MICA: MRC APBI STratification and Extreme Response Mechanism IN Diabetes - MASTERMIND

研究背景超过4%的人口患有2型糖尿病。它是疾病和早期死亡的主要原因，约占NHS支出的10%。通过适当的生活方式和药物治疗，控制好血糖，使患者感觉良好，降低糖尿病并发症发生的风险。MASTERMIND研究涉及学术研究人员和行业之间的合作，以帮助2型糖尿病患者接受最合适的治疗。目前，2型糖尿病患者的治疗指南中列出了大量的药物，但没有明确指导哪些患者应该服用哪些药物。这使得患者和他们的医疗保健专业人员很难知道哪种药物可能最适合他们。我们知道，2型糖尿病患者对不同的糖尿病药物的反应有很大的不同，他们是否会对特定的药物产生副作用。我们最初的试点研究帮助我们确定了确定反应亚组的最佳实验类型，并让我们产生了初步结果，现在我们可以对其进行测试、改进和扩展。该项目的目的是根据患者的体重或血液测试结果等特定临床特征，确定对特定药物反应良好或不良的亚组患者，以便更好地针对特定个体进行治疗。新项目旨在建立在最初的研究工作的基础上，涉及两个方面：1。我们将开展一项试验，目前接受二甲双胍和磺脲治疗的高血糖患者将随机接受3种不同的糖尿病片。我们将在研究开始时进行测量并采集血液样本，然后在使用每种药物4个月后测量患者的平均血糖控制（HbA1c）。我们还会记录任何副作用并询问患者他们更喜欢哪种治疗方法。这三种治疗糖尿病的方法不同。我们将能够测试这是否意味着不同的患者有不同的临床特征（例如，患者是否肥胖，或者他们是否有较差的肾功能），这些特征决定了他们对药物的反应是否良好。我们将分析拥有数千名2型糖尿病患者数据的大型公开数据集。我们将获得来自全科医生实践的匿名数据和制药公司进行的药物试验的数据。我们将使用统计分析来确定哪些特征挑选出在短期和长期内对不同药物反应良好的患者，并确定哪些患者有副作用。本研究的主要成果有：1.主要研究成果；可用于确定哪些亚组患者对哪些药物反应最佳的标准信息。这一证据将用于为2型糖尿病的新处方指南提供信息。2. 如何识别这些个体亚群的方法学的发展将有助于该领域的未来研究。这些新的科学方法和数据分析技术也可以应用于其他疾病。3. 学术团体和制药公司将获得大量来自2型糖尿病患者样本的生物资源，以及他们对三种不同的糖尿病药物的反应。这将在未来的研究中使用，在这些样本中可以分析发现新的血液标记物，以确定个体是否可能对特定药物产生良好或不良的反应，并将通过深入了解为什么不同的患者对不同的2型糖尿病药物产生不同的反应来帮助药物开发。

Context of the researchOver 4% of the population have Type 2 diabetes. It is a major cause of illness and early death accounting for around 10% of the money spent in the NHS. Good control of blood glucose with appropriate life style and medication makes patients feel better and reduces the risks of the development of the complications of diabetes. The MASTERMIND study involves collaboration between academic researchers and industry to help patients with Type 2 diabetes receive the most suitable treatment. At present, the guidelines for treatment of patients with Type 2 diabetes list a large number of drugs without giving clear guidance on which patients should have which drugs. This makes it difficult for patients and their health care professionals to know which drugs are likely to suit them best. We know that patients with Type 2 diabetes vary greatly in how well they respond to different diabetes drugs, and whether they develop side effects to particular medications. Our initial pilot study has helped us to determine the best types of experiment to identify response subgroups and has let us generate preliminary results that we can now test, improve and expand upon.Aim of the researchThe aim of this project is to identify subgroups of patients that respond well or poorly to particular drugs based on particular clinical characteristics such as their weight or blood test results, to enable better targeting of treatment for a particular individual. Outline of the researchThe new project aims to build on the work done in the initial study and involves 2 strands:1. We will carry out a trial where patients who currently have high blood glucose on metformin and sulphonylurea therapy will receive 3 different diabetes tablets in random order. We will take measurements and blood samples at the start of the study, and then measure the patients' average blood glucose control (HbA1c) at the end of 4 months on each of these drugs. We will also record any side effects and ask the patient which treatment they preferred. These 3 diabetes treatments work in different ways. We will be able to test whether this means different patients have different clinical features (e.g. whether a patient is obese, or whether they have poorer kidney function) that determine whether they respond well to the drugs.2. We will analyse large publicly-available datasets that have data on thousands of patients with Type 2 diabetes. We will have access to anonymised data from GP practices and data from drug trials run by pharmaceutical companies. We will use statistical analysis to identify which features pick out patients who respond well to the different drugs in the short and long term and also to identify which patients have side effects.Key outcomes of the researchThe key outcomes of this work are: 1. Information on the criteria that can be used to identify which subgroups of patients respond best to which drugs. This evidence will be used to inform new guidelines for prescribing drugs for Type 2 diabetes. 2. Development of methodology for how to identify these subgroups of individuals that will help future studies in this area. These new scientific methods and data analysis techniques can then also be applied to other diseases. 3. A large bioresource of samples from patients with Type 2 diabetes and how they responded to the three different diabetes drugs will be available to both academic groups and pharmaceutical companies. This will be used in future studies where these samples can be analysed to find new blood markers that identify whether an individual is likely to respond well or poorly to a particular drug, and will help drug development by giving insights into why different patients respond differently to the different Type 2 diabetes drugs.