Long-term effects of fingolimod in multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: To assess long-term safety and efficacy of fingolimod in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: Patients completing FTY720 Research Evaluating Effects of Daily Oral Therapy in MS (FREEDOMS) were eligible for this dose-blinded, parallel-group extension study, continuing fingolimod 0.5 mg/day or 1.25 mg/day, or switching from placebo to either dose, randomized 1:1. Efficacy variables included annualized relapse rate (ARR), brain volume loss (BVL), and confirmed disability progression (CDP). Between-group analyses were conducted in the intent-to-treat (ITT) population from FREEDOMS baseline to end of study. Within-group analyses compared years 0-2 (FREEDOMS) and years 2-4 (extension) in the extension ITT population. RESULTS: Of 1,272 patients (FREEDOMS ITT population), 1,033 were eligible, and 920 enrolled in the extension study (continuous-fingolimod: 0.5 mg [n = 331], 1.25 mg [n = 289]; placebo-fingolimod: 0.5 mg [n = 155], 1.25 mg [n = 145]); 916 formed the extension ITT population (n = 330; n = 287; n = 154; n = 145) and 773 (84%) completed. In the continuous-fingolimod groups, ARR was lower (p < 0.0001), BVL was reduced (p < 0.05), and proportionately more patients were free from 3-month CDP (p < 0.05) than in a group comprising all placebo-fingolimod patients. Within each placebo-fingolimod group, ARR was lower (p < 0.001, both) and BVL was reduced after switching (p < 0.01, placebo-fingolimod 0.5 mg). Rates and types of adverse events were similar across groups; no new safety issues were reported. CONCLUSION: Efficacy benefits of fingolimod during FREEDOMS were sustained during the extension; ARR and BVL were reduced after switching. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that long-term fingolimod treatment is well-tolerated and reduces relapse rates, disability progression, and MRI effects in patients with RRMS.
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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 | 0.002 | 0.002 |
| 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".