Effect of fingolimod on health-related quality of life in paediatric patients with multiple sclerosis: results from the phase 3 PARADIG<i>MS</i> Study
Bibliographic record
Abstract
Background In the PARADIG MS Study, fingolimod demonstrated superior efficacy versus interferon (IFN) β-1a and comparable overall incidence of adverse events but slightly higher rate of serious adverse events in patients with paediatric-onset multiple sclerosis (PoMS). Here, we report the health-related quality of life (HRQoL) outcomes from PARADIG MS . Methods Patients with PoMS (N=215; aged 10–<18 years) were randomised to once-daily oral fingolimod (N=107) or once-weekly intramuscular IFN β-1a (N=108). HRQoL outcomes were assessed using the 23-item Pediatric Quality of Life (PedsQL) scale that comprises Physical and Psychosocial Health Summary Scores (including Emotional, Social and School Functioning). A post hoc inferential analysis evaluated changes in self-reported or parent-reported PedsQL scores from baseline up to 2 years between treatment groups using an analysis of covariance model. Results Treatment with fingolimod showed improvements versus IFN β-1a on the PedsQL scale in both the self-reported and parent-reported Total Scale Scores (4.66 vs −1.16, p≤0.001 and 2.71 vs −1.02, p≤0.05, respectively). The proportion of patients achieving a clinically meaningful improvement in the PedsQL Total Scale Score was two times higher with fingolimod versus IFN β-1a per the self-reported scores (47.5% vs 24.2%, p=0.001), and fingolimod was favoured versus IFN β-1a per the parent-reported scores (37.8% vs 24.7%, p=non-significant). Group differences in self-reported Total Scale Scores in favour of fingolimod were most pronounced among patients who had ≥2 relapses in the year prior to study entry or who showed improving or stable Expanded Disability Status Scale scores during the study. Conclusion Fingolimod improved HRQoL compared with IFN β-1a in patients with PoMS as evidenced by the self-reported and parent-reported PedsQL scores.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".