Comparison of opioid rotation on pain, symptoms, and daily opioid dose in a supportive care clinic
Bibliographic record
Abstract
BACKGROUND: Opioid rotation (OR) is used to decrease patients' cancer-related pain and mitigate opioid-induced adverse effects. There is limited evidence regarding its effect on symptoms and morphine equivalent daily dose (MEDD). The objective of this study was to investigate the effects of OR on pain scores, Edmonton Symptom Assessment Score (ESAS), and MEDD in patients with cancer. METHODS: Retrospective observational study in an outpatient supportive care clinic using a within-subject design to analyze data collected over 34 months. Study included 676 patients with 217 rotations identified in 128 patients at supportive care clinic at a National Cancer Institute (NCI) Cancer Center. OR were identified and analysis compared the pre-visit data with the subsequent post-visit data following OR using paired t-tests. Primary endpoints included pain scores, total ESAS, and MEDD for OR and these endpoints were compared amongst rotations to specific opioid analgesics. RESULTS: Following OR, there was a statistically significant reduction in mean pain scores from 6.25 at the pre-visit to 5.75 following OR. Of the 194 ORs, 29.90% were successful in reducing patients' pain by either 30% or by 2-points. Only rotations to morphine, oxycodone, and methadone correlated with significant decreases in pain scores. Overall, OR did not correlate with significant changes in ESAS or MEDD. Only rotations to methadone correlated with a significant reduction in MEDD. CONCLUSIONS: These findings suggest OR is associated with decreased pain scores without increasing MEDD. Of the agents compared, only rotations to methadone correlated with both a significant reduction in pain scores and in MEDD.
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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 | 0.005 |
| 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) | 0.001 | 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".