Prospective Study of Use of Edmonton Symptom Assessment Scale Versus Routine Symptom Management During Weekly Radiation Treatment Visits
Bibliographic record
Abstract
PURPOSE: During radiotherapy (RT), patient symptoms are evaluated and managed weekly during physician on-treatment visits (OTVs). The Edmonton Symptom Assessment Scale (ESAS) is a 9-symptom validated self-assessment tool for reporting common symptoms in patients with cancer. We hypothesized that implementation and physician review of ESAS during weekly OTVs may result in betterment of symptom severity during RT for certain modifiable domains. METHODS: As an institutional quality improvement project, patients were partitioned into 2 groups: (1) 85 patients completing weekly ESAS (preintervention) but blinded to their providers who gave routine symptom management and (2) 170 completing weekly ESAS (postintervention group) reviewed by providers during weekly OTVs with possible intervention. To determine the independent association with symptom severity of the intervention, multivariate logistic regression was performed. At study conclusion, provider assessments of ESAS utility were also collected. RESULTS: Compared with the preintervention group, stable or improved symptom severity was seen in the postintervention group for pain (70.7% v 85.6%; P = .005) and anxiety (79.3% v 92.9%; P = .002). The postintervention group had decreased association (on multivariate analysis) with worsening severity of pain (OR, 0.13; P < .001), nausea (OR, 0.25; P = .023), loss of appetite (OR, 0.30; P = .024), and anxiety (OR, 0.19; P = .005). Most physicians (87.5%) and nurses (75%) found ESAS review useful in symptom management. CONCLUSION: Incorporation of ESAS for OTVs was associated with stable or improved symptom severity where therapeutic intervention is more readily available, such as counseling, pain medication, anti-emetics, appetite stimulants, and anti-anxiolytics. The incorporation of validated patient-reported symptom-scoring tools may improve provider management.
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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 | 0.000 | 0.000 |
| 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".