Health‐related quality of life among children with acute lymphoblastic leukemia
Bibliographic record
Abstract
BACKGROUND: The objective was to quantify the health-related quality of life (HRQL) of children treated for acute lymphoblastic leukemia (ALL) and identify specific disabilities for remediation. PROCEDURE: Two types of subjects were included: ALL patients 5 plus years old in a multi-center clinical trial and general population control groups. Patients were assessed during all four major phases of active treatment and approximately 2 years after treatment. Health status and HRQL were measured using HEALTH UTILITIES INDEX® (HUI®) Mark 2 (HUI2) and Mark 3 (HUI3). HRQL scores were used to calculate quality-adjusted life years (QALYs). Excess disability rates identified attributes for remediation. RESULTS: HUI assessments (n = 749) were collected during the five phases. Mean HRQL increased from induction through the post-treatment phase (P < 0.001). There were no significant demographic or treatment effects on HRQL, except for type of asparaginase during continuation therapy (P = 0.005 for HUI2 and P = 0.007 for HUI3). Differences in mean HRQL scores between patients and controls were important (P < 0.001) during the active treatment phases but not during the post-treatment phase. Relative to controls, patients lost approximately 0.2 QALYs during active treatment. Disability was evident in mobility/ambulation, emotion, self-care and pain, and declined over time. CONCLUSIONS: Patients with ALL experienced important but declining deficits in HRQL during active treatment phases: Equivalent to losing approximately 2 months of life in perfect health. HRQL within the 2-years post-treatment phase was similar to controls. The policy challenge is to develop new treatment protocols producing fewer disabilities in mobility/ambulation, emotion, self-care, and pain without compromising survival.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".