Obesity in pediatric oncology
Bibliographic record
Abstract
Today's obesity pandemic began in the United States, spread to Western Europe and other developed regions, and is emerging in developing countries. Its influences on outcomes of childhood cancer are unknown. A recent Children's Oncology Group symposium considered epidemiology of obesity, pharmacology of chemotherapy and outcomes in obese adults with cancer, excess mortality in obese pediatric patients with acute myeloid leukemia (AML), and complications in obese survivors. The salient points are summarized herein. Body mass index (BMI) is the accepted index of weight for height and age. In the US, obesity prevalence (BMI > 95th centile) is increasing in all pediatric age groups and accelerating fastest among black and Hispanic adolescents. Pharmacologic investigations are few and limited: half-life, volume of distribution, and clearance in obese patients vary between drugs. Obese adults with solid tumors generally experience less toxicity, suggesting underdosing. For patients undergoing bone marrow transplantation, obese adults generally experience greater toxicity. In pediatric acute myeloblastic leukemia, obese patients have greater treatment-related mortality (TRM), similar toxicity and relapse rates, and inferior survival compared with patients who are not obese. An excess of female survivors of childhood leukemia who received cranial irradiation are obese. Ongoing treatment effects of childhood cancer may predispose to a sedentary lifestyle. These findings call for measures to prevent obesity, retrospective and prospective studies of chemotherapy pharmacology of analyzed according to BMI and outcomes, additional studies of the obesity impact on outcomes in pediatric cancer, and promotion of a healthy lifestyle among survivors.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".