Overall Adverse Event Profile of Vadadustat versus Darbepoetin Alfa for the Treatment of Anemia Associated with Chronic Kidney Disease in Phase 3 Trials
Bibliographic record
Abstract
INTRODUCTION: Anemia frequently occurs in chronic kidney disease (CKD), is associated with poor quality of life and cardiovascular outcomes, and its treatment represents a considerable economic burden to the healthcare system. Although effective, the current standard of care for the treatment of anemia in chronic kidney disease patients with erythropoiesis-stimulating agents requires chronic/ongoing injections, making the treatment less accessible or desirable to patients not treated by in-center maintenance hemodialysis. Furthermore, safety concerns, including an increased risk of cardiovascular events and mortality, have emerged from their use in studies targeting hemoglobin concentrations in the normal or near-normal range. The orally active hypoxia-inducible factor prolyl hydroxylase inhibitor vadadustat may offer advantages over erythropoiesis-stimulating agents by correcting anemia via pathways activating endogenous erythropoietin production. METHODS: To comprehensively analyze the safety profile of vadadustat in patients with dialysis-dependent and non-dialysis-dependent CKD-related anemia, we pooled the safety populations from each of the four trials in the phase 3 clinical program (n = 7,373) and compared the risk of treatment-emergent adverse events (TEAEs) for each treatment arm. RESULTS: In patients randomized to vadadustat versus darbepoetin alfa, rates of TEAEs (88.9% vs. 89.3%), treatment-emergent serious adverse events (58.0% vs. 59.3%), and TEAEs leading to death (16.1% vs. 16.2%) were similar, as were rates of adverse events of special interest, including cardiovascular-, hepatic-, and neoplasm-related adverse events. DISCUSSION/CONCLUSION: Among patients with CKD-related anemia treated with vadadustat, we observed similar rates of adverse events relative to those treated with darbepoetin alfa.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".