Long-term efficacy and safety of alemtuzumab in patients with RRMS: 12-year follow-up of CAMMS223
Bibliographic record
Abstract
BACKGROUND: In the phase 2 CAMMS223 trial (NCT00050778), alemtuzumab significantly improved clinical and MRI outcomes versus subcutaneous interferon beta-1a over 3 years in treatment-naive patients with relapsing-remitting MS. Here, we assess efficacy and safety of alemtuzumab over 12 years in CAMMS223 patients who enrolled in the CAMMS03409 extension (NCT00930553), with available follow-up through the subsequent TOPAZ extension (NCT02255656). METHODS: In CAMMS223, patients received 2 alemtuzumab courses (12 mg/day; baseline: 5 days; 12 months later: 3 days); 22% received a third course. In the open-label, nonrandomized extensions, patients could receive as-needed additional alemtuzumab or other disease-modifying therapies. RESULTS: Of 108 alemtuzumab-treated patients in CAMMS223, 60 entered the CAMMS03409 extension; 33% received a total of 2 alemtuzumab courses, and 73% received no more than 3 courses through Year 12. Over 12 years, annualized relapse rate was 0.09, 71% of patients had stable or improved Expanded Disability Status Scale scores, and 69% were free of 6-month confirmed disability worsening. In Year 12, 73% of patients were free of MRI disease activity. Cumulatively throughout the extensions (Years 7-12), 34% of patients had no evidence of disease activity. Adverse event (AE) incidence declined through Year 12. Infusion-associated reactions peaked at first course and declined thereafter. Cumulative thyroid AE incidence was 50%; one immune thrombocytopenia event occurred, and there were no autoimmune nephropathy cases. CONCLUSIONS: Alemtuzumab efficacy was maintained over 12 years in CAMMS223 patients, with 73% receiving no more than three courses. The safety profile in this cohort was consistent with other alemtuzumab clinical trials.
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 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 | 0.000 | 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 | 0.000 |
| 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".