The effectiveness of a provincial symptom assessment program in reaching adolescents and young adults with cancer: A population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: Symptom control is prioritized by cancer patients and may improve overall survival. Ontario, Canada thus offers all cancer patients screening using the Edmonton Symptom Assessment System (ESAS) at outpatient cancer-related visits. We determined whether this initiative reached adolescents and young adults (AYA) and factors associated with screening in this population. METHODS: We linked all Ontario AYA diagnosed with cancer 2010-2018 aged 15-29 years to population-based databases identifying outpatient visits and ESAS screening. For each 2-week period in the year post-diagnosis, AYA with cancer-related visits were categorized as "unscreened" (no ESAS score) versus "screened" (≥1 ESAS score). Demographic and disease-related covariates were examined. RESULTS: Among 5435 AYA, 4204 (77.4%) had ≥1 ESAS screen. Within any 2-week period, only 30%-44% of AYA attending cancer-related visits were screened. Patients with hematologic malignancies were least likely to be screened [odds ratio (OR) vs. breast cancer 0.77, 95% confidence interval (95% CI) 0.67-0.88; p < 0.001]. AYA in remote Northern or rural areas had equivalent or higher rates of ESAS screening compared to those in high-income urban areas. However, AYA living in the lowest income urban neighborhoods were less likely to be screened (OR 0.86, 95% CI 0.77-0.97; p = 0.01). CONCLUSIONS: Within a population-wide symptom assessment program, while AYA living in rural and remote areas had high rates of screening, than those in low-income urban areas were substantially less likely to be screened. Though patients with hematologic cancers suffer from particularly high symptom burdens, they were also less likely to be screened. Interventions targeting AYA are required to increase uptake.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".