Comprehensive health status and health-related quality of life of children at diagnosis of high-risk neuroblastoma: a multicentric pilot study
Bibliographic record
Abstract
BACKGROUND: Neuroblastomas account for 8-10 % of all cancer diagnoses among children. Most patients present with advanced, high-risk disease and 90 % are less than five years old. The burden of morbidity and mortality is high and is quantifiable by measures of health-related quality of life (HRQL). Measuring quality of life in under five-year-old children is a particular challenge that has been met with the development of the Health Utilities Pre-School (HuPS) instrument. Quality of life studies in children with cancer are scarce in low- and middle-income countries and are usually conducted at a single center, thus limiting any conclusions drawn. This pilot study aimed to assess the health-related quality of life of children at the time of diagnosis of high-risk neuroblastomas. METHOD: This prospective cross-sectional multicentric study assessed the quality of life of children with high-risk neuroblastoma. The Health Utilities Pre-School instrument was applied to under five-year-olds, and the related Health Utilities Index Mark 3 instrument to over five-year olds. MAIN RESULTS: Eleven patients participated in this study. There was a high burden of morbidity at diagnosis, often equating to severe disability, indicative of states of health with scores worse than being dead in two under five-year-old children. CONCLUSION: The results of the current study will help to set research priorities for subsequent investigations and provide a basis to improve supportive care for children with high-risk neuroblastoma.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".