Long-term safety and efficacy of dimethyl fumarate for up to 13 years in patients with relapsing-remitting multiple sclerosis: Final ENDORSE study results
Bibliographic record
Abstract
Background: Dimethyl fumarate (DMF) demonstrated favorable benefit–risk in relapsing-remitting multiple sclerosis (RRMS) patients in phase-III DEFINE and CONFIRM trials, and ENDORSE extension. Objective: The main aim of this study is assessing DMF safety/efficacy up to 13 years in ENDORSE. Methods: Randomized patients received DMF 240 mg twice daily or placebo (PBO; Years 0–2), then DMF (Years 3–10; continuous DMF/DMF or PBO/DMF); maximum follow-up (combined studies), 13 years. Results: By January 2020, 1736 patients enrolled/dosed in ENDORSE (median follow-up 8.76 years (ENDORSE range: 0.04–10.98) in DEFINE/CONFIRM and ENDORSE); 52% treated in ENDORSE for ⩾6 years. Overall, 551 (32%) patients experienced serious adverse events (mostly multiple sclerosis (MS) relapse or fall; one progressive multifocal leukoencephalopathy); 243 (14%) discontinued treatment due to adverse events (4% gastrointestinal (GI) disorders). Rare opportunistic infections, malignancies, and serious herpes zoster occurred, irrespective of lymphocyte count. For DMF/DMF ( n = 501), overall annualized relapse rate (ARR) remained low (0.143 (95% confidence interval (CI), 0.120–0.169)), while for PBO/DMF ( n = 249), ARR decreased after initiating DMF and remained low throughout (ARR 0–2 years, 0.330 (95% CI, 0.266–0.408); overall ARR (ENDORSE, 0.151 (95% CI, 0.118–0.194)). Over 10 years, 72% DMF/DMF and 73% PBO/DMF had no 24-week confirmed disability worsening. Conclusion: Sustained DMF safety/efficacy was observed in patients followed up to 13 years, supporting DMF’s positive benefit/risk profile for long-term RRMS treatment.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".