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OBJECTIVES: The overall objective of this study was to estimate the costs and outcomes associated with treatment with valsartan for post-myocardial infarction (post-MI) patients with left ventricular systolic dysfunction, heart failure, or both, who are not suitable for treatment with angiotensin-converting enzyme (ACE) inhibitors, compared to placebo.
METHODS: A Markov model, using data drawn from the Valsartan in Acute Myocardial Infarction (VALIANT) trial and other trials, was developed to predict the future health pathways, resource use, and costs for patients who have recently experienced an MI. Patients received either valsartan (mean dose 247 mg) or placebo. Cost data were drawn from national databases and published literature, although health outcome utility weights were derived from existing studies. Patient outcomes were modeled for 10 years, and incremental cost-effective ratios were calculated for valsartan compared with placebo.
RESULTS: Over a period of 10 years, a cohort of 1000 patients treated with valsartan experienced 147 fewer cardiovascular deaths, 37 fewer nonfatal MIs, and 95 fewer cases of heart failure than a cohort who received placebo. The incremental cost of valsartan, compared with placebo, was 2680 pound per patient, although the incremental effectiveness of valsartan was 0.5021 quality-adjusted life-years (QALYs) gained per patient. Therefore, the incremental cost per QALY for treatment with valsartan was 5338 pound. When analysis was undertaken using life-years rather than QALYs, the cost per life-year gained was 4672 pound.
CONCLUSIONS: For patients who are not suitable for treatment with ACE inhibitors, valsartan is a viable and cost-effective treatment for their management after an MI.
Identifying information to inform patient care decisions can be straightforward if you know the important key resources. In recent years the NHS has invested in services that collate evidence and identify the messages from research. You can use these to help make patient care more evidence-based and to reduce health inequalities. This article describes some of the key resources you can use to inform life-long learning and to answer day-to-day clinical queries.
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Treatment with imatinib has demonstrated high response rates and improved prognosis in chronic myelogenous leukemia. However, while the short-term response to imatinib is high, there are some concerns that the long-term response is substantially lower. Durable response with imatinib is difficult to achieve in patients with resistant disease. The use of higher doses has also been associated with increased toxicity and intolerance. Dasatinib is a new SRC–ABL-kinase inhibitor that has been developed for treating chronic myelogenous leukemia patients, across all phases of disease, who are resistant or intolerant to imatinib. This article details the existing evidence on the clinical efficacy, safety and value for money of dasatinib in the treatment of imatinib-resistant and -intolerant patients with chronic myelogenous leukemia. Dasatinib is associated with higher levels of response compared with high-dose imatinib. In addition, higher levels of response are associated with improved health outcomes in terms of both quality- and quantity-of-life years.
While economic models are a useful tool to aid decision-making in healthcare, there remain several types of uncertainty associated with this method of analysis. One-way sensitivity analysis allows a reviewer to assess the impact that changes in a certain parameter will have on the model's conclusions. Sensitivity analysis can help the reviewer to determine which parameters are the key drivers of a model's results. By reporting extensive outputs from sensitivity analysis, modellers are able to consider a wide range of scenarios and, as such, can increase the level of confidence that a reviewer will have in the model. Probabilistic sensitivity analysis provides a useful technique to quantify the level of confidence that a decision-maker has in the conclusions of an economic evaluation.
As more countries use HTA to inform decisions on the reimbursement of health technologies, harmonization of evidence requirements between jurisdictions has been proposed, mainly on the grounds of improved efficiency. Harmonization has the potential to avoid duplication of effort for both manufacturers and HTA bodies involved in preparing and reviewing HTA submissions for innovative technologies. However, it also carries risks of loss of local control over decisions, the application of general data standards which are not universally accepted and slowing the rate of development of innovation in the analytical disciplines supporting HTA. This study reviews the issues associated with harmonization taking into account the perspectives of the multiple stakeholders. This study draws on experiences from recent initiatives intended to promote the harmonization of HTA and experience from related fields, particularly regulatory approval of new medical technologies.
