Incidence and Predictors of Mental Health Outcomes Among Survivors of Adolescent and Young Adult Cancer: A Population-Based Study Using the IMPACT Cohort
Bibliographic record
Abstract
PURPOSE Risk and predictors of long-term mental health outcomes in survivors of adolescent and young adult (AYA) cancers are poorly characterized. Mental health is consequently neglected in long-term follow-up. METHODS We identified all AYA in Ontario, Canada age 15-21 years when diagnosed with one of six common cancers between 1992-2012 using a population-based database, and compared them with matched controls. Linkage to provincial healthcare data allowed analysis of rates of outpatient (family physician and psychiatrist) visits for psychiatric indications and time to severe psychiatric events (emergency room visit, hospitalization, and suicide). Demographic-, disease-, and treatment-related predictors of adverse outcomes, including treatment setting (adult v pediatric), were examined. RESULTS Among 2,208 survivors and 10,457 matched controls, 5-year survivors experienced higher rates of outpatient mental health visits than controls (671 visits per 1,000 person-years v 506; adjusted rate ratio [RR] 1.3; 95% CI, 1.1 to 1.5; P = .006). Risk of a severe psychiatric episode was also increased among survivors (adjusted hazard ratio [HR], 1.2; 95% CI, 1.1 to 1.4, P = .008). Risk of a psychotic disorder–associated severe event was doubled in survivors (HR, 2.0, 95% CI, 1.3 to 2.4; P = .007) although absolute risk remained low (15-year cumulative incidence 1.7%; 95% CI, 1.0 to 2.7). In multivariable analysis, survivors treated in adult centers experienced substantially higher outpatient visit rates compared with those treated in pediatric settings (RR 1.8; 95% CI, 1.0 to 3.1; P = .04). CONCLUSION Survivors of AYA cancer are at substantially increased risk of adverse mental health outcomes, with those treated in adult centers at particular risk. Although absolute incidence was low, survivors were at increased risk of psychotic disorder–associated severe events. Long-term mental health surveillance is warranted, as is research into effective interventions during or after cancer treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".