Frailty among childhood cancer survivors: A report from the Childhood Cancer Survivor Study (CCSS).
Bibliographic record
Abstract
10026 Background: Childhood cancer survivors are at increased risk for frailty, which is a loss of physiological capacity that is typically observed among older adults. Aims: Estimate the prevalence of frailty among survivors, and examine direct and indirect effects of treatment, lifestyle, and chronic disease factors on frailty. Methods: CCSS participants who were > 5-year survivors of childhood cancer, diagnosed between 1970-1999 at <21 years of age (n=10,899, 48% male), and siblings (n=2,097, 42% male) were included. Frailty was defined from self-reported data at mean ages of 37.6±9.4 and 42.9±9.8 years for survivors and siblings, respectively, as ≥3 of the following: low lean mass, exhaustion, low energy expenditure, slow walking, and weakness. Results: The prevalence of frailty among survivors was higher compared to siblings (5.8%, 95% CI: 5.4-6.3% vs. 1.9%, 95% CI 1.4-2.5%). Prevalence was highest in survivors of CNS tumors (9.5%, 5.2-13.8%), bone sarcomas (8.1%, 5.1-11.1%) and Hodgkin lymphoma (7.5%, 4.9-10.1%). In models adjusted for sex, age at assessment, and race/ethnicity, treatment exposures were associated with frailty (Table). After adjusting for the presence of chronic diseases and lifestyle factors, these associations were attenuated. Conclusions: The prevalence of frailty among survivors (6.0% at 38 years of age) was similar to the general population aged ≥65 years (9.0%). Radiation, platinum, amputation and thoracotomy increased risk for frailty. Findings suggest interventions to prevent, delay onset, or remediate chronic disease and/or promote healthy lifestyle are needed to preserve function in this population. [Table: see text]
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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 | 0.002 |
| Science and technology studies | 0.000 | 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".