Comparative study evaluating the efficacy of duloxetine, gabapentin, and lacosamide on oxaliplatin-induced peripheral neuropathy
Bibliographic record
Abstract
Introduction: Peripheral neuropathic pain limits oxaliplatin use and negatively impacts patients' quality of life. Objectives: This study was conducted to assess the impact of gabapentin and lacosamide on oxaliplatin-induced peripheral neuropathy compared with duloxetine. Methods: In this randomized, double-blind study, 93 patients receiving oxaliplatin-based chemotherapy (FOLFOX-4 regimen: folinic acid, fluorouracil, and oxaliplatin) were assigned to 1 of 3 groups. Group 1 received duloxetine 30 mg/d, group 2 received gabapentin 300 mg/d, and group 3 received lacosamide 50 mg/d throughout 12 chemotherapy cycles. Neuropathy was assessed using the McGill Pain Questionnaire, 12-item neurotoxicity questionnaire (NTX-12), the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, and grading according to the Common Terminology Criteria for Adverse Events. Serum neuroinflammatory biomarkers, including nuclear factor kappa B, neurotensin, neurofilament light chain, and heme oxygenase-1, were also evaluated, along with adverse drug effects. Results: At cycles 10 and 12, the incidence of grade 2 to 3 neuropathy was significantly lower with duloxetine and lacosamide compared with gabapentin (45.2% and 32.2% vs 70.9%, P = 0.005; 51.6% and 38.8% vs 80.7%, P = 0.002), respectively. Patients receiving gabapentin showed lower 12-item neurotoxicity questionnaire scores at cycles 8, 10, and 12 (all P < 0.01), indicating greater neurotoxicity than duloxetine and lacosamide, as the scale is inversely scored. Consistently, serum levels of nuclear factor kappa B, neurotensin, and neurofilament light chain were reduced in the duloxetine and lacosamide groups relative to gabapentin. Conclusions: Lacosamide demonstrated neuroprotective efficacy comparable with duloxetine and may represent a promising therapeutic option for oxaliplatin-induced peripheral neuropathy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".