The effectiveness of a provincial symptom assessment program in reaching adolescents and young adults with cancer: A population-based cohort study.
Bibliographic record
Abstract
12101 Background: Symptom control is prioritized by cancer patients and may improve overall survival. Several jurisdictions have thus launched population-wide initiatives to assess symptoms at regular intervals. In Ontario, Canada, for example, all cancer patients are screened using the Edmonton Symptom Assessment System (ESAS) at every outpatient visit. Few studies have examined symptom burdens in adolescents and young adults (AYA). Previous work suggests that AYA symptoms differ from those in older patients, and that general screening tools may not be appropriate. Despite this, whether current symptom screening initiatives reach AYA with cancer are unknown. We therefore determined 1) Whether AYA with cancer were participating in ESAS screening, and 2) Which AYA were at highest risk of not being screened. Methods: We identified all Ontario AYA diagnosed with cancer at age 15-29 years between 2010-2018 and treated in adult centers. Patients were linked to population-based databases to identify all cancer-related outpatient visits in the year following diagnosis and whether visits involved completion of an ESAS form. Each patient’s first year was divided into two-week periods. For each period, AYA were considered either “unscreened” if they had a cancer-related visit but no ESAS score, or “screened” if they had a cancer-related visit with at least one ESAS score. Periods without cancer-related visits were not considered, given no potential for ESAS screening during such periods. Covariates included age at diagnosis, sex, cancer type, neighbourhood income quintile, and institution type [regional cancer centre (RCC) vs. community]. Multivariable logistic regression models were implemented under a generalized estimating equations approach to account for individual-level correlation. Results: The final cohort included 5,435 AYA. Within any given two-week period, only 36-45% of AYA attending cancer-related outpatient visits were screened. In adjusted analyses, age and sex were not associated with being screened. However, AYA living in the lowest income quintile neighbourhood were less likely to be screened [odds ratio (OR) 0.86, 95th confidence interval (95CI) 0.77-0.97; p = 0.01] compared to those in the highest. Patients with hematologic malignancies were least likely to be screened (OR 0.77, 95CI 0.67-0.88; p < 0.001), as were AYA attending community centers (OR 0.48, 95CI 0.42-0.55; p < 0.001). Conclusions: Despite a population-wide symptom assessment program, only a minority of AYA are screened. Though patients with hematologic cancers suffer from particularly high symptom burdens, they were less likely to be screened. Interventions targeting AYA are required to increase uptake, particularly among those in disadvantaged neighborhoods or attending community hospitals. Studies of AYA-specific symptom assessment tools are also warranted.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".