Analysis of effectiveness criteria in pharmacoeconomic studies of hypoglycemic drugs proposed for inclusion into the essential drug list in 2014-2016 in Russia

Rationale. There is a certain variability of endpoints in diabetes pharmacoeconomic research in Russia. It makes difficult to compare the economical effectiveness of hypoglycemic drugs. Aim. To estimate a proportion of final and surrogate endpoints used as effectiveness criteria in pharmacoeconomic studies of hypoglycemic drugs proposed for inclusion into the Russian essential drug list in 2014-2016. Methods. 22 pharmacoeconomic studies on 12 hypoglycemic drugs were reviewed. Results. 8 effectiveness criteria were analyzed. Four of them (50%) were final endpoints. 26 of 41 outcomes (63%) related to final endpoints. The most often used endpoint was quality adjusted life years (QALY) - 62% of all final outcomes. The number of avoided cardiovascular events was another commonly used final endpoint (31 % of all hard outcomes). Change in glycated hemoglobin level was the most often used surrogate endpoint (73% of all surrogate outcomes). Conclusions. 1. At least one final endpoint was used in 19 of 20 studies (95%). 2. The most commonly used final endpoints are QALYs and the number of avoided cardiovascular events (93% of all hard outcomes). 3. Glycated hemoglobin level should not be used as the main effectiveness criteria determining the inclusion of drugs into the essential drug list

Economic analysis of Lixisenatide in Diabetes Mellitus Type 2

Usage of glucagon like peptide-1 receptors’ agonists (aGLP-1) is a new step in the treatment of Diabetes Mellitus Type 2 (DM 2). General attractive effects are positive effect on bodyweight, lower risk of hypoglycemia, compliance and possibility of combination with insulin or it’s analogues etc. Clinical-economic analysis of Lixisenatide in combination with insulin glargine has been performed for evaluation of reasons for state or insurance budgeting. Methods: Model of DM 2 has been used for comparison of Direct Costs (DC) of glargine+lixisenatid and basal bolus glargine+glulisine, detemir+aspart, glargine+aspart, glargine+lispro, detemir+lispro, detemir+glulisis as well as with combnations of metformin with exenatide or liraglutide. Efficacy criteria were amount of patient-years without complications during one-year period and amount of patient-years with targeted HbA1c level. Calculation cost has included: expenditures on pharmacotherapy of DM2 and complications, costs of out-patients aid, emergency and hospital treatment. Cost-efficacy ratio and incremental cost-efficacy rate as well Budget Impact have been performed. Results: Highest DC based on 2-year horizon of modelling were calculated for detemir+aspart -277 356 RUR, DC for glargine+lixisenatide was less on 5,6%. Costs of aGLP-1 and insulins were different, and expenditures on hypoglycemia too. Thus detemir+aspart were most expensive 77 763 RUR. Also in this group treatment of hypoglycemia was very costly. CERs (cost- effectiveness ratios) were 2 456 RUR, 3 752 RUR and 3 980 RUR. for glargine+glulisine, glargine+lixisenatide and detemir+aspart accordingly. Highest level of DC has been done for detemir+glulisine 281 628 RUR and detemir+lispro 278 744 RUR. Lixisenatide has led to insulin (glargine) dose reduction in compare with other combinations that reflected in less cost (54 186 RUR for glargine vs 81 289 RUR for detemir+glulisine during 2 years). Amount of patient-years with targeted level of HbA1c was the same in different treatment options but scheme glargine+lixisenatide was less costly DC among schemes with another aGLP-1 was less in glargine+lixisenatide on 65% in compare with metformin+liraglutide (741 531 RUR with 2-years of modelling horizon). Conclusion: Scheme glargine+lixisenatide more cost-saving regimen in compare with metformin+exenatide, metformin+liraglutide, detemir+short acting insulin analogues Scheme glargine+lixisenatide has not benefits in compare with glargine+glulisin but has less hypoglycemia level. Glargine+lixisenatide is an economic appropriate scheme for state (insurance) budgeting

Budget impact analysis: principles of good practice. Report of the ISPOR Working Group on Good Practices for Budget Impact Analysis II, 2012

Background. Budget impact analyses (BIAs) are an essential part of a comprehensive economic assessment of a health care intervention and are increasingly required by reimbursement authorities as part of a listing or reimbursement submission. Objectives: The objective of this report was to present updated guidance on methods for those undertaking such analyses or for those reviewing the results of such analyses. This update was needed, in part, because of developments in BIA methods as well as a growing interest, particularly in emerging markets, in matters related to affordability and population health impacts of health care interventions. Methods. The Task Force was approved by the International Society for Pharmacoeconomics and Outcomes Research Health Sciences Policy Council and appointed by its Board of Directors. Members were experienced developers or users of BIAs; worked in academia and industry and as advisors to governments; and came from several countries in North America and South America, Oceania, Asia, and Europe. The Task Force solicited comments on the drafts from a core group of external reviewers and, more broadly, from the membership of the International Society for Pharmacoeconomics and Outcomes Research. Results. The Task Force recommends that the design of a BIA for a new health care intervention should take into account relevant features of the health care system, possible access restrictions, the anticipated uptake of the new intervention, and the use and effects of the current and new interventions. The key elements of a BIA include estimating the size of the eligible population, the current mix of treatments and the expected mix after the introduction of the new intervention, the cost of the treatment mixes, and any changes expected in condition-related costs. Where possible, the BIA calculations should be performed by using a simple cost calculator approach because of its ease of use for budget holders. In instances, however, in which the changes in eligible population size, disease severity mix, or treatment patterns cannot be credibly captured by using the cost calculator approach, a cohort or patient-level condition-specific model may be used to estimate the budget impact of the new intervention, accounting appropriately for those entering and leaving the eligible population over time. In either case, the BIA should use data that reflect values specific to a particular decision maker’s population. Sensitivity analysis should be of alternative scenarios chosen from the perspective of the decision maker. The validation of the model should include at least face validity with decision makers and verification of the calculations. Data sources for the BIA should include published clinical trial estimates and comparator studies for the efficacy and safety of the current and new interventions as well as the decision maker’s own population for the other parameter estimates, where possible. Other data sources include the use of published data, well-recognized local or national statistical information, and, in special circumstances, expert opinion. Reporting of the BIA should provide detailed information about the input parameter values and calculations at a level of detail that would allow another modeler to replicate the analysis. The outcomes of the BIA should be presented in the format of interest to health care decision makers. In a computer program, options should be provided for different categories of costs to be included or excluded from the analysis. Conclusions. We recommend a framework for the BIA, provide guidance on the acquisition and use of data, and offer a common reporting format that will promote standardization and transparency. Adherence to these good research practice principles would not necessarily supersede jurisdiction-specific BIA guidelines but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines

Biomarkers associated with atherogenesis: current status and promising areas

Biomarkers being used as a laboratory test allow diagnosing the disease at an early stage, confirming diagnostic assumptions or evaluating treatment results. The reveal of biomarkers is inextricably linked to an understanding of the pathogenesis of the disease. As a rule, a biomarker is a soluble molecule participating in the pathological process. The reveal of biomarkers of atherogenesis (BMA) is based on hypotheses of the atherosclerosis development. The formation of atherosclerotic plaques is associated with impaired lipid metabolism, inflammation, fibrosis, calcinosis and oxidative stress. Low-density cholesterol is a recognized BMA in terms of the concept of lipid metabolism disorder. Another concept of atherogenesis is inflammatory theory. To date, a large number of molecules that are involved in the inflammatory process in the formation of atherosclerotic plaques have been studied. For most of these molecules, association with cardiovascular diseases has been proven, but they enter clinical practice very slowly. The most widespread among inflammatory biomarkers of atherogenesis is the highly sensitive C-reactive protein. C-reactive protein is not directly associated with the development of atherosclerosis, however, it is formed in response to the inflammatory reaction, therefore it can be used as a BMA. Its main advantages include stability and well-known reference intervals. Other molecules that can directly participate in the formation of atherosclerotic plaques or lead to their instability are also being studied as BMA. To introduce the use of these markers into routine practice, additional studies are needed to establish reference intervals. In recent years, the role of micro RNA as BMA has been increasingly discussed. Micro RNA molecules have a high stability and indirectly reflect the level of expression of genes involved in the development of atherosclerosis. The determination of BMA directly involved in the formation of plaques will contribute to a more accurate diagnosis and assessment of existing and potential therapy for atherosclerosis