Challenges to the measurement of health‐related quality of life in children receiving cancer therapy
Bibliographic record
Abstract
Measures of health-related quality of life (HRQL) assess those areas of a patient's functioning that are affected by their cancer and its therapy. Although HRQL measures are integrated frequently into studies of survivors of childhood cancer, their use in the assessment of children receiving therapy has been limited by several methodological challenges. These arise from issues specific to measuring HRQL in young children, who comprise a large proportion of the pediatric oncology population, and from issues associated with assessing HRQL during therapy, when the patient's health status is in constant flux. This study summarizes the commonly used HRQL measures, and examines factors that impact their broad application. These include the influence of developmental changes on the content and format of HRQL measures, the role of proxy assessors, the important characteristics of measurement tools used to assess patients receiving active therapy, and the issues related to the ideal timing of serial HRQL assessments in prospective trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".