Cost-Effectiveness of a Microvolt T-Wave Alternans Screening Strategy for Implantable Cardioverter-Defibrillator Placement in the MADIT-II–Eligible Population
Paul S. Chan, MD, MSc*, ,*,
Kenneth Stein, MD ,
Theodore Chow, MD, FACC ,
Mark Fendrick, MD,
J. Thomas Bigger, MD|| and
Sandeep Vijan, MD, MSc*,
* VA Center for Practice Management and Outcomes Research, Ann Arbor, Michigan
University of Michigan, Ann Arbor, Michigan
Weill Medical Center, Cornell University, New York, New York
The Lindner Clinical Trial Center at the Christ Hospital and the Ohio Heart and Vascular Center, Cincinnati, Ohio
|| Columbia University Medical Center, New York, New York
View larger version (10K):
[in a new window]
|
Figure 1 Simplified schematic of Markov model. The square node at the far left symbolizes the choice between the three treatment strategies: implantable cardioverter-defibrillators (ICDs) for all, medical therapy, or risk stratification with microvolt T-wave alternans (MTWA) testing. Circles represent chance events, and M represents the Markov process with multiple health states (well, mildly disabled, moderately disabled, severely disabled) for each treatment option. Patients who survive ICD implantation or who are on medical therapy enter the Markov tree (denoted by two circles and arrow within a rectangle), which includes all potential clinical outcomes that occur with each cycle. Patients in the medical therapy arm are not subject to ICD complications and have no cardiac arrests prevented by defibrillator therapy. Patients in the MTWA risk stratification strategy enter the same pathway as those in the ICD-for-all strategy if they test MTWA non-negative and the medical therapy strategy if they test MTWA negative.
|
|
View larger version (16K):
[in a new window]
|
Figure 2 Effect of the microvolt T-wave alternans (MTWA) hazard ratio on cost-effectiveness when comparing a risk stratification strategy with MTWA to medical therapy. As varying the MTWA hazard ratio changes the underlying baseline annual mortality rate, the effect of this variable on cost-effectiveness is performed as a two-way sensitivity analysis. Base-case estimates are for an annual mortality rate of 10.1% and a MTWA hazard ratio of 2.35. The incremental cost-effectiveness of a risk stratification strategy with MTWA compared to medical therapy becomes more favorable as the MTWA hazard ratio or the annual mortality rate increases. ICER = incremental cost-effectiveness ratio; QALY = quality-adjusted life-year.
|
|
View larger version (20K):
[in a new window]
|
Figure 3 Effect of the MTWA hazard ratio on cost-effectiveness when comparing an ICD-for-all strategy with a MTWA risk stratification strategy. The incremental cost-effectiveness of an ICD-for-all strategy compared to a risk stratification strategy with MTWA becomes more favorable as the annual mortality rate increases or as the MTWA hazard ratio decreases. Abbreviations as in Figures 1 and 2.
|
|
View larger version (13K):
[in a new window]
|
Figure 4 Estimated distribution of the incremental cost-effectiveness ratio of risk stratification with MTWA testing versus medical therapy in the MADIT-II–eligible population. Data were obtained by performing 10,000 Monte Carlo simulations. The cost-effectiveness ratio was less than $50,000/QALY in 5,459 (54.6%) of the simulations, whereas none of the simulations yielded cost-effectiveness ratios above $100,000/QALY. Abbreviations as in Figures 1 and 2.
|
|
View larger version (13K):
[in a new window]
|
Figure 5 Estimated distribution of the incremental cost-effectiveness ratio of an ICD-for-all strategy versus risk stratification with MTWA testing in the MADIT-II–eligible population. Data were obtained by performing 10,000 Monte Carlo simulations. The cost-effectiveness ratio was above $100,000/QALY in 2,594 (25.9%) of all simulations, whereas no simulations gave cost-effectiveness ratios below $50,000/QALY. Abbreviations as in Figures 1 and 2.
|
|
|
