COVID-19 Infection in Fingolimod- or Siponimod-Treated Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: A descriptive analysis of COVID-19 infection in patients with multiple sclerosis (MS) receiving fingolimod or siponimod. METHODS: We reviewed the cases of COVID-19 from postmarketing or ongoing clinical trials reported to Novartis through December 27, 2020. RESULTS: As of December 27, 2020, 283 cases had been reported in fingolimod-treated patients. The mean age was 44 years (from n = 224; range 11-69 years), and 190 were women. Of 161 cases with available information, 138 were asymptomatic (6), mild (100), or moderate (32); 50 cases required hospitalization. At the last follow-up, 140 patients were reported as recovered/recovering, condition was unchanged in 22, and deteriorated in 3 patients; 4 patients had a fatal outcome. Information was not available for 114 patients. Of the 54 cases of COVID-19 reported in siponimod-treated patients, 45 were from the postmarketing setting and 9 from an ongoing open-label clinical trial. The mean age was 54 years (from n = 45; range 31-70), and 30 were women. Of 28 cases with available information, 24 were asymptomatic (2), mild (17), or moderate (5); 9 cases required hospitalization. At the last follow-up, 27 patients were reported as recovered/recovering, condition remained unchanged for 1, and 3 patients had a fatal outcome. Information was not available for 23 patients. DISCUSSION: Based on a review of available information, the risk of more severe COVID-19 in patients receiving fingolimod or siponimod seems to be similar to that reported in the general population and the MS population with COVID-19. However, limitations of spontaneous reporting, especially missing data, should be considered in the interpretation of these observations.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".