Symptom burden and performance status in a population‐based cohort of ambulatory cancer patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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) | 0.000 | 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 it