MRI Frequency and No Evidence of Disease Activity Status Among Patients with RRMS Receiving IFN β-1a SC tiw or IFN β-1a IM qw: Post Hoc Analyses of EVIDENCE (P6.190)
Bibliographic record
Abstract
Objective: Investigate how MRI frequency affects no evidence of disease activity (NEDA) status in patients receiving interferon beta-1a (IFN β-1a). Background: In EVIDENCE, patients with RRMS were randomized to IFN β-1a subcutaneously 3x/week (SC tiw; n=339) or intramuscularly weekly (IM qw; n=338) for 64 weeks on average. In the extension, IFN β-1a SC tiw patients continued their regimen; IFN β-1a IM qw patients switched to SC tiw or discontinued. Relapse/MRI outcomes favored IFN β-1a SC tiw. Methods: Patients underwent 6 monthly T2 and pre-/post-contrast T1 scans until Week (W) 24, and T2 scans at W48 and W72. NEDA at W24 indicated no relapses or EDSS progression (≥1-point increase, sustained 12 weeks) and no Gd+ or active T2 lesions at W24 only; NEDA up to W24 involved all monthly T2 scan results (plus W24 Gd+). NEDA* at W48/W72 included absence of clinical activity through W48/W72 and no active T2 lesions on W48/W72 scans; NEDA* up to those timepoints included all 7/8 T2 scans. Results: NEDA was achieved by more IFN β-1a SC tiw than IM qw patients at W24 (59.5[percnt] vs 41.2[percnt]; p<0.001) and up to W24 (43.1[percnt] vs 27.1[percnt]; p<0.001). NEDA* was achieved by more IFN β-1a SC tiw than IM qw patients at W48 (43.3[percnt] vs 31.5[percnt]; p=0.004) and up to W48 (33.2[percnt] vs 18.9[percnt]; p<0.001). Similar NEDA* results were seen at W72 (33.9[percnt] vs 18.7[percnt]; p<0.001) and up to W72 (26.4[percnt] vs 11.1[percnt]; p<0.001). Conclusions: More patients achieved NEDA using single versus multiple scans, indicating a notable relevance of MRI protocol in evaluating disease activity. More stringent NEDA that included more frequent MRIs continued to favor IFN β-1a SC tiw over IFN β-1a IM qw. Study supported by: EMD Serono, Inc., Rockland, MA, USA (a business of Merck KGaA, Darmstadt, Germany); Pfizer Inc, New York, NY, USA.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".