Combination Therapy for Pain Management in Inflammatory Arthritis: A Cochrane Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy and safety of combination pain therapy for people with inflammatory arthritis (IA). METHODS: Systematic review of randomized controlled trials using Cochrane Collaboration methodology. Combination therapy was defined as at least 2 drugs from the following classes: analgesics, nonsteroidal antiinflammatory drugs (NSAID), opioids, opioid-like drugs, and neuromodulators (antidepressants, anticonvulsants, and muscle relaxants). The main efficacy and safety outcomes were pain and withdrawals due to adverse events, respectively. RESULTS: Twenty-three trials (total of 912 patients) met inclusion criteria [22 in rheumatoid arthritis (RA) and 1 in a mixed population of RA and osteoarthritis]. All except 1 were published before 1990. All trials were at high risk of bias, and heterogeneity precluded metaanalysis. Statistically significant differences between treatment groups were reported in only 5/23 (22%) trials: in 3 trials combination therapy was better (2 trials with NSAID + analgesic versus NSAID only and 1 trial with 2 NSAID versus 1 NSAID), in 1 trial combination therapy was worse (opioid + neuromodulator versus opioid only), and in the fifth trial (NSAID + analgesic versus NSAID alone) reported results were mixed depending on the dosage used in the monotherapy arm. In general, there were no differences in safety and withdrawals due to inadequate analgesia between combination and monotherapy. CONCLUSION: Based on 23 trials, all at high risk of bias, there is insufficient evidence to establish the value of combination therapy over monotherapy for pain management in IA. Well-designed trials are needed to address this question.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 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".