2 Long-term safety and efficacy of zilucoplan in generalised myasthenia gravis: 120-week interim analysis of RAISE-XT
Bibliographic record
Abstract
a:2:{s:4:"lang";s:2:"en";s:7:"content";s:1534:" Background In this interim analysis of RAISE-XT (NCT04225871), an ongoing, Phase 3, open-label extension study, we evaluate the long-term safety and efficacy of zilucoplan, a macrocyclic peptide complement component 5 inhibitor, in patients with acetylcholine receptor autoantibody-positive generalised myasthenia gravis (gMG). Methods Adults with gMG who completed a qualifying double-blind study (NCT03315130/NCT04115293) self-administered daily subcutaneous zilucoplan 0.3mg/kg. Primary outcome: incidence of treatment-emergent adverse events (TEAEs). Change from baseline (CFB) to Week 120 in MG Activities of Daily Living (MG-ADL) score was analysed for pooled data from participants who received zilucoplan 0.3mg/kg or placebo in the qualifying studies. Results 200 patients enrolled in RAISE-XT. At data cut-off (11 November 2023), median (range) exposure to zilucoplan was 2.2 (0.1–5.6) years. TEAEs occurred in 194 (97.0%) patients; 81 (40.5%) experienced a serious TEAE. The most common TEAEs were COVID-19 (71 [35.5%]) and MG worsening (59 [29.5%]). Of 183 patients who received zilucoplan 0.3mg/kg or placebo in the qualifying study, 93 continued zilucoplan and 90 switched from placebo to zilucoplan. At Week 120, mean CFB in MG-ADL score in pooled zilucoplan 0.3mg/kg patients was –7.14 (standard error 0.44). Conclusions Zilucoplan demonstrated a favourable long-term safety profile with sustained efficacy up to Week 120. maria.leite{at}ndcn.ox.ac.uk ";}
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".