Serial combination therapy: is immune modulation in multiple sclerosis enhanced by initial immune suppression?
Bibliographic record
Abstract
BACKGROUND: Although the concept that an initial course of immune-suppression facilitates subsequent immune-modulation (such as Th1 to Th2 deviation) is attractive for several autoimmune diseases, such a mechanism for serial-combination therapy has never been formally demonstrated. Recently, brief mitoxantrone induction-chemotherapy followed by immune-modulation with glatiramer acetate (GA) was significantly more effective at reducing multiple sclerosis disease activity than with GA alone. OBJECTIVE: To examine whether the benefit of initial immune suppression with mitoxantrone before GA treatment is associated with more efficient immune modulation. METHODS: IgG1/IgG4 GA-reactive antibody profiles, previously established as markers of GA-induced Th2 immune-deviation, were prospectively measured in vivo in patients treated with GA alone or with mitoxantrone induction therapy followed by GA. RESULTS: Significant and sustained increase in IgG4 antibodies (and the anticipated reversal of the IgG1/IgG4 ratio) was seen in patients treated with GA alone. Combination therapy resulted in lesser IgG4 induction (and no reversal of IgG1/IgG4 ratio). Thus, the enhanced efficacy of mitoxantrone-GA combination regimen was associated with decreased, rather than increased, efficiency of shifting the GA-reactive IgG1/IgG4 antibody profile. CONCLUSION: These results provide important insights into mechanisms of combination therapy and therapeutic strategies for autoimmune diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".