Experimental Studies of Potential Analgesics for the Treatment of Chemotherapy-Evoked Painful Peripheral Neuropathies
Bibliographic record
Abstract
OBJECTIVE: We investigated potential analgesics for chemotherapy-evoked neuropathic pain using rats treated with paclitaxel. DESIGN: Drugs were tested in a repeated dosing paradigm (four daily injections). Topiramate was tested with a long-term treatment paradigm (12 days). A literature search was performed to summarize prior data. MEASURES: Mechanical stimulation of the hind paw was used to assay antiallodynic and antihyperalgesic effects acutely and 24 hours after injection. RESULTS: Amitriptyline produced significant analgesia, but this was not apparent until after the second injection. Baclofen produced significant effects, but the response varied erratically. Mexiletine and NMED-126 (a mixed N- and T-type calcium channel blocker) produced consistent, significant analgesia when tested acutely, but the pain relief did not persist at 24 hours postinjection. Oxcarbazepine had no effect at any time. Tramadol produced consistent, near-complete analgesia when tested acutely, but the analgesia did not persist to 24 hours postinjection. Topiramate produced significant effects that were first evident after 6-8 days of dosing. CONCLUSIONS: The present data and data from the literature review suggest that there are several potential treatments for chemotherapy-evoked neuropathic pain. Nonsteroidal anti-inflammatory drugs have little or no efficacy. Opioids have an effect, but probably only with high doses. At least some antidepressants are analgesic in these conditions. Some, but clearly not all, anticonvulsants and sodium channel blockers have efficacy. Tramadol is a particularly promising candidate. Topiramate, acetyl-L-carnitine, carbamazepine, and venlafaxine may have protective or restorative effects. Clinical trials of these candidates are needed to advance the treatment of chemotherapy-evoked pain.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".