Optimization of Medical Treatment Decisions for Type 2 Diabetes

该项目的研究目标是开发新的数学模型和求解方法，以研究2型糖尿病最佳治疗方案的设计。这项研究将首先调查使用常见药物治疗方案(如胆固醇和降血压药物)管理心血管风险的模型。在患者未来健康状况存在不确定性的情况下，将开发算法方法来计算最优和近似(接近最优)的治疗指南。这些模型将考虑多个角度，包括患者的质量调整后的寿命、治疗成本以及糖尿病相关并发症给医疗系统带来的成本。根据美国糖尿病协会的数据，美国有2000多万儿童和成年人患有糖尿病。在受影响的人群中，大约90%患有2型糖尿病。目前，存在几种风险模型来预测与2型糖尿病相关的并发症的概率，包括心脏病发作和中风等心血管并发症；然而，关于如何使用这些模型来做出最佳治疗决策的调查有限。该项目寻求通过进一步了解如何在患者的一生中以最佳方式治疗2型糖尿病的基本知识来弥合这一差距。预计这一研究项目的发现将可用于其他疾病的治疗。

The research objective of this project is to develop new mathematical models and solution methodologies to study the design of optimal treatment plans for type 2 diabetes. The research will begin by investigating models for the management of cardiovascular risk using common drug treatment options such as cholesterol and blood pressure lowering medication. Algorithmic methods will be developed for computing optimal and approximate (near optimal) treatment guidelines in the presence of uncertainty about a patient's future health status. The models will consider multiple perspectives including a patient's quality adjusted lifespan, the costs of treatment, and the cost of diabetes related complications to the health system.According to the American Diabetes Association, there are more than 20 million children and adults in the United States who have diabetes. Of the affected population, approximately 90 percent have type 2 diabetes. Currently, several risk models exist to predict the probability of complications related to type 2 diabetes, including cardiovascular complications such as heart attack and stroke; however, there has been limited investigation of how to use these models to make optimal treatment decisions. This project seeks to bridge this gap by furthering the basic knowledge of how to optimally treat type 2 diabetes over the course of a patient's lifetime. It is anticipated that discoveries from this research project will be transferrable to the treatment of other diseases.