IL-6 inhibition with clazakizumab in patients receiving maintenance dialysis: a randomized phase 2b trial
Bibliographic record
Abstract
Abstract Inflammation mediated by interleukin-6 (IL-6) is strongly associated with cardiovascular risk. Here we evaluated clazakizumab, a monoclonal antibody targeting the IL-6 ligand, in a phase 2b dose-finding study. Adults with cardiovascular disease and/or diabetes receiving maintenance dialysis with high-sensitivity C-reactive protein (hs-CRP) ≥ 2 mg l −1 at baseline were randomized to receive clazakizumab (2.5 mg, 5 mg or 10 mg, n = 32 per dose group) or placebo ( n = 31) every 4 weeks. The primary endpoint was the change from baseline in hs-CRP to week 12, expressed as the geometric mean ratio. Clazakizumab treatment signficantly reduced serum hs-CRP concentrations at week 12 by 86%, 90% and 92% relative to placebo in patients randomized to 2.5 mg, 5 mg or 10 mg clazakizumab, respectively (all P < 0.0001), meeting the primary outcome. With regard to secondary endpoints, clazakizumab treatment reduced serum fibrinogen, amyloid A, secretory phospholipase A2, and lipoprotein(a) concentrations, as well as increased mean serum albumin concentrations at 12 weeks, relative to placebo. The proportion of patients who achieved hs-CRP < 2.0 mg l −1 was 79%, 82% and 79% in the 2.5 mg, 5 mg and 10 mg clazakizumab groups, respectively, compared with 0% of placebo-treated patients. With regard to safety, no cases of sustained grade 3 or 4 thrombocytopenia or neutropenia were observed. Serious infections were seen with similar frequency in the placebo, clazakizumab 2.5 mg and clazakizumab 5 mg groups, but were numerically more frequent in the clazakizumab 10 mg group. The results of this trial indicate that in patients receiving maintenance dialysis, clazakizumab reduced inflammatory biomarkers associated with cardiovascular events. ClinicalTrials.gov registration: NCT05485961 .
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".