Background: Islet cell transplantation is a method to stabilize type 1 diabetes patients with hypoglycemia unawareness\nand unstable blood glucose levels by reducing insulin dependency and protecting against severe hypoglycemia through\nrestoring endogenous insulin secretion. This study analyses the current cost-effectiveness of this technology and\nestimates the value of further research to reduce uncertainty around cost-effectiveness.\nMethods: We performed a cost-utility analysis using a Markov cohort model with a mean patient age of 49 to simulate\ncosts and health outcomes over a life-time horizon. Our analysis used intensive insulin therapy (IIT) as comparator and\ntook the provincial healthcare provider perspective. Cost and effectiveness data for up to four transplantations per patient\ncame from the University of Alberta hospital.\nCosts are expressed in 2012 Canadian dollars and effectiveness in quality-adjusted life-years (QALYs) and life years. To\ncharacterize the uncertainty around expected outcomes, we carried out a probabilistic sensitivity analysis within the\nBayesian decision-analytic framework. We performed a value-of-information analysis to identify priority areas for future\nresearch under various scenarios. We applied a structural sensitivity analysis to assess the dependence of outcomes on\nmodel characteristics.\nResults: Compared to IIT, islet cell transplantation using non-generic (generic) immunosuppression had additional\ncosts of $150,006 ($112,023) per additional QALY, an average gain of 3.3 life years, and a probability of being costeffective\nof 0.5 % (28.3 %) at a willingness-to-pay threshold of $100,000 per QALY. At this threshold the non-generic\ntechnology has an expected value of perfect information (EVPI) of $260,744 for Alberta. This increases substantially in\ncost-reduction scenarios. The research areas with the highest partial EVPI are costs, followed by natural history, and\neffectiveness and safety.\nConclusions: Current transplantation technology provides substantial improvements in health outcomes over\nconventional therapy for highly selected patients with ââ?¬Ë?unstableââ?¬â?¢ type 1 diabetes. However, it is much more costly and\nso is not cost-effective. The value of further research into the cost-effectiveness is dependent upon treatment costs.\nFurther, we suggest the value of information should not only be derived from current data alone when knowing that\nthis data will most likely change in the future.
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