ORAL ABSTRACTS: COST EFFECTIVENESS OF CARDIOVASCULAR DISEASE INTERVENTIONS
ALL TAKING SOME OR SOME TAKING NONE? ASSESSING WHETHER DIFFERENT APPROACHES FOR MODELING DRUG COMPLIANCE AFFECT THE OPTIMAL DECISION FOR STATIN TREATMENT INITIATION
Purpose: When medication compliance is reported as a single value without additional context, it is unclear how this parameter should be modeled in cost-effectiveness analyses. We sought to evaluate whether modeling compliance using two extreme assumptions affected the optimal decision for initiating statin treatment for primary atherosclerotic cardiovascular disease (ASCVD) prevention in the U.S.
Methods: We used a previously developed and validated ASCVD micro-simulation model for a representative adult population in the U.S. (ages 40-75 years). In the model, hypothetical individuals received statin treatment, experienced ASCVD events, and died from ASCVD-related or non-ASCVD-related causes based on ASCVD natural history and statin treatment parameters. All model parameters were estimated from published sources. Statin compliance rates after initiating treatment were 67%, 53%, and 50% in years 1, 2, and 3+, respectively. We used this model to identify and compare optimal ASCVD treatment thresholds under two statin compliance assumptions: 1) proportional reductions in drug effectiveness/risks/costs for all users; and 2) some proportion of patients that are fully compliant with all others completely noncompliant. We evaluated various 10-year ASCVD risk thresholds between >2.0-15.0% (including >7.5%, the current policy recommendation in the U.S.) as well as a treat none strategy in our cost-effectiveness analyses. We used a societal perspective, 3% discount rate for costs and health outcomes, and $50,000-$150,000 per quality-adjusted life year (QALY) cost-effectiveness threshold range.
Results: For any given ASCVD treatment threshold strategy, lifetime discounted costs and QALYs were lower using compliance approach 1 (proportional reductions) compared to compliance approach 2 (individuals either fully compliant or noncompliant). The differences between compliance approaches were more pronounced for strategies that resulted in more individuals taking statins (i.e., for more lenient treatment thresholds). Optimal ASCVD treatment thresholds were >7.5%, >4.0%, and >3.0% using cost-effectiveness thresholds of $50,000/QALY, $100,000/QALY, and $150,000/QALY respectively for both compliance approaches (Table).
Conclusions: While the choice of modeling statin compliance affected total cost and QALY results, we found that the optimal decisions regarding statin treatment thresholds in the U.S. did not differ by compliance approach. The true effect of medication noncompliance likely lies somewhere between the two extreme approaches we evaluated.
Hundreds of thousands of patients each year undergo percutaneous coronary intervention (PCI) after either a myocardial infarction (MI) or angina. Antiplatelet therapy with 12 months use of clopidogrel (Plavix) has long been considered standard treatment after a PCI in order to prevent MI and death. Recently two new drugs, prasugrel and ticagrelor, have been introduced, but there is uncertainty as to whether or not these new treatments offer value for money. Our objective was to compare the cost-effectiveness of different antiplatelet drugs for patients who have undergone PCI.
We modified a previously developed probabilistic Markov model to fit the current research question. The model applies a lifelong health care payer perspective after a PCI operation including risk of MI, major bleeding, new revascularization (PCI or coronary artery bypass graft) and death. All costs and health benefits were discounted at 4% as recommended in national guidelines.
Efficacy data of prasugrel and ticagrelor compared to clopidogrel were based on the two licensing phase III randomized controlled trials including 13 608 and 18 624 participants, respectively. Outcomes included significant reductions in risk of MI for both drugs, increased risk of bleeding and reduced risk of revascularization with prasugrel and reduced overall mortality with ticagrelor.
Costs of all three antiplatelet drugs are based on current prices from the Norwegian Medicines Agency; EUR 207 per year for Clopidogrel, EUR 509 per year for Prasugrel and EUR 817 per year for Ticagrelor.
60-year old patients undergoing PCI had a life expectancy of 17.52 (11.96 discounted) if treated with clopidogrel the first year. Treatment with prasugrel increased life expectancy to 18.21 (12.30 discounted), while ticagrelor resulted in 19.04 life years (12.69 discounted). Ticagrelor was cost-effective compared to clopidogrel at an ICER of EUR 8 000 per life year gained, while prasugrel was extendedly dominated by ticagrelor and clopidogrel. At an assumed cost-effectiveness threshold of EUR 70 000 per life year gained, 77%, 23% and 0.1% of simulations indicated that ticagrelor, prasugrel and clopidogrel were cost-effective, respectively.
Ticagrelor is clearly cost-effective compared to prasugrel and clopidogrel for a Norwegian setting.
Method: A state-transition model was used to examine the cost-effectiveness of telehomecare and usual care for a hypothetical cohort of mixed gender 50 year old Canadian COPD patients. The model included health states structured around disease stages according to GOLD (Global Initiative for Chronic Obstructive Lung Disease) classifications. Subgroup analyses were performed for age decile groups (30 to 80 years) and disease severity. A conservative scenario analysis, in which the treatment effect of telehomecare ceased upon patient departure from the telehomecare program (6 months), was conducted to consider the impact of duration of effect on the cost-effectiveness estimate. Model data were obtained from published literature. We used a payer perspective, a lifetime horizon and a 5% discount rate.
Result: Telehomecare was associated with higher costs ($38,320.01 vs. $36,862.72) and gains QALYs (13.02 vs. 13.00 QALYs) per person, translating to an ICER of $53,336.99/QALY gained compared to usual care. Subgroup analyses indicated that ICERs were lower for older patients (>60 years) or higher disease severity (> stage 2). In a scenario analysis in which the effect of telehomecare was not sustained beyond the duration of the program (6 months), the model estimated a higher ICER of $84,933.23/QALY gained.
Conclusion: Our analysis suggested that telehomecare is likely to be cost-effective for 50-year old mixed gender COPD patients at a WTP threshold of $100,000/QALY. Telehomecare may be more cost-effective in older, more severe patients. The duration of telehomecare effects over the cohort’s lifetime may have substantial effects on the cost-effectiveness of the program.
Methods: We developed two analogous decision analytic models and conducted value of information(VOI) analyses to quantitatively compare the evidence from two interventions in atrial fibrillation patients: pharmacogenomic-based algorithm for warfarin dosing and dose reduction of warfarin following amiodarone initiation. The key model differences were intervention specific parameters. We used the baseline clinical event rates from ARISTOTLE(main study) trial for pharmacogenomic-based intervention and rates from re-analysis of ARISTOTLE study(analysis of amiodarone use) for DDI-based intervention. Relative risk estimates were taken from a recent meta-analysis of RCTs for pharmacogenomic-model, whereas for DDI-model, from a large observational study. We used US payer perspective and a lifetime horizon. We estimated the probability of making a non-optimal decision, expected value of perfect information(EVPI) per patient, and EVPI at the population level.
Results: The relative risk of major hemorrhage for CYPC29 gene variant (exposure for pharmacogenomics) vs wild type was 2.26(95%CI:1.36, 3.75), and the hazard ratio for major hemorrhage related hospitalization following concomitant warfarin and amiodarone(exposure for DDI) therapy was 2.45(95%CI:1.49, 4.02). The treatment effects(prevention of major hemorrhage) for the pharmacogenomic-and DDI-based interventions were 0.60 and 0.41, respectively. Initial simulation results indicate the QALYs improvements were 0.011 and 0.033 for pharmacogenomics- and DDI-based interventions, respectively. The probability of making a non-optimal decision was 15.6 and 10.1 percent for pharmacogenomics- and DDI-based intervention. The EVPI was $119 and $187 per patient and $179 million and $280 million at the AF population level for pharmacogenomics- and DDI-based interventions. The population EVPI for pharmacogenomic-based intervention decreased to $49 million with an assumed test cost of $0.
Conclusions: The evidence levels for warfarin pharmacogenomics and warfarin-amiodarone DDI appear to be similar. The value of perfect information is higher for DDI because of greater uncertainty in the stroke risk due to dose reduction of warfarin. Our findings suggest that policies for implementation of pharmacogenomics-based testing should be comparable to the DDI-based clinical decisions, which is not the case currently in both clinical and reimbursement guidelines.
Purpose: Stratified medicine may improve the cost-effectiveness of medical interventions by targeting the right patients. Long-term survival benefit of a one-time treatment may be estimated by multiplying a trial-based short-term mortality risk reduction with the life expectancy after short-term survival. We aimed to study the influence of different modelling choices for the within-trial mortality risk reduction and post-trial life expectancy on estimates of cost-effectiveness for individual patients.
Method: We analyzed 30,510 patients with an acute myocardial infarction who were included in the GUSTO-I trial and treated with different forms of thrombolysis. Estimates of short-term mortality risk reduction were obtained from a logistic regression model with treatment (aggressive vs standard thrombolysis), sex and age as predictor variables. Life expectancy estimates were derived from sex and age-specific US life tables with an additional 2% yearly excess hazard to capture the increased mortality risk of cardiovascular patients. Aggressive thrombolysis was considered cost-effective when incremental costs per life year gained fell below $50,000.
Result: Based on sex and age-specific risk reductions but average population life expectancy, there was a substantial difference in expected life years gained between the lowest and highest quintile of short-term mortality risk (0.04 in first quintile vs 0.43 in fifth quintile; Figure 1). On individual patient level these assumptions imply aggressive thrombolysis to be cost-effective for men above the age of 48 and women above the age of 44 (83% of the population). When both mortality risk reduction and life expectancy were sex and age-specific, the difference in life years gained between the lowest and highest risk quintile was substantially attenuated (0.06 in first quintile vs 0.24 in fifth quintile; Figure 1). Individual cost-effectiveness of aggressive thrombolysis was extended to men above 43 and women above 37 of age (92% of the population).
Conclusion: This case-study illustrates how failure to model short-term risk
reduction and life expectancy at a congruent level of detail may mislead our
estimates of individualized cost-effectiveness and misallocate resources.
Figure 1 Life years gained from aggressive thrombolysis per 100 patients with an acute MI by sex and age specific short-term mortality risk quintile. Based on average population life expectancy (white bars) and on sex and age specific life expectancy (grey bars).
USING MODELING TO PROJECT OPTMIAL CAROTID STENOSIS SCREENING PRACTICES
Purpose: Carotid artery stenosis (50-99% extracranial internal carotid artery blockage) is a risk factor for ischemic stroke. The United States Preventive Services Task Force (USPSTF) recently recommended against screening for asymptomatic carotid artery stenosis (ACAS) in the general population, although the USPSTF report also suggested that improved testing approaches could justify some screening. We sought to use simulation modeling to identify potentially efficient ACAS screening practices.
Methods: We developed a decision analytic model to compare the following screening strategies for ACAS in 65-year-olds in the U.S.: 1) general population screening with Duplex ultrasound (DUS); 2) focused DUS screening on individuals at highest risk for ACAS (based on clinical risk factors); 3) screening with confirmatory diagnostic test (ACAS diagnosis requires positive DUS and follow-up magnetic resonance imaging angiography results); 4) focused screening with confirmatory diagnostics (combination of strategies 2 and 3); and 5) no screening. Individuals' stroke risks were based their ACAS state. In the model, patients with positive ACAS test results undergo revascularization (carotid endarterectomy), which reduces the risk of stroke (relative risk of 0.54). ACAS prevalence (1.0%), test performance parameters (including sensitivity and specificity, ranging from 88-98%), and revascularization benefits, risks and costs, were estimated from published sources. Discounted lifetime costs and quality-adjusted life years (QALYs) were projected for each strategy.
Results: Strategy 5 (no screening) had lifetime discounted costs and QALYs of $7,758 and 11.695, respectively. All other strategies were dominated (i.e., had higher costs and lower or equal QALYs), with costs and QALYs ranging from $7,766 (strategy 4)-$9,464 (strategy 1) and 11.695 (strategies 2 and 4)-11.678 (strategy 1). Results were robust to changes in all parameters related to costs inputs, utility values, and revascularization risks and benefits in one-way sensitivity analyses. Results were sensitive to the probability of stroke in ACAS patients the specificity of the DUS test for ACAS (Figure).
Conclusions: The USPSTF recommendation is consistent with our cost-effectiveness results for general population or staged screening for ACAS, although identifying ACAS patients at higher risk for stroke (i.e., risk stratification among ACAS patients) coupled with improved DUS specificity could result in cost-effective ACAS screening strategies.