Health‐related quality of life in multiple sclerosis: effects of natalizumab
Bibliographic record
Abstract
OBJECTIVE: To report the relationship between disease activity and health-related quality of life (HRQoL) in relapsing multiple sclerosis, and the impact of natalizumab. METHODS: HRQoL data were available from 2,113 multiple sclerosis patients in natalizumab clinical studies. In the Natalizumab Safety and Efficacy in Relapsing Remitting Multiple Sclerosis (AFFIRM) study, patients received natalizumab 300 mg (n = 627) or placebo (n = 315); in the Safety and Efficacy of Natalizumab in Combination with Interferon Beta-1a in Patients with Relapsing Remitting Multiple Sclerosis (SENTINEL) study, patients received interferon beta-1a (IFN-beta-1a) plus natalizumab 300 mg (n = 589), or IFN-beta-1a plus placebo (n = 582). The Short Form-36 (SF-36) and a subject global assessment visual analog scale were administered at baseline and weeks 24, 52, and 104. Prespecified analyses included changes from baseline to week 104 in SF-36 and visual analog scale scores. Odds ratios for clinically meaningful improvement or worsening on the SF-36 Physical Component Summary (PCS) and Mental Component Summary were calculated. RESULTS: Mean baseline SF-36 scores were significantly less than the general US population and correlated with Expanded Disability Status Scale scores, sustained disability progression, relapse number, and increased volume of brain magnetic resonance imaging lesions. Natalizumab significantly improved SF-36 PCS and Mental Component Summary scores at week 104 in AFFIRM. PCS changes were significantly improved by week 24 and at all subsequent time points. Natalizumab-treated patients in both studies were more likely to experience clinically important improvement and less likely to experience clinically important deterioration on the SF-36 PCS. The visual analog scale also showed significantly improved HRQoL with natalizumab. INTERPRETATION: HRQoL was impaired in relapsing multiple sclerosis patients, correlated with severity of disease as measured by neurological ratings or magnetic resonance imaging, and improved significantly with natalizumab.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".