Understanding the Symptoms and Concerns of Adolescents and Young Adults with Cancer in Alberta: A Comparative Cohort Study Using Patient-Reported Outcomes
Bibliographic record
Abstract
Purpose: Adolescents and young adults (AYAs) with cancer are in a unique situation due to their age and developmental stage in life and may have different symptoms and concerns than older patients. Patient-Reported Outcomes (PROs) questionnaires, routinely used in Alberta, can help identify the distinct needs of AYAs. We aimed to compare PROs data for AYAs and older adults (OAs) to better understand how the concerns of AYAs differ, which is key to providing individualized care and creating targeted programming and system-level change. Methods: Retrospective data were collected for two patient cohorts who completed at least one PROs questionnaire between October 1, 2019 and April 1, 2020. The AYA cohort was aged 18–39, and the OA cohort was aged 40 and older. Symptoms were compared using mean scores and multiple linear regression, and concerns were compared using counts and multivariate negative binomial regression. Results: AYAs had significantly higher mean scores on depression and anxiety, compared to OAs, and lower mean scores for most physical symptoms. They indicated significantly more concerns in the Emotional and Social/Family/Spiritual domains, and were over three times more likely to indicate Work/School as a concern. Conclusion: AYAs with cancer have distinct concerns that should be addressed to ensure comprehensive, quality cancer care for this population. PROs data are useful in identifying needs and facilitating evidence-based, data-driven change at all levels of the health care system.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".