Long-term Safety and Dosing of OnabotulinumtoxinA: A Prospective, Observational Study
Bibliographic record
Abstract
BACKGROUND: Although therapeutic treatments are intended to help alleviate symptoms associated with disease, safety must be carefully considered and monitored to confirm continued positive benefit/risk balance. The objective of MOBILITY was to study the long-term safety of onabotulinumtoxinA for treatment of various therapeutic indications. METHODS: A prospective, multicenter, observational, Phase IV Canadian study in patients treated with onabotulinumtoxinA for a therapeutic indication. Dosing was determined by the participating physician. Adverse events (AEs) were recorded throughout the study. RESULTS: Patients (n = 1372) with adult focal spasticity, blepharospasm, cerebral palsy, cervical dystonia, hemifacial spasm, hyperhidrosis, or "other" diagnoses were enrolled into the safety cohort. Eighty-three patients (6%) reported 209 AEs; 44 AEs in 24 patients (2%) were considered treatment-related AEs. Seventy-two serious AEs were reported by 38 patients (3%); 10 serious AEs in 5 patients (0.4%) were considered treatment related. Most commonly reported treatment-related AEs were muscular weakness (n = 7/44) and dysphagia (n = 6/44). CONCLUSIONS: In patients with follow-up for up to six treatments with onabotulinumtoxinA, treatment-related AEs were reported in <2% of the safety population over the course of nearly 5 years. Our findings from MOBILITY provide further evidence that onabotulinumtoxinA treatment is safe for long-term use across a variety of therapeutic indications.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".