Designing and Validating a Comprehensive Patient-Reported Outcomes Measure for Ambulatory Cancer Settings: The Revised Edmonton Symptom Assessment System for Cancer
Bibliographic record
Abstract
PURPOSE Patient-reported outcomes (PROs) information has been routinely collected in Cancer Care Alberta (CCA) for years using the revised Edmonton Symptom Assessment System (ESAS-r) and Canadian Problem Checklist (CPC). There was interest in combining these into a more comprehensive single measure tailored to ambulatory cancer settings. The purpose of this study was to validate an expanded and redesigned ESAS-r called the ESAS-r Cancer. METHODS Stakeholder engagement, a review of the literature, and 2 years of CPC data collected in the cancer program informed the addition of six symptoms to the ESAS-r. To assess and validate the measure, 1,600 randomly sampled patients were mailed paper copies of the ESAS-r Cancer, ESAS-r, and a validated, comprehensive PRO measure called the Memorial System Assessment Scale-Short Form (MSAS-SF), which is often used with patients with cancer. Canonical Correlation Analysis and exploratory factor analyses were performed to assess concurrent and construct validity of the ESAS-r Cancer against ESAS-r, using MSAS-SF as the reference measure for comparison. Cronbach α was calculated to assess reliability. RESULTS Four hundred and sixty-one patients (29% response rate) completed all three questionnaires. ESAS-r Cancer showed higher numerical correlation than ESAS-r and accounted for more information included on MSAS-SF, explaining slightly more variance than ESAS-r (75.2% v 73.5%). The three-dimensional factor structure of ESAS-r Cancer outperformed the two-dimensional factor structure of ESAS-r. The reliability of ESAS-r Cancer was verified and found to be slightly higher than ESAS-r (Cronbach α = .903 v .884). CONCLUSION ESAS-r Cancer is now in use with patients throughout CCA. This valid and reliable PRO measure can be used by other cancer or specialized health care programs who wish to routinely assess common symptoms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".