Peginterferon beta-1a in multiple sclerosis: 2-year results from ADVANCE
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy and safety of subcutaneous peginterferon beta-1a over 2 years in patients with relapsing-remitting multiple sclerosis in the ADVANCE study. METHODS: Patients were randomized to placebo or 125 µg peginterferon beta-1a every 2 or 4 weeks. For Year 2 (Y2), patients originally randomized to placebo were re-randomized to peginterferon beta-1a every 2 weeks or every 4 weeks. Patients randomized to peginterferon beta-1a in Year 1 (Y1) remained on the same dosing regimen in Y2. RESULTS: Compared with Y1, annualized relapse rate (ARR) was further reduced in Y2 with every 2 week dosing (Y1: 0.230 [95% CI 0.183-0.291], Y2: 0.178 [0.136-0.233]) and maintained with every 4 week dosing (Y1: 0.286 [0.231-0.355], Y2: 0.291 [0.231-0.368]). Patients starting peginterferon beta-1a from Y1 displayed improved efficacy versus patients initially assigned placebo, with reductions in ARR (every 2 weeks: 37%, p<0.0001; every 4 weeks: 17%, p=0.0906), risk of relapse (every 2 weeks: 39%, p<0.0001; every 4 weeks: 19%, p=0.0465), 12-week disability progression (every 2 weeks: 33%, p=0.0257; every 4 weeks: 25%, p=0.0960), and 24-week disability progression (every 2 weeks: 41%, p=0.0137; every 4 weeks: 9%, p=0.6243). Over 2 years, greater reductions were observed with every 2 week versus every 4 week dosing for all endpoints and peginterferon beta-1a was well tolerated. CONCLUSIONS: Peginterferon beta-1a efficacy is maintained beyond 1 year, with greater effects observed with every 2 week versus every 4 week dosing, and a similar safety profile to Y1.Clinicaltrials.gov REGISTRATION NUMBER: NCT00906399.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".