Safety and efficacy of daclizumab beta in patients with relapsing multiple sclerosis in a 5-year open-label study (EXTEND): final results following early termination
Bibliographic record
Abstract
BACKGROUND: EXTEND (NCT01797965), an open-label extension study, evaluated the safety and efficacy of daclizumab beta in participants with relapsing multiple sclerosis (MS) who had completed the randomized DECIDE study. METHODS: Eligible participants who received either daclizumab beta or interferon beta-1a in DECIDE received daclizumab beta 150 mg subcutaneously every 4 weeks for up to 5 years in EXTEND, followed by 24 weeks of post-dosing follow-up. Safety and tolerability were evaluated, as were clinical efficacy and magnetic resonance imaging (MRI). EXTEND was terminated ahead of schedule by the sponsors. RESULTS: = 1203) received at least one dose of daclizumab beta in EXTEND. In the DECIDE and EXTEND combined periods, the median number of doses of daclizumab beta was 53; median time on treatment was 196 weeks. By 24 September 2018, the end of the study, 110/1203 (9%) participants had completed the protocol-specified treatment period and 1101/1203 (92%) had experienced an adverse event (AE). The most commonly reported AEs were MS relapse, nasopharyngitis, and upper respiratory tract infection. Hepatic events (18%), cutaneous events (45%), and infections (62%) were common treatment-related AEs. The incidence of serious AEs was 29%, most commonly MS relapse and infections. The incidence of immune-mediated disorders was 2%; three of seven were encephalitis. Two of six deaths were considered treatment related. In participants who received continuous daclizumab beta throughout DECIDE and EXTEND, the treatment effects on clinical and MRI outcomes were maintained for up to 6 years. CONCLUSION: Results from the combined DECIDE-EXTEND study elucidate outcomes of longer-term treatment with daclizumab beta in the clinical trial setting and underscore the importance of pharmacovigilance with immunomodulatory therapies in the real-world setting.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".