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Getting the Diagnosis Right: Approaches to New Diagnostics for Childhood Tuberculosis

Getting the Diagnosis Right: Approaches to New Diagnostics for Childhood Tuberculosis
正确诊断:儿童结核病的新诊断方法
批准号:
2125613
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

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中文摘要
翻译
尽管每年估计有100万儿童新发结核病病例,约占疾病总负担的7%,但这仍然是一个被忽视的问题。每年约有20.9万名儿童死于结核病,其中一半发生在非洲;据信,结核病是造成五岁以下儿童死亡的十大原因之一。主要问题仍然是及时和准确的诊断,因为治疗结果——即使是在耐药性的情况下——明显好于成人。结核病诊断在儿童中仍然是一项挑战,因为检测本身和抽样/检测策略都是为成人结核病设计的。儿童往往患有少杆菌和/或肺外疾病,从儿童身上收集足够的样本是困难的,而且耗时耗力。解决对新诊断方法的需求意味着需要非痰液检测和提高灵敏度,同时使其更可行,特别是在资源有限的环境中。最近,越来越多的宣传、政治和资金支持导致努力制定新的测试和测试战略;因此,已经确定了一些潜在的候选药物,它们具有显著改善儿科结核病诊断的潜力。rapae - tb是一项针对撒哈拉以南非洲地区15岁以下儿童的前瞻性临床研究,旨在评估新的检测方法和检测策略,最终目标是获得世卫组织的认可。该研究将在LMU的AIDA结核病平台(成人和儿童急性和突发结核病的早期和敏感检测的创新诊断和算法评估)上运行,该平台为该项目提供项目管理、科学人员支持和数据管理方面的宝贵基础设施。本研究中评估的大多数新测试使用非痰样本,并采用不同的测试方法:-宿主反应(即Stellenbosch大学基于细胞酮的生物标志物小组和hostRNA特征的评估)-抗原检测(包括两种新的尿液和一种粪便脂arabinman聚糖[LAM]测试)-细胞免疫反应(t细胞活化标记物-结核试验[TAM TB]),LMU/Beckman Coulter)-核酸扩增试验(Xpert Ultra对不同类型的标本,例如使用新的粪便处理方案和鼻咽吸附剂)重要的是,这些新的测试具有很大的潜力,可以通过避免培养来提高儿科病例的检测,而培养在大多数情况下仍然是一个重大的基础设施挑战。最终目标是创建新的分诊算法,允许在怀疑患有结核病的儿童中筛查、确认或排除结核病,这是基于在单个患者队列中同时评估多项检测的研究设计。亚组分析(例如,基于艾滋病毒或营养状况的敏感性分析)和对各种测试序列进行建模以确定新的算法,将大大加强测试性能数据。
英文摘要
Even though children account for an estimated 1 million new cases of TB every year, representing roughly 7% of the total disease burden, it remains a neglected problem. Every year, around 209 000 children die from TB, half of those cases are in Africa; it is believed that TB is among the top ten causes of mortality in children under five years of age. The main issue continues to be timely and accurate diagnosis, as treatment outcomes - even in thecase of drug resistance - are significantly better than in adults.TB diagnosis remains a challenge in children, as both the tests themselves and the sampling/testing strategies are designed for TB among adults. Children tend to have paucibacillary and/or extrapulmonary disease and collection of adequate samples from children is difficult as well as time- and resource-consuming. Addressing the need for new diagnostic approaches implies the need for non-sputum based tests and improved sensitivity, while being morefeasible to conduct, particularly in resource-limited settings.Recently, increased advocacy, political and funding support have led to an effort to develop new tests and testing strategies; as such, a number of potential candidates have been identified with the potential to substantially improve paediatric TB diagnosis.RaPaed-TB is a prospective clinical study among children younger than 15 years in Sub-Sahara Africa, evaluating new tests and testing strategies with the ultimate goal of WHO endorsement. The study will be run on LMU' s AIDA TB platform (Assessment of Innovative Diagnostics and Algorithms for Early and Sensitive Detection of Acute and Incident TB in Adults and Children), which provides project management, scientific staffing support and valuable infrastructure in terms of data management for this project.Most novel tests to be evaluated in this study use non-sputum samples and have different testing approaches:- host response (i.e. a cytokione-based biomarker panel by the University of Stellenbosch and evaluation of hostRNA signatures)- antigen-detection (incl. two novel urinary and one stool lipoarabinomannan [LAM] tests)- cellular immunoresponse (T-cell activation marker-tuberculosis assay [TAM TB], LMU/Beckman Coulter)- nucleic-acid amplification tests (Xpert Ultra on different specimen types, such as using a new stool processingprotocol and nasopharyngeal aspirates)Importantly, these new tests have great potential to enhance paediatric case detection by circumventing the need for culture, which still represents a significant infrastructural challenge in most settings. The ultimate goal is to create novel triage algorithms, allowing to screen, confirm or rule out TB in children suspected of having TB, based on a study design that simultaneously evaluates multiple tests in a single patient cohort. The data on test performances will be significantly strengthened by subgroup analyses (e.g. sensitivity analyses based on HIV- or nutritional status) and the modeling of various successions of tests to identify novel algorithms.
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