Patient‐Reported Symptoms and Mental Health Event Risks in Adolescents and Young Adults With Cancer
Bibliographic record
Abstract
INTRODUCTION: Adolescents and young adults (AYA) with cancer are at risk of adverse mental health outcomes during and after treatment. Tools identifying AYA at the highest risk would guide screening and interventions. We determined whether self-reported symptoms following cancer diagnosis were associated with early and late severe mental health events (SMHEs). METHODS: Ontario AYA diagnosed with cancer aged 15-29 between 2010 and 2018 were identified and linked to healthcare databases, including one capturing self-reported Edmonton Symptom Assessment System (ESAS) scores at cancer-related visits. Scores for depression, anxiety, and poor well-being were categorized as not measured, mild, moderate, or severe. SMHEs were defined as mental health-related Emergency Department visits or hospitalizations. We determined the association of ESAS scores with subsequent early SMHEs (< 5 years). Among 5-year survivors, we determined the association between the maximum ESAS score within 1 year of cancer diagnosis and late SMHEs (occurring > 5 years from cancer diagnosis). RESULTS: Among 5435 AYA, symptom severity was associated with subsequent SMHE risk. AYA who reported severe versus mild anxiety were at > 3-fold higher risk of subsequent early SMHEs [adjusted hazard ratio (aHR) 3.6, 95th confidence interval (CI) 1.9-6.7; p < 0.001]. Among 3518 (64.7%) 5-year survivors, symptom severity predicted late SMHE. At 5 years postcancer diagnosis, those who reported severe versus mild depression within 1 year following cancer diagnosis were at 3-fold elevated risk (aHR 3.0, 95 CI 1.8-4.9; p < 0.0001). CONCLUSION: Systematic symptom screening early postcancer diagnosis identifies AYA at high risk of both early and late SMHEs who may benefit from targeted screening and interventions.
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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 | 0.000 | 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 | 0.000 |
| 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".