Quality of life among survivors of adolescent and young adult cancer in Canada: A Young Adults With Cancer in Their Prime (YACPRIME) study
Bibliographic record
Abstract
BACKGROUND: The quality of life (QoL) among survivors of adolescent and young adult (AYA) cancer may be compromised compared with that in the general population. In this study, the authors: 1) assessed for differences in QoL among a national study of AYA cancer survivors compared with the Canadian population and 2) explored the factors associated with poorer QoL in AYA cancer survivors. METHODS: For the current research, data from the Young Adults With Cancer in Their Prime study were used. QoL was measured using physical and mental component scores from a 12-item short-form health status measure. A comparison group was derived from the Canadian Community Health Survey. RESULTS: AYAs (n = 195; 17.8% male; mean ± SD: 35.62 ± 6.89 years on study, 6.48 ± 5.73 years from treatment) were compared with a comparison sample (n = 665; 21.2% male). Among survivors, 31.8% reported poor physical health, and 49.7% reported poor mental health. Compared with the general population, AYAs had significantly lower physical health (F[1,818] = 52.80; P = .00) and mental health (F[1,818] = 83.54; P = .00), controlling for sex and age. Multivariable logistic regression analyses revealed that an annual income level <$40,000 (adjusted odds ratio [AOR], 8.32; 95% CI, 2.85-24.30), poor sleep quality (AOR, 1.19; 95% CI, 1.06-1.33), worse body image (AOR, 1.08; 95% CI, 1.02-1.14), and higher social support (AOR, 1.02; 95% CI, 1.00-1.05) were significantly associated with poor physical health. Poor sleep quality (AOR, 1.22; 95% CI, 1.08-1.38), body image (AOR, 1.06; 95% CI, 1.01-1.12), fear of cancer recurrence (AOR, 1.13; 95% CI, 1.06-1.21) were associated with poor mental health. CONCLUSIONS: The QoL of AYAs requires urgent attention. Sleep, body image, and social support may be important modifiable targets for intervention to improve their QoL.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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".