Bibliographic record
Abstract
PURPOSE OF REVIEW: The treatment of multiple sclerosis (MS) is evolving beyond the current parenteral immunomodulators and early oral alternatives, offering physicians considerable choice of therapies. Although all agents are tested in similarly designed clinical studies, comparison of their outcomes is not possible except in carefully controlled head-to-head comparator studies. In this review, the current, recent, and most imminent therapies are discussed and an overall summary is presented along with a discussion of how they are perceived relative to the older or other recent agents. RECENT FINDINGS: The list of potentially effective agents for the treatment of MS may be exhaustive, but several have now completed their phase 3 trials and have received or imminently expect government approval. This review discusses these new agents in terms of their perceived mechanisms of action and their respective results, and attempts to position them among the currently approved and utilized agents for MS. SUMMARY: Although it is not yet possible to predict which treatment is best suited to a given patient, it is nevertheless important to have a perspective of the possible agents and their efficacy and safety, and a plan regarding how to use them in order to maximize benefit and minimize harm in controlling relapsing MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| 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 | 0.001 | 0.002 |
| 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".