Safety and Immunogenicity of Two Dosing Frequencies of Subcutaneous Interferon (scIFN) β-1a in Patients with a First Clinical Demyelinating Event (FCDE): 5-year Results of Phase III, Double-blind, Multicenter Trials (REFLEX/REFLEXION) (P7.211)
Bibliographic record
Abstract
OBJECTIVE:To determine the long-term safety and immunogenicity profile of scIFN β-1a in patients with an FCDE, up to 60 months after randomization. BACKGROUND:Early treatment with scIFN β-1a 44 µg three times weekly (tiw) or once weekly (qw) after an FCDE significantly delays clinically definite MS (CDMS) for up to 24 months with safety outcomes consistent with its well-characterized safety profile. DESIGN/METHODS:In REFLEX, patients were randomized to double-blind treatment with scIFN β-1a 44 µg tiw or qw, or placebo for 24 months (upon CDMS patients switched to open-label scIFN β-1a 44 µg tiw). In REFLEXION, placebo patients not reaching CDMS were switched to tiw (delayed treatment; DT); scIFN β-1a patients not reaching CDMS continued their initial regimen (qw or tiw) for up to 60 months after randomization. RESULTS:Safety population comprised 300 patients who received treatment during Months 24-60 (DT, n=84; qw, n=117; tiw, n=99). Approximately 83[percnt] of subjects had 蠅1 treatment-emergent adverse event (TEAE); treatment-related TEAEs were higher with DT (66.7[percnt]) than qw (53.8[percnt]) and tiw (43.4[percnt]).The incidence of TEAEs of both serious and severe intensity were similar across groups. The most common TEAEs were influenza-like illness (53.6[percnt], 33.3[percnt] and 17.2[percnt] for DT, qw and tiw, respectively), injection site erythema (20.2[percnt], 5.1[percnt], 8.1[percnt]) and headache (13.1[percnt], 16.2[percnt], 16.2[percnt]). Proportion of patients positive for neutralizing antibodies at the last observed value over the 60-month trial was lower for tiw versus qw (DT 11.2[percnt], qw 16.7[percnt], tiw 11.2[percnt]); for binding antibodies, the proportions were 20.1[percnt], 26.2[percnt] and 14.8[percnt], respectively. CONCLUSIONS:Over 5 years, scIFN β-1a was generally well tolerated, with outcomes consistent with its well-characterized safety profile. A higher incidence of treatment-related TEAEs may be expected among patients who have recently initiated active treatment compared to those who have previously been receiving active treatment. Study Supported by:Merck Serono.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".