Long-Term Clopidogrel Therapy in Patients Receiving Percutaneous Coronary Intervention

Background: The PCI-CURE (Percutaneous Coronary Intervention-Clopidogrel in Unstable Angina to Prevent Recurrent Events) and CREDO (Clopidogrel for the Reduction of Events During Observation) studies have demonstrated that, in addition to aspirin, pre-treatment with clopidogrel followed by long-term (i.e. 9-12 months) therapy significantly reduces the risk of atherothrombotic events in patients undergoing percutaneous coronary intervention (PCI). Objective: To examine the economic implications, from the Dutch healthcare perspective, of the use of clopidogrel in patients undergoing PCI (elective procedures or in patients with acute coronary syndrome), comparing pre-treatment followed by long-term therapy with only 4 weeks of treatment. Methods: A lifetime Markov model was used to combine data from the PCI-CURE and CREDO trials with data from the literature concerning epidemiology, costs and quality of life. The model was run separately for each trial. Only direct healthcare costs (_, year 2004 values) were considered. Costs and outcomes were discounted at 4% per anum. For each trial, the cost effectiveness is expressed as costs per life-year and QALY gained. Uncertainties are addressed by uni- and probabilistic multivariate sensitivity analysis. Results: When starting with the data from the PCI-CURE trial, pre-treatment plus 9-month clopidogrel therapy was predicted to save _1119 and gain 0.03 life-years and 0.07 QALYs per patient compared with short-term treatment. When starting with the data from the CREDO trial, the combination of pre-treatment and prolonged clopidogrel therapy (1 year) was estimated to save _497 and gain 0.10 life-years and 0.14 QALYs per patient. Univariate and probabilistic multivariate sensitivity analyses suggested that the conclusions were generally robust, but that the expected gain in survival for the PCI-CURE population was very sensitive to the effects on mortality within the combined endpoint of myocardial infarction/stroke-free survival. Conclusions: In The Netherlands, pre-treatment plus long-term (9-12 months) therapy with clopidogrel is estimated to save costs and increase (quality-adjusted) survival in the prevention of ischaemic events among patients undergoing elective PCI (CREDO) and in patients with acute coronary syndrome (PCI-CURE) compared with short-term treatment with clopidogrel without pre-treatment.Cardiovascular-disorders, Cardiovascular-disorders, Clopidogrel, Cost-utility

Costs and Consequences of Clopidogrel versus Aspirin for Secondary Prevention of Ischaemic Events in (High-Risk) Atherosclerotic Patients in Sweden: A Lifetime Model Based on the CAPRIE Trial and High-Risk CAPRIE Subpopulations

Background: Antiplatelet therapy plays a central role in the prevention of atherothrombotic events. Both acetylsalicylic acid (aspirin) and clopidogrel have been shown to reduce the risk of recurrent cardiovascular events in various subgroups of patients with vascular disease. Objective: To estimate the cost effectiveness of clopidogrel versus aspirin in Sweden for the prevention of atherothrombotic events based on CAPRIE trial data. The focus of this study is on two high-risk subpopulations: (i) patients with pre-existing symptomatic atherosclerotic disease; and (ii) patients with polyvascular disease. Methods: A Markov model combining clinical, epidemiological and cost data was used to assess the economic value of clopidogrel compared with aspirin during a patient's lifetime. A societal perspective was used, with costs stated in Swedish kronor (SEK), year 2007 values. For the first 2 years, the clinical input for the model was based on the relevant subpopulations in the CAPRIE trial. Thereafter, transition probabilities were extrapolated, taking account of increased risks related to age and to a history of events. Cost effectiveness of 2 years of therapy is presented as cost per life-year gained (LYG) and as cost per QALY. Univariate and multivariate sensitivity analyses were performed to investigate robustness of results. Results: For patients resembling the total CAPRIE population, who were treated with clopidogrel, the expected cost per LYG was SEK217 806 and the cost per QALY was estimated at SEK169 154. For the high-risk CAPRIE subpopulations, costs per QALY were lowest for patients with pre-existing symptomatic atherosclerotic disease (SEK38 153). Using a 'willingness-to-pay' perspective indicated that treatment with clopidogrel instead of aspirin in high-risk patients is associated with a high probability for cost effectiveness; 81% using a threshold of SEK100 000 per QALY and 98% using a threshold of SEK500 000 per QALY. Overall, the results appeared to be robust over the sensitivity analyses performed. Conclusion: When considering the cost-effectiveness categorization as proposed by the Swedish National Board of Health and Welfare, clopidogrel appears to be associated with costs per QALY that range from intermediate in the total CAPRIE population to low in high-risk atherosclerotic patients.aspirin, therapeutic use, clopidogrel, therapeutic use, cost-utility, myocardial-infarction, prevention, stroke, prevention.

Modelling approaches : the case of schizophrenia

Schizophrenia is a chronic disease characterized by periods of relative stability interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter- and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between co-variates and variability (first-order uncertainty).We note that, depending on the research question, the optimal modelling approach should be selected based on the expected differences between the comparators, the number of co-variates, the number of patient subgroups, the interactions between co-variates, and simulation time. Finally, it is argued that in case micro-simulation is required for the cost-effectiveness analysis of schizophrenia treatments, a discrete event simulation model is best suited to accurately capture all of the relevant interdependencies in this chronic, highly heterogeneous disease with limited long-term follow-up data.

Modelling approaches - The case of schizophrenia: the case of schizophrenia

Schizophrenia is a chronic disease characterized by periods of relative stability interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter- and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between covariates and variability (first-order uncertainty). We note that, depending on the research question, the optimal modelling approach should be selected based on the expected differences between the comparators, the number of co-variates, the number of patient subgroups, the interactions between co-variates, and simulation time. Finally, it is argued that in case micro-simulation is required for the cost-effectiveness analysis of schizophrenia treatments, a discrete event simulation model is best suited to accurately capture all of the relevant interdependencies in this chronic, highly heterogeneous disease with limited long-term follow-up data

Modelling Approaches: The Case of Schizophrenia

Schizophrenia is a chronic disease characterized by periods of relative stability interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter- and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between co-variates and variability (first-order uncertainty). We note that, depending on the research question, the optimal modelling approach should be selected based on the expected differences between the comparators, the number of co-variates, the number of patient subgroups, the interactions between co-variates, and simulation time. Finally, it is argued that in case micro-simulation is required for the cost-effectiveness analysis of schizophrenia treatments, a discrete event simulation model is best suited to accurately capture all of the relevant interdependencies in this chronic, highly heterogeneous disease with limited long-term follow-up data.Antipsychotics, Cost-effectiveness, Decision-analysis, Discrete-event-simulation, Markov-model, Modelling, Schizophrenia