Peginterferon β-1a every 2 weeks increased achievement of no evidence of disease activity over 4 years in the ADVANCE and ATTAIN studies in patients with relapsing–remitting multiple sclerosis
Bibliographic record
Abstract
Background: No evidence of disease activity (NEDA) is a composite measurement, incorporating clinical and magnetic resonance imaging (MRI) elements of disease activity to sensitively evaluate the therapeutic efficacy of treatments for relapsing–remitting multiple sclerosis (RRMS). Objective: To assess the NEDA status of patients treated with peginterferon β-1a in the ADVANCE and ATTAIN studies and explore its predictive value on longer-term clinical outcomes. Methods: ATTAIN was a 2-year extension of the pivotal 2-year ADVANCE study of peginterferon β-1a for RRMS. Achievement of clinical NEDA, MRI NEDA, or overall NEDA was calculated cumulatively and by year over 4 years. Clinical outcomes during ATTAIN were analyzed based on NEDA status at the end of ADVANCE. Results: Significantly more patients treated with peginterferon β-1a every 2 weeks than every 4 weeks achieved clinical NEDA (60.6% versus 50.6%, p = 0.0063) and MRI NEDA (28.3% versus 15.8%, p = 0.0005) through year 4 and overall NEDA through year 3 (20.9% versus 13.9%, p = 0.0160). Over 4 years, 15.8% of patients in the every 2 weeks group and 10.7% of patients in the every 4 weeks group maintained overall NEDA ( p = 0.0584). Achievement of clinical NEDA, MRI NEDA, or overall NEDA in ADVANCE was predictive of annualized relapse rate in ATTAIN; achievement of clinical NEDA in ADVANCE was also predictive of NEDA achievement and confirmed disability worsening in ATTAIN. Conclusions: Peginterferon β-1a every 2 weeks is associated with higher levels of NEDA compared with placebo in year 1 or peginterferon β-1a every 4 weeks in years 2–4. Overall NEDA within the first 2 years of treatment may be prognostic of long-term clinical outcomes. Clinicaltrials.gov: NCT01332019
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".