3 resultados para Dalys

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Cardiovascular disease (CVD) due to atherosclerosis of the arterial vessel wall and to thrombosis is the foremost cause of premature mortality and of disability-adjusted life years (DALYs) in Europe, and is also increasingly common in developing countries.1 In the European Union, the economic cost of CVD represents annually E192 billion1 in direct and indirect healthcare costs. The main clinical entities are coronary artery disease (CAD), ischaemic stroke, and peripheral arterial disease (PAD). The causes of these CVDs are multifactorial. Some of these factors relate to lifestyles, such as tobacco smoking, lack of physical activity, and dietary habits, and are thus modifiable. Other risk factors are also modifiable, such as elevated blood pressure, type 2 diabetes, and dyslipidaemias, or non-modifiable, such as age and male gender. These guidelines deal with the management of dyslipidaemias as an essential and integral part of CVD prevention. Prevention and treatment of dyslipidaemias should always be considered within the broader framework of CVD prevention, which is addressed in guidelines of the Joint European Societies’ Task forces on CVD prevention in clinical practice.2 – 5 The latest version of these guidelines was published in 20075; an update will become available in 2012. These Joint ESC/European Atherosclerosis Society (EAS) guidelines on the management of dyslipidaemias are complementary to the guidelines on CVD prevention in clinical practice and address not only physicians [e.g. general practitioners (GPs) and cardiologists] interested in CVD prevention, but also specialists from lipid clinics or metabolic units who are dealing with dyslipidaemias that are more difficult to classify and treat.

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Background: WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies. Methods: We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis. Findings: All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6—12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility. Interpretation: The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per μL, and then at a CD4 cell count lower than 500 cells per μL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future. Funding: Bill & Melinda Gates Foundation, WHO.

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BACKGROUND The cost-effectiveness of routine viral load (VL) monitoring of HIV-infected patients on antiretroviral therapy (ART) depends on various factors that differ between settings and across time. Low-cost point-of-care (POC) tests for VL are in development and may make routine VL monitoring affordable in resource-limited settings. We developed a software tool to study the cost-effectiveness of switching to second-line ART with different monitoring strategies, and focused on POC-VL monitoring. METHODS We used a mathematical model to simulate cohorts of patients from start of ART until death. We modeled 13 strategies (no 2nd-line, clinical, CD4 (with or without targeted VL), POC-VL, and laboratory-based VL monitoring, with different frequencies). We included a scenario with identical failure rates across strategies, and one in which routine VL monitoring reduces the risk of failure. We compared lifetime costs and averted disability-adjusted life-years (DALYs). We calculated incremental cost-effectiveness ratios (ICER). We developed an Excel tool to update the results of the model for varying unit costs and cohort characteristics, and conducted several sensitivity analyses varying the input costs. RESULTS Introducing 2nd-line ART had an ICER of US$1651-1766/DALY averted. Compared with clinical monitoring, the ICER of CD4 monitoring was US$1896-US$5488/DALY averted and VL monitoring US$951-US$5813/DALY averted. We found no difference between POC- and laboratory-based VL monitoring, except for the highest measurement frequency (every 6 months), where laboratory-based testing was more effective. Targeted VL monitoring was on the cost-effectiveness frontier only if the difference between 1st- and 2nd-line costs remained large, and if we assumed that routine VL monitoring does not prevent failure. CONCLUSION Compared with the less expensive strategies, the cost-effectiveness of routine VL monitoring essentially depends on the cost of 2nd-line ART. Our Excel tool is useful for determining optimal monitoring strategies for specific settings, with specific sex-and age-distributions and unit costs.