Emerging Therapies in Relapsing-Remitting Multiple Sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Disease modifying therapy (DMT) first became available for relapsing-remitting multiple sclerosis (RRMS) fifteen years ago with the development of the moderately effective injectable agents interferon (IFN)-beta and glatiramer acetate (GA). The subsequent licensure of mitoxantrone (MX) and natalizumab (NZ) has allowed for better control of refractory disease at the expense of potentially life-threatening side effects in a minority of patients. This dichotomy between DMT potency and safety also characterizes the next generation of DMTs. Five oral medications (fingolimod, cladribine, teriflunomide, laquinimod and fumarate) are at various stages of phase III trials and it is anticipated that at least some of these will be on the market within the next year. The development of oral agents would be a tremendous advance with respect to convenience and it is anticipated that this would dramatically increase the number of patients on therapy. In parallel with oral therapies, powerful immunosuppressive monoclonal antibodies (alemtuzumab, rituximab/ocrelizumab, daclizumab) are also being evaluated. Enthusiasm for the next generation of therapies is tempered by safety concerns. Serious and occasionally fatal complications have occurred with the emerging monoclonal therapies and rigorous patient selection will be required for these agents. Moreover, some of the oral DMTs that are most eagerly awaited by patients have also been associated with serious side-effects in the trials to date. It is unclear how oral agents will be incorporated into future treatment algorithms given the need to weigh the ease of oral administration against the relative inconvenience but long-term safety of current first-line injectable therapies.
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.
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 | 0.023 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it