A Multicentre Open-Label Safety and Efficacy Study of Tetrodotoxin for Cancer Pain
Bibliographic record
Abstract
BACKGROUND: Cancer pain is highly prevalent, and existing treatments are often insufficient to provide adequate relief. OBJECTIVES: We assessed the long-term safety and efficacy of subcutaneous tetrodotoxin treatment in reducing the intensity of chronic cancer-related pain. METHODS: In this multicentre open-label longitudinal trial, 30 μg tetrodotoxin was administered subcutaneously twice daily for 4 days in a heterogeneous cohort of patients with persistent pain despite opioids and other analgesics. "Responder" was defined as a mean reduction of 30% or more in pain intensity from baseline; and "clinical responder" as some pain reduction, but less than 30%, plus agreement on the part of both the patient and the physician that a meaningful analgesic response to treatment had occurred. RESULTS: Of 45 patients who entered the longitudinal trial, 41 had sufficient data for analysis. Of all 45 patients, 21 (47%) met the criteria for "responder" [16 patients (36%)] or "clinical responder" [5 patients (11%)]. Onset of pain relief was typically cumulative over days, and after administration ended, the analgesic effect subsided over the course of a few weeks. No evidence of loss of analgesic effect was observed during subsequent treatments (2526 patient-days in total and a maximum of 400 days in 1 patient). One patient withdrew from the study because of adverse events. Toxicity was usually mild (82%) or moderate (13%), and remained so through subsequent treatment cycles, with no evidence of cumulative toxicity or tolerance. CONCLUSIONS: Long-term treatment with tetrodotoxin is associated with acceptable toxicity and, in a substantial minority of patients, resulted in a sustained analgesic effect. Further study of tetrodotoxin for moderate-to-severe cancer pain is warranted.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".