Phase 2 Study of the Factor XI Antisense Inhibitor IONIS-FXIRx in Patients With ESRD
Bibliographic record
Abstract
Introduction Patients with end-stage renal disease (ESRD) requiring hemodialysis (HD) have an increased risk of thrombotic events and bleeding. Antisense reduction of factor XI (FXI) with IONIS-FXI Rx is a novel strategy that may safely reduce the risk of thrombotic events. Methods This multicenter study enrolled 49 patients receiving HD in 2 parts. First, 6 participants (pharmacokinetics [PK] cohort) received 1 open-label 300 mg dose of IONIS-FXI Rx both before and after HD. Subsequently, 43 participants were treated in a double-blind, randomized design with 200 mg or 300 mg IONIS-FXI Rx or placebo for 12 weeks. The PK, pharmacodynamics (PD), and adverse events of IONIS-FXI Rx were evaluated (ClinicalTrials.gov: NCT02553889). Results The PK of IONIS-FXI Rx was consistent with previous studies and similar whether injected before or after HD. No accumulation of IONIS-FXI Rx was observed after repeat administration. By day 85, mean levels of FXI activity fell 56.0% in the 200 mg group, 70.7% in the 300 mg group, and 3.9% in the placebo group compared with baseline. FXI antigen levels paralleled FXI activity. Dose-dependent prolongation of activated partial thromboplastin time (aPTT) was observed, with no changes in international normalized ratio (INR). IONIS-FXI Rx was not associated with drug-related serious adverse events. In the randomized phase of the study, major bleeding events occurred in 0 (0.0%; 200 mg), 1 (6.7%; 300 mg), and 1 (7.7%; placebo) patients and were not considered related to treatment. Conclusion IONIS-FXI Rx reduced FXI activity in patients with ESRD receiving HD. Further studies are needed to determine the benefit-risk profile of FXI as a therapeutic target for patients who require HD.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".