Economic evaluation of vaccines:Considerations on evidence, discounting, models and futures challenges

OBJECTIVES: During the last decade, with the arrival of new innovative vaccines, there was a huge increase in the number of papers on economic evaluation of vaccination programmes. Our study had a 3-fold objective: 1) Appraise available methodological papers dealing with specificities of vaccines in term of health economics; 2) Illustrate the impact of each issue in term of decision-making process with concrete examples; and 3) Identify futures challenges. METHODS: A comprehensive literature search was conducted to identify methodological papers dealing with specificities of economic evaluations of vaccines. Each issue was illustrated with concrete examples of cost-effectiveness analyses recently performed for HPV vaccines, or pneumococcal diseases. RESULTS: Except guidelines issued in 2008 by the WHO and a few general papers, most of methodological papers focused on modelling techniques and showed a trend in using more and more sophisticated methods (e.g. calibration). Several papers highlighted the need for having strong dynamic transmission models of infectious diseases to evaluate appropriately the cost-effectiveness of vaccination programmes. Other papers focused on the issue of discounting, and showed the extreme impact of discounting for some vaccines given this long-term assessment, possibly warranting an alternative method of discounting for vaccines. Fewer papers highlighted the different type of clinical evidence compared with curative pharmaceutical drugs, in particular the need to model immunological responses into clinical endpoints of disease and short-term efficacy into long-term effectiveness. Although there is an increasing level of expertise in the field, other important issues such as the choice of realistic assumptions (coverage rates or vaccine prices) and the inclusion of externalities (i.e. changes in the epidemiology of the infection) are not well analysed. CONCLUSIONS: It is important for decision makers to keep in mind the above vaccine specificities when they assess the cost-effectiveness of new vaccination programmes in order to provide relevant conclusions

New European guidelines for the management of dyslipidaemia in cardiovascular prevention

The new guidelines from the European Atherosclerosis Society and the European Society of Cardiology include a number of updated items. In this paper, we summarize 4 of these changes that we consider to be the most pertinent. Firstly, cardiovascular risk is now stratified according to 4 (previously 2) categories: "very high risk" (patients with cardiovascular disease, patients with diabetes > 40 years old who have at least one other risk factor, patients with kidney failure, or patients in primary prevention with a SCORE value > or = 10%); "high risk" (patients in primary prevention with a SCORE value > or = 5% and or = 1% and < 5%); and "low risk" (primary prevention with SCORE < 1%). The SCORE value for patients in primary prevention is estimated using the SCORE table (calibrated for Belgium). Risk in this table may now be corrected according to HDL cholesterol level. Secondly, the therapeutic targets for each category are now more stringent: LDL cholesterol < 70 mg/dl (or reduced by at least 50%) if the risk is "very high"; < 100 mg/dl if the risk is "high"; and < 115 mg/dl if the risk is "moderate". Thirdly, for patients at "high" or "very high" risk, particularly in patients with combined dyslipidaemia, two further therapeutic targets should be considered: non-HDL cholesterol and apolipoprotein B levels. Fourthly, the follow-up of efficacy (lipid profile) and tolerance (hepatic and muscular enzymes) is described in more details so as to harmonize case management in clinical practice.Peer reviewe

ES8 COST-EFFECTIVENESS OF DARUNAVIR/R IN HIGHLY TREATMENT-EXPERIENCED HIV/AIDS PATIENTS IN DIFFERENT EUROPEAN HEALTH CARE SETTINGS

Large-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function