Is therapy-free remission a realistic goal with cladribine tablets in multiple sclerosis? New insights into the mechanism of action and clinical implications of immune reconstitution with cladribine tablets in MS therapy
Bibliographic record
Abstract
Oral cladribine is a highly effective pulsed selective immune reconstitution therapy (SIRT) that received approval for the treatment of relapsing multiple sclerosis (RMS) in 2017. The concept of SIRT is characterized by brief exposure to active substances with long-term effectiveness, repopulation of lymphocytes, and maintenance of immune competence. In consequence, cladribine tablets allow patients to enter a prolonged treatment-free period, which offers time windows for family planning and vaccinations. Long-term control of disease activity has been linked to the sustained reduction of memory B cells. Based on more than 17 years of follow-up, the favorable safety profile is characterized by manageable front loading side effects and a low cumulative risk. Overall, therapy with cladribine tablets is associated with a low monitoring burden and leads to high treatment satisfaction. Meanwhile, 15 years after primary results from the pivotal trial were published, a vast amount of new data has emerged, including central effects of cladribine tablets. This narrative review discusses existing and emerging efficacy and safety data for cladribine tablets in MS and links these learnings to different patient profiles encountered in clinical practice. These include young patients with newly diagnosed RMS, young patients with highly active disease, and older patients switching from anti-CD20 antibodies or spingosine-1-phosphate modulators.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".