Relapse rates and enhancing lesions in a phase II trial of natalizumab in multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Natalizumab, a humanized monoclonal IgG4 antibody, is an alpha4-integrin antagonist, which inhibits the migration of inflammatory cells into the central nervous system, a key pathogenic mechanism in multiple sclerosis (MS). In a six month, phase II clinical trial of patients with relapsing MS, natalizumab significantly reduced the formation of new gadolinium-enhanced (Gd+) lesions and the number of clinical relapses. OBJECTIVE: To investigate the relationship of historical relapse rate and new Gd + lesion number with subsequent MS disease activity and natalizumab treatment in the phase II study. METHODS: Patients who participated in the phase II study were stratified into subgroups according to: (i) the number of relapses in the two years prior to entry into the study: 2 relapses (n = 108), 3 relapses (n =57), and >3 relapses (n =48); (ii) the number of new Gd + lesions at baseline (Month 0): 0 (n = 129), 1-2 (n =50), and >2 (n =33). Relapses and new Gd + lesions during the treatment phase of the trial were determined and compared for each subgroup. RESULTS: Both the prestudy relapse rate and number of new Gd + lesions at baseline were related to the subsequent risk of a relapse; baseline number of Gd + lesions was related to the likelihood of subsequent new Gd + lesion formation. There was a lower proportion of subjects with an on-study relapse and fewer new Gd + lesions in all natalizumab-treated subgroups when compared with their placebo counterpart; the difference was most apparent in the subgroups of patients with >3 relapses in the two years prior to study entry and >2 new Gd -- lesions at Month 0. CONCLUSIONS: There was a lower proportion of subjects with an on-study relapse in natalizumab-treated patients, particularly in those with a more active disease at study entry. Larger ongoing phase III studies will allow more definitive investigation of these preliminary subgroup findings.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".