Cost-effectiveness analysis of radiofrequency renal denervation for uncontrolled hypertension in Canada
Bibliographic record
Abstract
Catheter-based radiofrequency renal denervation (RF RDN) is an interventional treatment for uncontrolled hypertension. This analysis explored the therapy’s lifetime cost-effectiveness in a Canadian healthcare setting. A decision-analytic Markov model was used to project health events, costs, and quality-adjusted life years over a lifetime horizon. Seven primary health states were modeled, including hypertension alone, stroke, myocardial infarction (MI), other symptomatic coronary artery disease, heart failure (HF), end-stage renal disease (ESRD), and death. Multivariate risk equations and a meta-regression of hypertension trials informed transition probabilities. Contemporary clinical evidence from the SPYRAL HTN-ON MED trial informed the base case treatment effect (-4.9 mmHg change in office systolic blood pressure (oSBP) observed vs. sham control). Costs were sourced from published literature. A 1.5% discount rate was applied to costs and effects, and the resulting incremental cost-effectiveness ratio (ICER) was evaluated against a willingness-to-pay threshold of $50,000 per QALY gained. Extensive scenario and sensitivity analyses were performed. Over 10 years, RF RDN resulted in relative risk reduction in clinical events (0.80 for stroke, 0.88 for MI, and 0.72 for HF). Under the base case assumptions, RF RDN was found to add 0.51 (15.81 vs. 15.30) QALYs at an incremental cost of $6,031 ($73,971 vs. $67,040) over a lifetime, resulting in an ICER of $11,809 per QALY gained. Cost-effectiveness findings were found robust in sensitivity analyses, with the 95% confidence interval for the ICER based on 10,000 simulations ranging from $4,489 to $22,587 per QALY gained. Model projections suggest RF RDN, under assumed maintained treatment effect, is a cost-effective treatment strategy for uncontrolled hypertension in the Canadian healthcare system based on meaningful reductions in clinical events. Radiofrequency renal denervation (RF RDN) is an adjunctive treatment option for patients suffering from uncontrolled hypertension. The therapy is approved by Health Canada and globally by a wide range of regulators including the United States Food and Drug Administration. This analysis sought to assess the health-economic value of RF RDN in the Canadian setting. RF RDN demonstrated to be a high-value, cost-effective intervention in the Canadian healthcare setting across all scenarios explored.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".