Non-adherence to therapy in chronic conditions (initially tuberculosis): a quantitative, methodological approach.

慢性病（最初是结核病）不坚持治疗：一种定量的方法论方法。

• 批准号: 2444987
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2444987
• 关键词: Non; adherence; therapy; chronic; conditions

The severity and spread of an infectious disease can be seen as the culmination of three elements: its global prevalence, its lethality and the difficulty in eradicating it. This severity of this summation should be mitigated by the existence of an effective cure. However, difficulties in ensuring adherence to treatment prevents the success of reducing the burden of many preventable diseases. This project will use tuberculosis (TB) as an example of a chronic disease.TB continues to be one of the most widespread infectious diseases and is responsible for 1.5 million deaths a year. This estimate is set to rise because of the disruption to supply chains of medication and health care systems caused by SARS-CoV-2. TB is one of the top ten causes of death and it the most lethal single infectious agent in humans. The pathogens that cause the majority of TB transmission are Mycobacterium tuberculosis and the closely related Mycobacterium africanum. The Mycobacterium genus is notoriously difficult to eliminate from the body and requires a long course of several drugs which can have serious side-effects that can be difficult to manage. Adherence to these drugs is important for curing the disease. The extent of adherence to therapy required for a positive outcome is unknown. Aims: To investigate how adherence patterns should influence our approach to treatment to maximise favourable outcomes, starting with tuberculosis as a model disease:Objectives1) Describe non-adherence patterns across the duration of treatment in tuberculosis, using pre-existing and newly collected data sources.2) Determine how different adherence patterns impact treatment outcomes?3) Ascertain if patient characteristics are associated with being at risk of the most detrimental adherence patterns.4) Working with modelling colleagues, examine how such patterns could influence optimal dosing.

传染病的严重性和传播可以被视为三个因素的结果：其全球流行性、致命性和根除难度。这种总和的严重性应该通过有效治疗的存在来减轻。然而，确保坚持治疗的困难阻碍了减轻许多可预防疾病负担的成功。该项目将使用结核病 (TB) 作为一种慢性疾病的示例。结核病仍然是最广泛传播的传染病之一，每年导致 150 万人死亡。由于 SARS-CoV-2 造成药物和医疗保健系统供应链中断，这一估计数将会上升。结核病是十大死因之一，也是人类最致命的单一传染病。引起大多数结核病传播的病原体是结核分枝杆菌和密切相关的非洲分枝杆菌。众所周知，分枝杆菌属很难从体内消除，并且需要多种药物的长期疗程，这可能会产生难以控制的严重副作用。坚持使用这些药物对于治愈疾病很重要。获得积极结果所需的治疗坚持程度尚不清楚。目的：以结核病为模型疾病开始，研究依从模式应如何影响我们的治疗方法，以最大限度地提高有利结果：目标 1) 使用预先存在的和新收集的数据源描述结核病治疗期间的不依从模式。2) 确定不同的依从模式如何影响治疗结果？3) 确定患者特征是否与面临最有害依从风险相关 4) 与建模同事合作，研究这些模式如何影响最佳剂量。