Health‐related quality of life in adult survivors of childhood Wilms tumor or neuroblastoma: A report from the childhood cancer survivor study
Bibliographic record
Abstract
BACKGROUND: Long-term survivors of Wilms tumor and neuroblastoma may experience significant late adverse effects from their disease and its therapy. Little is known, however, about the health-related quality of life experienced by these survivors. PROCEDURE: Health-related quality of life, measured by the 36-Item Short Form Health Survey (SF-36), was assessed from self-report in adult survivors of Wilms tumor (N = 654) and neuroblastoma (N = 432) who participated in the Childhood Cancer Survivor Study. RESULTS: More than 90% of the study population was 18-34 years old at interview, and 58% were females. There was no significant difference on any SF-36 subscale or summary scale between the two diagnostic groups. On average, survivors reported no decrement on the Physical Component Summary scale of the SF-36 when compared to population norms. However, both groups scored significantly below the population mean score (50) on the Mental Component Summary Scale of the SF-36 (Wilms tumor mean = 41.66, standard error = 2.19, P < 0.0001; neuroblastoma mean = 42.41, standard error = 2.23, P < 0.0001) reflecting decreased emotional health. Independent risk factors for lower scores on this scale included female gender, Native American race, unemployment, and household income below $20,000. CONCLUSIONS: Adult survivors of childhood Wilms tumor and neuroblastoma do not differ from population norms on most health-related quality of life (HRQL) measures. These data, however, indicate that the emotional well being of adult survivors may be compromised. Health care providers should be aware of the risk of adverse outcomes in emotional health even many years after treatment and cure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".