Comparative effectiveness of natalizumab on cognition in multiple sclerosis: A cohort study
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment occurs in 40%-70% of persons with multiple sclerosis (MS). OBJECTIVE: To examine the effectiveness of natalizumab compared with other disease-modifying treatments (DMTs) on improving cognition as measured by the Symbol Digit Modalities Test (SDMT). METHODS: Data were collected as part of Swedish nationwide phase IV surveillance studies (2007-2020). An increase in SDMT score by ⩾10% of the difference between maximum score possible (110) and the baseline value was defined as cognitive improvement. The likelihood of improvement was compared between natalizumab-treated individuals and individuals treated with other DMTs using mixed effect logistic regression. Trend in odds of improvement was investigated using slope analyses. RESULTS: We included 2100 persons with relapsing-remitting MS treated with natalizumab and 2622 persons treated with other DMTs. At 6 months, 45% reached improvement. The natalizumab group showed largest odds of improvement during follow-up (odds ratio: 2.3, 95% confidence interval (CI): 1.5-3.5). The odds of improvement increased by 7% (95% CI: 6-7) per month of natalizumab treatment. The equivalent estimate was 4% (95% CI: 2-5) for other monoclonal antibodies and nonsignificant for oral or platform therapies. CONCLUSION: Treatment with natalizumab or other monoclonal antibodies is associated with a significantly faster likelihood of cognitive improvement than platform or oral DMTs.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".