Effects of Inhibitors of the Renin-Angiotensin System on the Efficacy of Interferon beta-1b: A post hoc Analysis of the BEYOND Study
Bibliographic record
Abstract
BACKGROUND: In experimental autoimmune encephalomyelitis, inhibition of the renin-angiotensin system with angiotensin receptor blockers (ARBs) or angiotensin-converting enzyme (ACE) inhibitors resulted in a significantly ameliorated disease course. We evaluated the effects of ARBs and ACE inhibitors on the efficacy of interferon beta-1b in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: In this post hoc analysis of the BEYOND (Betaferon Efficacy Yielding Outcomes of a New Dose) study, clinical and MRI end points were compared between patients treated with interferon beta-1b 250 or 500 µg and concomitant ARBs or ACE inhibitors and patients treated with interferon beta-1b 250 or 500 µg only (reference group). RESULTS: Patients in the ARB group (n = 22) tended to have a higher relapse rate (0.48 vs. 0.23, p = 0.051) and a higher number of new gadolinium-enhancing lesions (0.6 vs. 0.3, p = 0.057) than patients in the reference group. Patients in the ACE inhibitor group (n = 49) also tended to have a higher relapse rate (0.29 vs. 0.22, p = 0.357). No differences were observed for the other end points. CONCLUSION: In the BEYOND study cohort, a concomitant medication with ARBs or ACE inhibitors did not have a beneficial effect in patients with RRMS treated with interferon beta-1b. As patients appeared to have a higher relapse rate, our results warrant further investigation.
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 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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".