Cancer treatment-related neuropathic pain: proof of concept study with menthol—a TRPM8 agonist
Bibliographic record
Abstract
PURPOSE: Effective treatment of neuropathic pain without unacceptable side effects is challenging. Cancer sufferers increasingly live with long-term treatment-related neuropathic pain, resulting from chemotherapy-induced peripheral neuropathy (CIPN) or surgical scars. This proof-of-concept study aimed to determine whether preclinical evidence for TRPM8 ion channels in sensory neurons as a novel analgesic target could be translated to clinical benefit in patients with neuropathic pain, using the TRPM8 activator menthol. PATIENTS AND METHODS: Patients with problematic treatment-related neuropathic pain underwent a baseline assessment using validated questionnaires, psychophysical testing, and objective functional measures. The painful area was treated with topical 1 % menthol cream twice daily. Assessments were repeated at 4-6 weeks. The primary outcome was the change in Brief Pain Inventory total scores at 4-6 weeks. Secondary outcomes included changes in function, mood and skin sensation. RESULTS: Fifty-one patients (female/male, 32/19) were recruited with a median age of 61 (ranging from 20 to 89). The commonest aetiology was CIPN (35/51), followed by scar pain (10/51). Thirty-eight were evaluable on the primary outcome. Eighty-two per cent (31/38) had an improvement in total Brief Pain Inventory scores (median, 47 (interquartile range, 30 to 64) to 34 (6 to 59), P < 0.001). Improvements in mood (P = 0.0004), catastrophising (P = 0.001), walking ability (P = 0.008) and sensation (P < 0.01) were also observed. CONCLUSION: This proof-of-concept study indicates that topical menthol has potential as a novel analgesic therapy for cancer treatment-related neuropathic pain. Improvements in patient-rated measures are supported by changes in objective measures of physical function and sensation. Further systematic evaluation of efficacy is required.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".