Finerenone in CKD and Type 1 Diabetes
Bibliographic record
Abstract
Background: Type 1 diabetes (T1D) is predicted to affect nearly 15 million people by 2040, and ~30% of those will develop chronic kidney disease (CKD). Although innovation in therapies to treat CKD in type 2 diabetes (T2D) has advanced in recent years, the treatment of CKD in T1D remains an area of urgent unmet need due to high residual risk. The nonsteroidal mineralocorticoid receptor antagonist finerenone has demonstrated reductions in the risk of major clinical kidney and cardiovascular outcomes in patients with CKD and T2D. Reduction in urinary albumin-creatinine ratio (UACR) explained 84% of the benefit of finerenone on the risk of a composite kidney outcome. The FINE-ONE trial (NCT05901831) assesses the efficacy and safety of finerenone in patients with CKD and T1D and uses change in UACR as a bridging biomarker to translate evidence of the long-term kidney benefits of finerenone from T2D to T1D. Methods: FINE-ONE is a global, phase 3, double-blind trial evaluating finerenone in patients with CKD (UACR ≥200–<5000 mg/g; estimated glomerular filtration rate [eGFR] ≥25–<90 mL/min/1.73 m2), T1D, HbA1c <10%, and serum [K+] ≤4.8 mmol/L. Patients receiving stable renin-angiotensin system therapy were randomized 1:1 to finerenone (10 or 20 mg od) or placebo. The primary efficacy outcome was change in UACR from baseline over 6 months. Safety outcomes included the proportion of participants who experienced treatment-emergent adverse events and hyperkalemia. Results: FINE-ONE randomized 242 patients with CKD and T1D. At baseline, the mean (standard deviation [SD]) age of patients was 52 (14) years, and 65.3% were male. The median (Q1–Q3) UACR was 549 (299–1191) mg/g, and the mean (SD) eGFR was 59 (19) mL/min/1.73 m2. Mean (SD) serum [K+] at baseline was 4.6 (0.4) mmol/L, and mean diabetes duration was 32 years. As of 23 August 2025, all patients had completed the 6-month treatment period. The study close-out procedures and statistical analyses are ongoing. Efficacy and safety outcome results will be presented at ASN Kidney Week. Conclusion: The FINE-ONE trial analysis will provide vital evidence for the efficacy and safety of finerenone in patients with CKD and T1D, and may result in finerenone becoming the first regulatory approved treatment for CKD associated with T1D in 30 years. Funding: Commercial Support - Bayer AG
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".