Individual opioids, and long- versus short-acting opioids, for chronic noncancer pain
Bibliographic record
Abstract
BACKGROUND: Opioids are frequently prescribed for the management of patients with chronic non-cancer pain (CNCP). Previous meta-analyses of efficacy and harms have combined treatment effects across all opioids; however, specific opioids, pharmacokinetic properties (ie, long acting vs short acting), or the type of formulation (ie, immediate vs extended release) may be a source of heterogeneity for pooled effects. METHODS: We will conduct a network meta-analysis (NMA) of randomized controlled trials evaluating opioids for CNCP. We will acquire eligible studies through systematic searches of EMBASE, MEDLINE, CINAHL, AMED, PsycINFO, and the Cochrane Central Registry of Controlled Trials (CENTRAL). Eligible studies will have randomly allocated adult CNCP patients to an oral or transdermal opioid versus another type of opioid (or formulation) or placebo, and follow patients for ≥ 4 weeks. We will collect outcome data for pain intensity, physical function, nausea, vomiting, and constipation. Pairs of reviewers will, independently and in duplicate, abstract data from eligible trials and assess risk of bias using a modified Cochrane tool. We will assess coherence of our networks through both a global test, and by comparing direct and indirect evidence for each comparison with node-splitting. RESULTS: Using a frequentist approach, we will conduct random effects multiple treatment meta-analysis to establish treatment effects of individual opioids for each outcome. The certainty of evidence for pooled treatment effects will be assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. We will categorize interventions from most to least effective based on the effect estimates obtained from NMAs and their associated certainty of evidence, as follows: superior to both placebo and alternatives; superior to placebo, but inferior to alternatives; and no better than placebo. CONCLUSION: This NMA will determine the relative effectiveness and adverse effects of individual opioids among patients with CNCP. Our results will help inform the appropriateness of assuming similar beneficial and adverse effects of varying opioid formulations. SYSTEMATIC REVIEW REGISTRATION: This systematic review is registered with Prospective Register of Systematic Reviews, an international prospective register of systematic reviews (registration no.: CRD42018110331), available at https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=110331.
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.
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 | 0.061 | 0.145 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.018 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".