Methadone rotation for cancer pain: an observational study
Bibliographic record
Abstract
CONTEXT: Methadone is a useful option in the treatment of cancer pain. Despite its advantages, methadone use is complicated due to high interindividual variability in pharmacokinetics. Various rotation methods from other opioids have been proposed in mostly Caucasian populations. OBJECTIVES: This study aims to describe our experience with opioid rotation to methadone for management of cancer pain in a predominantly Asian population. METHODS: A retrospective review of 52 inpatients initiated on methadone for cancer pain from June 2015 to June 2018 was conducted. Our institution protocol for methadone rotation involves either one of two methods ('Stop-and-go' or the Edmonton 3-day rotation) based on the morphine-equivalent daily dose (MEDD), using an equianalgesic ratio of 10:1 for MEDD <1000 mg. To account for incomplete cross-tolerance, we further reduce the calculated dose by 30%. RESULTS: The majority of patients had mixed nociceptive-neuropathic pain (83%) and the predominant reason for methadone rotation was ineffective analgesia with other opioids (75%). The median MEDD before rotation was 104 mg. Effective analgesia (defined as a decrease in numerical rating scale (NRS) of ≥1 or attainment of NRS ≤3) was achieved within 3 days after rotation in 89% of patients. Patients with an MEDD ≤100 mg/day required a greater degree of uptitration of methadone dose after rotation compared with those with an MEDD >100 mg/day. CONCLUSION: Rotation to methadone according to our protocol is effective in achieving adequate analgesia in most patients experiencing nociceptive-neuropathic pain. Our results also suggest that a fixed equianalgesic ratio of 10:1 may be adequate for patients at low-to-moderate MEDD <400 mg/day.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".