Self and proxy‐reported health status and health‐related quality of life in survivors of childhood cancer in Uruguay
Bibliographic record
Abstract
BACKGROUND: The incidence of cancer in children in Uruguay is similar to that in industrialized societies but the survival rate is half as great. This study assesses another important measure of treatment effectiveness: the health-related quality of life (HRQL) of survivors. METHODS: All new patients diagnosed in a 3-year period were eligible if free of disease for at least 2 years after therapy and at least 7 years of age at the time of study. A sample of convenient subjects for comparison was obtained from schools and clinics for well children. During a 7-month period, Spanish language interviewer-administered questionnaires were used to collect Health Utilities Index data from survivors and the comparison group (self-reports), and from proxies (parents, physicians, and teachers). RESULTS: Of 113 eligible survivors, 95 (84%) participated together with 96 "control" subjects. Control subjects have a higher mean HRQL utility score than survivors (P < 0.001). The mean score for survivors of acute lymphoblastic leukemia (ALL): 0.72 (n = 49) is higher than the score for survivors of brain tumors: 0.60 (n = 20), as expected. Inter-rater agreement is highest between survivors and parents, and lowest between controls and physicians or teachers. CONCLUSIONS: The burden of morbidity in survivors of childhood cancer in Uruguay is considerable and greater than that in a comparative group of healthy children. Survivors of ALL have better HRQL than survivors of brain tumors, mirroring experience elsewhere. The level of inter-rater agreement is related to the degree of familiarity of the pair-members of respondents with each other.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".