Cross-sectional study assessing long-term safety of interferon-β-1b for relapsing-remitting MS
Bibliographic record
Abstract
OBJECTIVE: The 16-Year Long-Term Follow-Up (LTF) to the pivotal interferon-beta-1b (IFNbeta-1b) trial explored clinical, MRI, cognitive, and patient-reported outcomes. Here, we report the safety assessments. METHODS: In the pivotal study, 372 patients were randomized to placebo (n = 123), IFNbeta-1b 50 microg (n = 125), or IFNbeta-1b 250 microg (n = 124) subcutaneously every other day for up to 5 years. Sixteen years later, patients were asked to participate in this cross-sectional follow-up study. No particular therapy was stipulated during follow-up. Adverse events experienced since the pivotal trial were recorded. Neutralizing antibodies (NAbs) to IFNbeta-1b were measured using the myxovirus protein A induction assay. Statistical analyses were descriptive. RESULTS: In total, 88.2% of patients (328/372) were identified. Some centers achieved 100% ascertainment, obviating selection bias. Treatment-related adverse events (e.g., leukopenia and liver and thyroid dysfunction) reported by LTF participants were in keeping with those previously established. Based on a follow-up period that includes 2,000 patient-years of IFNbeta-1b treatment, no new adverse events were observed that were associated with long-term IFNbeta-1b exposure. By LTF, NAbs to IFNbeta-1b disappeared in the majority (76%) of NAb-positive patients. NAb status during the pivotal study appeared to have no impact on long-term clinical and MRI outcomes. There were more deaths among patients assigned to placebo in the pivotal study (20/109 [18.3%]) compared with patients who received IFNbeta-1b 50 microg (9/108 [8.3%]) or IFNbeta-1b 250 microg (6/111 [5.4%]). CONCLUSION: The results from the 16-Year Long-Term Follow-Up study support the long-term safety of interferon-beta-1b therapy in multiple sclerosis. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that patients with relapsing-remitting MS taking IFNbeta-1b 50 microg or 250 microg subcutaneously every other day for up to 5 years, with subsequent unspecified treatment, have fewer deaths after 16 years of follow-up than similar patients on placebo for up to 5 years, with subsequent unspecified treatment (risk difference 11.5%, 95% confidence interval 4-19).
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| 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".