Effects of Dimethyl Fumarate on Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: Pooled Analysis Phase 3 DEFINE and CONFIRM Studies
Bibliographic record
Abstract
Objective In the pivotal DEFINE and CONFIRM trials for dimethyl fumarate (DMF), patterns of brain volume changes were different, potentially due to low sample sizes and because MRIs were analyzed at two different reading centers. We evaluated effects of DMF on brain volume change in patients with multiple sclerosis (MS) through reanalysis of pooled images from DEFINE/CONFIRM trials in one reading center. Methods MRIs from DEFINE/CONFIRM at weeks 0, 24, 48, and 96 from patients randomized to twice-daily DMF or placebo (PBO) were reanalyzed at the Cleveland Clinic to measure brain parenchymal fraction (BPF). To account for pseudoatrophy, brain volume estimates were re-baselined to calculate changes for weeks 48–96. Results Across studies, 301 and 314 patients receiving DMF and PBO, respectively, had analyzable MRIs. In weeks 0–48, mean ± SE percentage change in BPF was −0.44 ± 0.04 vs. −0.34 ± 0.04% in DMF vs. PBO, respectively, whereas in weeks 48–96, mean ± SE percentage change in BPF was −0.27 ± 0.03 vs. −0.41 ± 0.04% in DMF vs. PBO, respectively. The mixed-effect model for repeated measures showed similar results: in weeks 48–96, estimated change (95% confidence interval) in BPF was −0.0021 (−0.0027, −0.0016) for DMF vs. −0.0033 (−0.0039, −0.0028) for PBO (35.9% reduction;p= 0.0025). Conclusions The lower rate of whole brain volume loss with DMF in this pooled BPF analysis in the second year vs. PBO is consistent with its effects on relapses, disability, and MRI lesions. Brain volume changes in the first year may be explained by pseudoatrophy effects also described in other MS clinical trials.
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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 | 0.029 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.022 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".