Cost-effectiveness of finerenone therapy for patients with chronic kidney disease and type 2 diabetes in England & Wales: results of the FINE-CKD model
Bibliographic record
Abstract
OBJECTIVE: Chronic kidney disease (CKD) is the leading cause of kidney failure, end-stage kidney disease (ESKD), and cardiovascular (CV) events in patients with type 2 diabetes (T2D). The FIDELIO-DKD trial demonstrated that finerenone lowered the risk of renal and CV events in patients with CKD and T2D, regardless of cardiovascular disease history. This study evaluated the cost-effectiveness of finerenone added to background treatment (finerenone + BT) versus background treatment (BT) alone in patients with CKD and T2D from the perspective of the National Health Service in England and Wales. METHODS: A lifetime Markov model assessed the indicated usage of finerenone for the treatment of stage 3 or 4 CKD with albuminuria associated with T2D in adults, as per the relevant marketing authorization. The model structure considered kidney disease progression and CV risk, with health states encompassing patients' kidney disease stage and CV event profiles, using patient-level data from the FIDELIO-DKD trial. Model outcomes were life years, quality-adjusted life years (QALYs), per-patient costs, incremental costs, and incremental cost-effectiveness ratio (ICER). Sensitivity and scenario analysis were performed, including an analysis exploring the impact of real-world data which suggests more frequent sodium-glucose co-transporter-2 (SGLT2) inhibitor use in the United Kingdom since FIDELIO-DKD. RESULTS: Patients receiving finerenone experienced kidney and CV benefits, including reduced rates of nonfatal CV events and CV deaths, translating to improvements in survival and quality-adjusted life years (QALYs) of 6.11 and 5.97 per patient for finerenone + BT versus BT, respectively. Total discounted per-patient costs were £48,940 for finerenone + BT and £47,716 for BT alone, resulting in an incremental cost-effectiveness ratio of £8,808 per QALY gained for finerenone + BT versus BT. CONCLUSION: Sensitivity and scenario analyses, including more frequent SGLT2 inhibitor use consistent with real-world data, indicate a robust ICER that remains within the bounds of what is typically considered cost-effective.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".