Evaluating the ability to detect change of health‐related quality of life in children with Hodgkin disease
Bibliographic record
Abstract
BACKGROUND: We evaluated 4 different health-related quality of life (HRQL) measures prospectively to determine their ability to detect change over time: the Health Utilities Index Mark 2 and Mark 3, the Pediatric Quality of Life Inventory (PedsQL) 4.0 Generic Core and Cancer Module, the EuroQol EQ-5D visual analogue scale (EuroQol), and the Lansky Play-Performance Scale. METHODS: Children with all stages of Hodgkin disease from 12 centers across Canada were asked to complete the 4 measures at 4 time points: 2 weeks after the first course of chemotherapy, on the third day of the second course of chemotherapy, during the third week of radiation, and 1 year after diagnosis. RESULTS: Fifty-one patients were enrolled in the study between May 1, 2002 and March 31, 2005. Two patients were excluded: 1 patient died shortly after the first time point and the other patient failed to complete any of the questionnaires. All measures showed a significant change between Time 1 and Time 4 (<0.05). When the change in child scores was analyzed between the time points using the child's self-reported change in HRQL, the PedsQL and the EuroQol showed significant change at all time points. CONCLUSIONS: All of the measures were able to detect change in a diverse group of children with Hodgkin disease. The PedsQL and the EuroQol appeared to be the most sensitive to change.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".