Treatment options for patients with multiple sclerosis who have a suboptimal response to interferon‐<i>β</i> therapy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although the first-line disease-modifying therapies (DMTs) interferon beta and glatiramer acetate have a favourable benefit-to-risk profile, they are only partially effective for treating relapsing-remitting multiple sclerosis (RRMS). The optimization of treatment in patients who do not show a maximum response to first-line therapy is critical for achieving the best long-term outcomes. Treatment strategies for patients with a suboptimal response include switching to another first-line DMT or a second-line DMT. Natalizumab and fingolimod are approved for RRMS with high disease activity in the European Union and Canada. METHODS: A comprehensive literature search for articles published between 1990 and April 2012 was undertaken. RESULTS: This review discusses key clinical and safety data for fingolimod and natalizumab, particularly in the patient subgroups for whom these treatments are approved. Benefit-to-risk profiles, including first-dose cardiovascular effects associated with fingolimod and the risk of progressive multifocal encephalopathy with natalizumab, are discussed. CONCLUSION: A descriptive comparison of fingolimod and natalizumab is provided in the context of the decision-making process of how and when to switch patients who have a suboptimal response to first-line therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".