Diroximel Fumarate Demonstrates an Improved Gastrointestinal Tolerability Profile Compared with Dimethyl Fumarate in Patients with Relapsing–Remitting Multiple Sclerosis: Results from the Randomized, Double-Blind, Phase III EVOLVE-MS-2 Study
Bibliographic record
Abstract
BACKGROUND: Diroximel fumarate (DRF) is a novel oral fumarate approved in the USA for relapsing forms of multiple sclerosis. DRF is converted to monomethyl fumarate, the pharmacologically active metabolite of dimethyl fumarate (DMF). DRF 462 mg and DMF 240 mg produce bioequivalent exposure of monomethyl fumarate and are therefore expected to have similar efficacy/safety profiles; the distinct chemical structure of DRF may contribute to its tolerability profile. OBJECTIVES: The objective of this study was to compare the gastrointestinal tolerability of DRF and DMF over 5 weeks in patients with relapsing-remitting multiple sclerosis. METHODS: EVOLVE-MS-2 was a phase III, randomized, double-blind, head-to-head, 5-week study evaluating the gastrointestinal tolerability of DRF 462 mg vs DMF 240 mg, administered twice daily in patients with relapsing-remitting multiple sclerosis, using two self-administered gastrointestinal symptom scales: Individual Gastrointestinal Symptom and Impact Scale (IGISIS) and Global Gastrointestinal Symptom and Impact Scale (GGISIS). The primary endpoint was the number of days with an IGISIS intensity score ≥ 2 relative to exposure. Other endpoints included the degree of gastrointestinal symptom severity measured by IGISIS/GGISIS and assessment of safety/tolerability. RESULTS: DRF-treated patients experienced a statistically significant reduction (46%) in the number of days with an IGISIS symptom intensity score ≥ 2 compared with DMF-treated patients (rate ratio [95% confidence interval]: 0.54 [0.39-0.75]; p = 0.0003). Lower rates of gastrointestinal adverse events (including diarrhea, nausea, vomiting, and abdominal pain) were observed with DRF than DMF (34.8% vs 49.0%). Fewer patients discontinued DRF than DMF because of adverse events (1.6% vs 5.6%) and gastrointestinal adverse events (0.8% vs 4.8%). CONCLUSIONS: DRF demonstrated an improved gastrointestinal tolerability profile compared with DMF, with less severe gastrointestinal events and fewer days of self-assessed gastrointestinal symptoms, fewer gastrointestinal adverse events, and lower discontinuation rates because of gastrointestinal adverse events. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov (NCT03093324).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".