Improvement in Clinical Outcomes in Treatment-Naive Relapsing-Remitting Multiple Sclerosis Patients Who Switched From Subcutaneous Interferon Beta-1a to Alemtuzumab (P7.270)
Bibliographic record
Abstract
OBJECTIVE: To examine the efficacy and safety of switching to alemtuzumab in patients who received subcutaneous interferon beta-1a (SC IFNB-1a) in the CARE-MS I core study. BACKGROUND: In the 2-year CARE-MS I core study (NCT00530348) of treatment-naive patients with active relapsing-remitting multiple sclerosis, alemtuzumab-treated patients experienced significantly reduced annualized relapse rate (ARR) compared with SC IFNB-1a-treated patients, with manageable tolerability and safety. DESIGN/METHODS: In the core study, SC IFNB-1a-treated patients received 44 μg 3 times/week. In the first 2 years of the extension study (NCT00930553), these patients received 2 annual alemtuzumab courses (12 mg intravenous). Disability was assessed quarterly with the Expanded Disability Status Scale (EDSS); relapses were assessed as needed. Efficacy outcomes were assessed by raters blinded to patients’ earlier treatment assignment. Endpoints that were evaluated included ARR, change in EDSS score, and 6-month sustained reduction in preexisting disability (SRD). RESULTS: The extension study enrolled 144 (83[percnt]) SC IFNB-1a-treated patients from CARE-MS I. Two years after switching to alemtuzumab, ARR decreased by 69[percnt] compared with the 2 years in CARE-MS I (0.39 vs 0.12). EDSS scores after 2 alemtuzumab courses were stable/improved in 73[percnt] of patients. After switching to alemtuzumab, an additional 17[percnt] of patients achieved 6-month SRD. The safety profile of alemtuzumab after switching was similar to findings from the core study. CONCLUSIONS: Switching from SC IFNB-1a to alemtuzumab improved clinical outcomes. The safety profile of alemtuzumab after switching was similar to that observed in the core study. These findings support the favorable benefit-risk profile of alemtuzumab in patients who received prior disease-modifying therapy. Study Supported by: Genzyme, a Sanofi company, and Bayer Healthcare Pharmaceuticals
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".