Investigation of heterogeneity in the association between interferon beta and disability progression in multiple sclerosis: an observational study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: It was recently reported that there was no significant overall association between interferon beta exposure and disability progression in relapsing-remitting multiple sclerosis (RRMS) patients in an observational study from Canada. In the current study, the potential for heterogeneity in the association between exposure to interferon beta and disability progression across patients' baseline characteristics was investigated. METHODS: RRMS patients treated with interferon beta (n = 868) and two cohorts of untreated patients (829 contemporary and 959 historical controls) were included. The main outcome was time from interferon beta treatment eligibility (baseline) to a confirmed and sustained Expanded Disability Status Scale (EDSS) score 6 using a multivariable Cox model, with treatment as a time-varying predictor, testing interaction effects for five pre-specified baseline characteristics: sex, age, disease duration, EDSS and annualized relapse rate (ARR) based on the previous 2 years. RESULTS: Significant heterogeneity was found in the association of interferon beta exposure and disability progression only across ARR, and only when treated patients were compared with historical controls (P = 0.005 at a Bonferroni-adjusted alpha of 0.01). For patients with ARR>1, treatment-exposed time was associated with a hazard ratio of 0.38 (95%CI 0.20-0.75) for disability progression compared with the unexposed time. CONCLUSIONS: RRMS patients with more frequent relapses at baseline may be more likely to benefit from interferon beta treatment with respect to long-term disability progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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".