<p>Rational treatment of chemotherapy-induced peripheral neuropathy with capsaicin 8% patch: from pain relief towards disease modification</p>
Bibliographic record
Abstract
Purpose: Chemotherapy-induced peripheral neuropathy (CIPN) with associated chronic pain is a common and disabling condition. Current treatments for neuropathic pain in CIPN are largely ineffective, with unfavorable side-effects. The capsaicin 8% patch (capsaicin 179 mg patch) is approved for the treatment of neuropathic pain: a single topical cutaneous application can produce effective pain relief for up to 12 weeks. We assessed the therapeutic potential of capsaicin 8% patch in patients with painful CIPN, and its mechanism of action. Patients and methods: 16 patients with chronic painful CIPN (mean duration 2.5 years), in remission for cancer and not receiving chemotherapy, were treated with 30 min application of capsaicin 8% patch to the feet. Symptoms were monitored using the 11-point numerical pain rating scale (NPRS), and questionnaires. Investigations were performed at baseline and three months after patch application, including skin biopsies with a range of markers, and quantitative sensory testing (QST). Results: Patients reported significant reduction in spontaneous pain (mean NPRS: −1.27; 95% CI 0.2409 to 2.301; p =0.02), touch-evoked pain (−1.823; p =0.03) and cold-evoked pain (−1.456; p =0.03). Short-Form McGill questionnaire showed a reduction in neuropathic ( p =0.0007), continuous ( p =0.01) and overall pain ( p =0.004); Patient Global Impression of Change showed improvement ( p =0.001). Baseline skin biopsies showed loss of intra-epidermal nerve fibers (IENF), and also of sub-epidermal nerve fibers quantified by image analysis. Post-patch application skin biopsies showed a significant increase towards normalization of intra-epidermal and sub-epidermal nerve fibers (for IENF: structural marker PGP9.5, p =0.009; heat receptor TRPV1, p =0.027; regenerating nerve marker GAP43, p =0.04). Epidermal levels of Nerve Growth Factor (NGF), Neurotrophin-3 (NT-3), and Langerhans cells were also normalized. QST remained unchanged and there were no systemic side-effects, as in previous studies. Conclusion: Capsaicin 8% patch provides significant pain relief in CIPN, and may lead to regeneration and restoration of sensory nerve fibers ie, disease modification. Keywords: capsaicin, neuropathic pain, chemotherapy, skin biopsy
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".