Evaluating effects of complex treatments in chronic disease using large observational datasets

慢性病患者和他们的照顾者面临着关于治疗效果的难题：联合使用多种治疗方法的长期效果是什么？在不同的治疗选择下，给定患者的预期健康结果是什么？随机对照试验是评估治疗效果的黄金标准，但它们回答复杂问题的能力有限。它们通常局限于最终治疗人群的一部分，随访时间短，通常不考虑几种治疗方法的组合，而且可能是不道德的。来自疾病登记处和电子健康记录的大型纵向观察数据集提供了了解治疗效果的手段，而这在试验中是不可行的。然而，要做到这一点，我们必须成功地克服一个根本困难，即那些接受治疗的人是有原因的，因此接受治疗和没有接受治疗的群体不能直接进行比较。如何处理这一问题是一个非常活跃的研究领域。该奖学金将开发和评估所需的统计方法，以利用大型观测数据集解决有关治疗对健康结果的影响的关键问题。它还将利用英国囊性纤维化注册中心的数据解决有关治疗对囊性纤维化患者健康结局的影响的关键问题。CF是一种遗传性、慢性、进行性和缩短寿命的疾病，在英国约有10,000人受到影响。CF患者需要来自卫生服务机构和家庭的强化治疗和支持。英国CF注册中心几乎每年都会收集几乎所有英国CF的数据，这些数据包含人口统计信息、所用治疗的信息、临床测量以及出生、诊断和死亡日期。主要的统计进步将包括能够估计多种联合使用的治疗对健康结果的影响的方法；以与患者和临床医生最相关的方式回答有关一次性主要干预(例如肺移植)对生存的影响的问题的方法；以及向患者提供关于不同治疗选择下他们的预期结果的个性化信息的方法。CF患者每天要接受许多治疗，这既耗时又令人不快。该奖学金中涉及的问题将集中在那些可以帮助减轻治疗负担并帮助患者和临床医生做出治疗决定的问题上。我们将调查三种常用治疗方法对肺功能的影响，以及接受异烟肼治疗的患者现有治疗是否多余。异烟肼自2012年以来是CF的一种主要新治疗方法，对特定基因型的患者有效。另一个关键问题是肺移植对CF存活率的影响。这项研究将为患者提供个性化的信息，了解如果他们选择是否被列入肺移植名单，他们的预期生存情况。在奖学金的第二部分，我将使用临床实践研究数据库(CPRD)研究治疗对其他具有重大公共卫生重要性的慢性疾病领域健康结局的影响。CPRD是一个数据库，包含英国1100多万名患者，来自全科医生的记录。对慢性萎缩性胃炎和其他慢性疾病中出现的新问题作出反应将是重要的。进一步的统计学发展将是一个持续的焦点。这项研究将由未来领导者研究员领导，并由一名博士后研究员协助。主办机构是伦敦卫生和热带医学院。囊性纤维化信托基金是一家英国慈善机构，也是该项目的合作伙伴。几位合作者将提供专家意见：他们包括统计学家、临床医生和患者代表。

Patients with chronic conditions and their carers face difficult questions about the effects of treatments: What are the long-term effects of multiple treatments used in combination? What are the expected health outcomes for a given patient under different treatment choices? Randomized controlled trials are the gold standard for estimating treatment effects, but their ability to answer complex questions is limited. They are typically restricted to a subset of the eventual treatment population, have short follow-up, usually do not consider several treatments in combination, and can be unethical. Large longitudinal observational datasets from disease registries and electronic health records provide the means to gain understanding of treatment effects that would not be feasible in a trial. However, to do this we have to successfully overcome the fundamental difficulty that those who received a given treatment were prescribed it for a reason, and hence the groups who do and do not receive treatment are not directly comparable. How to handle this is a highly active area of research. This fellowship will develop and evaluate statistical methods needed to address key questions about the effects of treatments on health outcomes using large observational datasets. It will also tackle crucial questions about the effects of treatments on health outcomes for patients with cystic fibrosis (CF) using data from the UK CF Registry. CF is an inherited, chronic, progressive, and life-shortening condition affecting about 10,000 in the UK. People with CF need intensive treatment and support from health services and families. The UK CF Registry captures data on nearly all UK CF approximately annually and the data contain demographic information, information on treatments used, clinical measurements, and dates of birth, diagnosis and death.Key statistical advancements will include methods enabling estimation of the effects of multiple treatments used in combination on health outcomes; methods for answering questions about the impact of a one-time major intervention (e.g. lung transplantation) on survival in a way that is most relevant to patients and clinicians; and methods for providing personalised information to patients about their expected outcomes under different treatment choices. Patients with CF take many treatments daily, which is time consuming and unpleasant. Questions addressed in this fellowship will focus on those that could help reduce treatment burden and help patients and clinicians in making treatment decisions. We will investigate the impact of three commonly used treatments on lung function, and whether existing treatments are redundant in patients receiving Ivacaftor, which is a major new treatment in CF since 2012 and effective for patients with a certain genotype. Another key question will be about the impact of lung transplantation on survival in CF. This research will provide personalised information for patients about what their expected survival would be should they choose to be listed for lung transplant or not.In the second part of the fellowship, I will study the impact of treatments on health outcomes in other chronic disease areas of major public health importance, including type 2 diabetes, using the Clinical Practice Research Database (CPRD). CPRD is a database of over 11 million patients in the UK, obtained from General Practitioner records. It will be important to react to new questions arising in CF and in other chronic diseases. Further statistical developments will be an ongoing focus.This research will be led by the Future Leaders Fellow with assistance from a postdoctoral researcher. The host institution is the London School of Hygiene and Tropical Medicine. The Cystic Fibrosis Trust, a UK-wide charity, is a Project Partner. Several collaborators will provide expert input: they include statisticians, clinicians, and patient representatives.