A Qualitative Systematic Review of Head‐to‐Head Randomized Controlled Trials of Oral Analgesics in Neuropathic Pain
Bibliographic record
Abstract
BACKGROUND: Neuropathic pain (NP) encompasses many difficult-to-treat disorders. There are few head-to-head, comparative, randomized controlled trials (RCTs) of drugs for NP in different analgesic categories, or of different drugs within a category, despite many placebo-controlled RCTs for individual agents. Well-designed head-to-head comparative trials are an effective way to determine the relative efficacy and safety of a new drug. OBJECTIVE: To perform a systematic review of head-to-head RCTs of oral analgesics in NP. METHODS: A systematic review of RCTs involving NP patients was performed, of which head-to-head comparative trials were selected. Reference lists from published systematic reviews were searched. These studies were rated according to the Jadad scale for quality. RESULTS AND CONCLUSIONS: Twenty-seven such trials were identified. Seventeen were comparisons of different analgesics, and 10 were of different drugs within an analgesic class. Important information was obtained about the relative efficacy and safety of drugs in different categories and within a category. Some significant differences between active treatments were reported. Trial inadequacies were identified. More and improved head-to-head RCTs are needed to inform clinical choices.
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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 | 0.078 | 0.221 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".