Symptom burden and performance status in a population‐based cohort of ambulatory cancer patients
Bibliographic record
Abstract
BACKGROUND: For ambulatory cancer patients, Ontario has standardized symptom and performance status assessment population-wide, using the Edmonton Symptom Assessment System (ESAS) and Palliative Performance Scale (PPS). In a broad cross-section of cancer outpatients, the authors describe the ESAS and PPS scores and their relation to patient characteristics. METHODS: This is a descriptive study using administrative healthcare data. RESULTS: The cohort included 45,118 and 23,802 patients' first ESAS and PPS, respectively. Fatigue was most prevalent (75%), and nausea least prevalent (25%) in the cohort. More than half of patients reported pain or shortness of breath; about half of those reported moderate to severe scores. Seventy-eight percent had stable performance status scores. On multivariate analysis, worse ESAS outcomes were consistently seen for women, those with comorbidity, and those with shorter survivals from assessment. Lung cancer patients had the worst burden of symptoms. CONCLUSIONS: This is the first study to report ESAS and PPS scores in a large, geographically based cohort with a full scope of cancer diagnoses, including patients seen earlier in the cancer trajectory (ie, treated for cure). In this ambulatory cancer population, the high prevalence of numerous symptoms parallels those reported in palliative populations and represents a target for improved clinical care. Differences in outcomes for subgroups require further investigation. This research sets the groundwork for future research on patient and provider outcomes using linked administrative healthcare data.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".