Long‐Term Safety and Efficacy of Repeat Treatments with <scp>DaxibotulinumtoxinA</scp> in Cervical Dystonia: Results from the <scp>ASPEN</scp> ‐Open‐Label Study
Bibliographic record
Abstract
BACKGROUND: DaxibotulinumtoxinA (DAXI), a novel botulinum neurotoxin (BoNT) formulation, was shown to be safe, effective, and long-lasting in the treatment of cervical dystonia (CD) over one treatment cycle in the phase 3, randomized, placebo-controlled ASPEN-1 trial. OBJECTIVES: To evaluate the safety, immunogenicity, and efficacy of repeat DAXI treatments for CD over 52 weeks in the phase 3, open-label ASPEN-OLS (NCT03617367). METHODS: Adults with moderate-to-severe CD (Toronto Western Spasmodic Torticollis Rating Scale [TWSTRS] score ≥20) initially received DAXI 125U or 250U based on treatment history and investigator judgment. Retreatment could be titrated (50U-75U) each cycle (maximum 300U) for up to four cycles over 52 weeks. Assessments were conducted at Week 4, 6, 12, and every 4 weeks until retreatment. RESULTS: In all, 357 subjects received ≥1 dose of DAXI; most subjects (68.9%) received 250U during Cycle 1. Subjects most commonly received three (47.3%) or two (26.6%) treatments over 52 weeks. The average dose increased with successive cycles (Cycle 2: 239U, Cycle 3: 256U, Cycle 4: 270U). Mean (SD) change in TWSTRS score from baseline increased from -15.4 (10.3) in Cycle 1 to -19.9 (13.6) in Cycle 4. Median duration of effect was 20.1 weeks (Cycle 1, 2). No trend was observed between exposure to DAXI and any safety signals or antibody events. The most frequently reported treatment-related adverse events per treatment were muscular weakness (4.9%), injection-site pain (4.2%), and dysphagia (3.9%). CONCLUSION: DAXI was safe and efficacious over repeated treatments in adults with CD. Adverse event rates were similar to or potentially lower compared with conventional BoNTs.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".