The cost-effectiveness of exenatide twice daily (BID) vs insulin lispro three times daily (TID) as add-on therapy to titrated insulin glargine in patients with type 2 diabetes

Objective: To evaluate the cost-effectiveness of exenatide twice daily (BID) vs bolus insulin lispro three times daily (TID) as add-on therapy when glycemic control is sub-optimal with titrated basal insulin glargine and metformin.

Methods: The analysis was based on the recent 4B Study, which compared exenatide BID and lispro TID as add-on therapies in subjects with type 2 diabetes insufficiently controlled, despite titrated insulin glargine. The Cardiff Diabetes Model was used to simulate patient costs and health benefits beyond the 4B Study. The Swedish healthcare perspective was adopted for this analysis; costs are reported in €EUR to aid interpretation. The main outcome measure was the cost per quality-adjusted life-year (QALY) gained with exenatide BID compared to lispro TID.

Results: Exenatide BID was associated with an incremental cost of €1,270 and a QALY increase of +0.64 compared with lispro TID over 40 years. The cost per QALY gained with exenatide BID compared with lispro TID was €1,971, which is within conventional limits of cost-effectiveness. Cost-effectiveness results were generally robust to alternative assumptions and values for key model parameters.

Limitations: Extrapolation of trial data over the longer term can be influenced by modeling and parameter uncertainty. Cost-effectiveness results were generally insensitive to alternative values of key model input parameters and across scenarios.

Conclusions: The addition of exenatide BID rather than insulin lispro to basal insulin is associated with similar or better clinical outcomes. Illustrated from the Swedish healthcare perspective, analysis with the Cardiff Diabetes Model demonstrated that exenatide BID represents a cost-effective treatment alternative to lispro TID as add-on therapy in type 2 diabetes patients insufficiently controlled on basal insulin.     

The opportunity cost of duality

A dual representation of a technology, e.g., a cost function, may not contain all of the technological information, but it will contain all of the information about input vectors that would be chosen by a cost-minimizing firm. At least this much is clear for deterministic technologies. The main question addressed in this paper is whether the same can be said about stochastic technologies and their dual representations. Despite some pessimism expressed in the stochastic frontier literature on this question, we argue that there is no extra cost imposed in the stochastic case. Thus, the conclusion of this paper is: Just dual it!     

Technological change and timing reductions in greenhouse gas emissions

In 2007 Nicholas Stern’s Review (in Science 317:201–202, 2007) estimated that global GDP would shrink by 5–20% due to climate change which brought forth calls to reduce emissions by 30–70% in the next 20 years. Stern’s results were contested by Weitzman (in J Econ Lit XLV(3):703–724, 2007) who argued for more modest reductions in the near term, and Nordhaus (in Science 317:201–202, 2007) who questioned the low discount rate and coefficient of relative risk aversion employed in the Stern Review, which caused him to argue that ‘the central question about global-warming policy—how much how, how fast, and how costly—remain open.’ We present a simulation model developed by Färe et al. (in Time substitution with application to data envelopment analysis, 2009) on intertemporal resource allocation that allows us to shine some light on these questions. The empirical specification here constrains the amount of undesirable output a country can produce over a given period by choosing the magnitude and timing of those reductions. We examine the production technology of 28 OECD countries over 1992–2006, in which countries produce real GDP and CO₂ using capital and labor and simulate the magnitude and timing necessary to be in compliance with the Kyoto Protocol. This tells us ‘how fast’ and ‘how much’. Comparison of observed GDP and simulated GDP with the emissions constraints tells us ‘how costly’. We find these costs to be relatively low if countries are allowed reallocate production decision across time, and that emissions should be cut gradually at the beginning of the period, with larger cuts starting in 2000.     

Seeking External Evidence to Assess Benefit Transfers for Environmental Policy

The cost and time required to produce original benefit estimates makes benefit transfers a highly valuable component of the process of assessing the benefits and costs of environmental improvements. Because of the great variety of benefit estimates, conducted at different times with different data sources and different techniques, there is concerted effort to understand the validity of transfers. The research in this paper approaches the validity issue of benefit transfers by asking whether there is indirect evidence of the benefits. The premise of the paper is that policies that give significant benefits should induce expected and unexpected behavioral changes. We look for evidence of potential indirect evidence by by estimating the effect of differences air pollutants on activities such as outdoor recreation and work, as found in the American Time Use Survey.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

The origins of terrorism: Cross-country estimates of socio-economic determinants of terrorism

Prior research has concluded that socio-economic development does not significantly affect terrorism. We take an alternative view. First, we note that a country's socio-economic circumstances affect terrorists' behavior through terrorism's opportunity costs. We argue that this reasoning also holds for the case of supreme value terrorism. Then, we run a series of negative binomial regressions for 110 countries between 1971 and 2007 to test the hypothesis that poor socio-economic development is conducive to terrorism. We find that socio-economic variables indeed matter to terrorism, contrary to other results. Our findings imply that countries can benefit from economic development and growth in terms of a reduction in terrorism.