Food habits during treatment of childhood cancer: a critical review
Bibliographic record
Abstract
Several factors can affect the nutritional status of children undergoing cancer therapy. The present review aims to describe children's food intake during cancer treatments and to explore the contributing determinants. It also assesses the nutritional educational interventions developed for this clientele. Scientific literature from January 1995 to January 2018 was searched through PubMed and MEDLINE using keywords related to childhood cancer and nutritional intake. Quantitative and qualitative studies were reviewed: forty-seven articles were selected: thirty-eight related to food intake and parental practices and nine related to nutritional interventions. Patients' intakes in energy, macronutrients and micronutrients were compared with those of healthy controls or with requirement standards. Generally, patients ate less energy and proteins than healthy children, but adhered similarly to national guidelines. There is a lack of consensus for standard nutrient requirement in this population and a need for more prospective evaluations. Qualitative studies provide an insight into the perceptions of children, parents and nurses on several determinants influencing eating behaviours, including the type of treatment and their side effects. Parental practices were found to be diverse. In general, savoury and salty foods were preferred to sweet foods. Finally, most interventional studies in childhood cancer have presented their protocol or assessed the feasibility of an intervention. Therefore, because of the variability of study designs and since only a few studies have presented results, their impact on the development of healthful eating habits remains unclear. A better understanding of children's nutritional intakes and eating behaviours during cancer treatment could guide future nutritional interventions.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".