Bibliographic record
Abstract
Purpose Effective treatment of neuropathic pain without un-acceptable side effects is challenging. Cancer sufferers in-creasingly live with long-term treatment-related neuropathic pain, resulting from chemotherapy-induced peripheral neu-ropathy (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 neuro-pathic 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. Sec-ondary 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 out-come. 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 mea-sures 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.261 | 0.161 |
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".