Model analysis shows promising data for renal denervation's cost-effectiveness

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catheter-based renal denervation, blood pressure - 275.70 Kb
Symplicity renal denervation system Source: Medtronic

Catheter-based renal denervation (RDN), over a wide range of assumptions, is a cost-effective strategy for resistant hypertension and might result in lower cardiovascular morbidity and mortality, according to an assessment using a state-transition, or Markov, model. The study was published in the Sept. 18 edition of the Journal of the American College of Cardiology.

RDN affects 12 percent of hypertensive persons. In the Symplicity HTN-2 randomized controlled trial, catheter-based RDN lowered systolic blood pressure (BP) by 32 mm Hg from 178 mm Hg at baseline.

Benjamin P. Geisler, MD, MPH, of Wing Tech, and colleagues sought to develop a decision-analytic model to predict long-term cardiovascular consequences and to ultimately assess the cost-effectiveness based on the long-term clinical effectiveness of this novel treatment option compared with standard of care alone. Wing Tech of Freemont, Calif., provided consulting services for Medtronic Ardian to construct the health-economic model.

The researchers used a Markov model to predict the effect of RDN and standard of care on 10-year and lifetime probabilities of stroke, MI, all coronary heart disease, heart failure, end-stage renal disease and median survival with the Symplicity RDN system (Medtronic Ardian). They used the model to compare RDN plus the existing standard of care—three or more antihypertensive medications—to standard of care alone.  

The Markov model, which had a cycle length of one month and half-cycle correction, included 34 health states to represent clinical disease progression. The same model structure was used for the two competing strategies. The model operates by taking the reductions in systolic BP observed in the randomized controlled trial and applying associations, known from the published literature, between systolic BP and clinical events to estimate their number by type. The model follows a simulated cohort with hypertension but no prior cardiovascular events and tracks occurrence of stroke, MI, angina, heart failure, end-stage renal disease and death.

“Our model differs from other recently published decision-analytic hypertension models in some important respects,” the authors wrote. First, it includes ESRD as an additional endpoint for costs and life expectancy. Second, the model characterizes possible sequelae of CVD, including acute-phase and secondary events. Third, because the model uses the Framingham and other multivariate risk equations, differences in event probabilities between cohorts with different risk profiles can be modeled more accurately by explicitly taking into account relevant clinical input parameters, such as lipid levels or underlying comorbid conditions such as atrial fibrillation or cardiomegaly/ventricular hypertrophy.

Also, they adopted a societal perspective and estimated an incremental cost-effectiveness ratio in U.S. dollars per quality-adjusted life-year—both discounted at 3 percent per year.

For the clinical outcomes, Geisler et al found that RDN substantially reduced event probabilities (10-year/lifetime relative risks: stroke 0.70/0.83; MI 0.68/0.85; all coronary heart disease 0.78/0.90; heart failure 0.79/0.92; end-stage renal disease 0.72/0.81). The median survival was 18.4 years for RDN versus 17.1 years for standard of care.

Also, the cardiovascular endpoints decreased by 21 percent to 32 percent over 10 years and between 8 percent and 17 percent over lifetime.

For the cost-effectiveness outcomes, they found the discounted lifetime incremental cost-effectiveness ratio was $3,071 per quality-adjusted life-year. Findings were relatively insensitive to variations in input parameters except for systolic BP reduction, baseline systolic BP and effect duration. The 95 percent credible interval for incremental cost-effectiveness ratio was cost-saving to $31,460 per quality-adjusted life-year.

The authors listed several of the study’s limitations, including:

  • The model, by definition, represents cardiovascular disease using a limited number of health states and transitions that may not always reflect the full spectrum of possible pathways of disease progression.
  • The model assumptions are based on office-based systolic BP measurements, which may imply larger systolic BP reductions than would be implied by ambulatory measurements.
  • Subjects in the dataset were mostly Caucasian.
  • To facilitate implementation, they did not build into the