Tetrodotoxin (TTX) for Chemotherapy Induced Neuropathic Pain (CINP): A Randomized, Double-Blind, Dose-Finding, Placebo Controlled, Multicenter Study (S17.003)
Bibliographic record
Abstract
OBJECTIVE: A phase 2 randomized, double-blind, dose-finding, placebo controlled, multicenter trial is ongoing to evaluate TTX as a treatment for CINP. Here we report completed dose optimization results, the objective of which was to identify up to two dosing schemes for further study. BACKGROUND: Tetrodotoxin is a small molecule that blocks voltage-gated sodium channels involved in pain signaling. METHODS: Subjects with taxane or platinum induced CINP were randomized to one of five cohorts: placebo twice daily (b.i.d.), TTX 7.5 µg b.i.d., TTX 15 µg b.i.d., TTX 30 µg daily (q.d.) or TTX 30 µg b.i.d. TTX or placebo was injected subcutaneously for four consecutive days. The TTX 30 µg q.d. cohort also received a daily placebo to maintain blinding. The primary efficacy endpoint was assessed using the numerical pain rating scale. RESULTS: 125 patients (77 women) were randomized, with 125 in the intent to treat population and 107 in the per protocol population. The mean change from baseline pain score was greatest in the TTX 30 µg q.d. (-1.7 ± 2.3) and TTX 30 µg b.i.d. (-1.5 ± 1.8) cohorts for week 4 post-treatment, the primary endpoint. Analysis of ≥ 30[percnt] improvement in 10-day average pain scores at any time point demonstrated that the TTX 30 µg b.i.d. cohort had the largest number of responders (15/26; 57.7[percnt]) compared to placebo (8/25; 32.0[percnt]) (P = 0.027). Oral paresthesia was the most common AE (37/125; 29.6[percnt]), followed by oral hypesthesia (31/125; 24.8[percnt]). Most AE were grade 1 or 2. There were four grade 3 AE and no grade 4 AE. Three patients experienced SAE, two unrelated and one unlikely related to TTX. CONCLUSIONS: The TTX 30 µg b.i.d. regimen is well tolerated with promising early efficacy data to merit further study. Clinical development is ongoing. STUDY SUPPORTED BY: WEX Pharmaceuticals.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".