstract
BACKGROUND: In children with cancer, poor nutritional status adversely affects outcomes. Hypoalbuminemia is common in pediatric oncology patients, and in some groups is associated with inferior survival rates. We sought to determine if serum albumin associates with body mass index (BMI) percentile and if combining serum albumin and BMI is associated with survival. METHODS: We performed a single institution, retrospective review of pediatric oncology patients and collected data regarding baseline BMI, serum albumin, and survival outcome. Combining baseline BMI and serum albumin, we classified patients' nutritional status as adequately nourished, mildly/moderately depleted, and severely depleted. RESULTS: In a cohort of 490 pediatric oncology patients, hypoalbuminemia prevalence was 49%. Serum albumin did not associate with BMI percentile for age. Overall, those defined as severely depleted had an increased risk of relapse or death at 3 and 6 months from chemotherapy initiation compared with those defined as adequately nourished (hazard ratio [HR] = 2.37, 95% CI 1.29-4.37 at 3 months, p = 0.006; HR = 1.77, CI 1.11-2.82 at 6 months, p = 0.017). Statistical analyses suggest the inferior survival in those deemed severely depleted was primarily driven by hypoalbuminemia rather than BMI. CONCLUSIONS: In this cohort of pediatric oncology patients, serum albumin did not correlate with BMI. Severe hypoalbuminemia is an adverse prognostic factor. Baseline BMI had a minimal impact on relapse-free survival and overall survival, independently or in combination with hypoalbuminemia.
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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 | 0.003 |
| 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) | 0.001 | 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".