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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
尽管儿童每年约有100万新发结核病病例,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209 000名儿童死于结核病,其中一半发生在非洲;据信,结核病是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-即使在耐药性的情况下-也明显好于成人。结核病诊断在儿童中仍然是一个挑战,因为检测本身和取样/检测策略都是为成人结核病设计的。儿童往往患有少菌性和/或肺外疾病,从儿童身上收集足够的样本是困难的,也是耗时耗力的。解决对新的诊断方法的需要意味着需要进行非痰基检测和提高敏感性,同时更可行,特别是在资源有限的情况下,最近,宣传、政治和资金支持的增加导致了开发新的检测和检测战略的努力;这样,已经确定了许多潜在的候选药物,这些药物有可能大大改善儿科结核病诊断。结核病是在撒哈拉以南非洲15岁以下儿童中进行的一项前瞻性临床研究,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 TB平台上运行(评估成人和儿童急性和突发结核病早期敏感检测的创新诊断和算法),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型检测使用非痰样本,并具有不同的检测方法:- 宿主应答(即斯泰伦博斯大学的基于细胞分裂素的生物标志物组和宿主RNA特征的评估)两种新的尿和一种粪便脂阿拉伯甘露聚糖[LAM]试验)-细胞免疫应答(T细胞活化标志物-结核病检测[TAM TB],LMU/Beckman Coulter)-核酸扩增试验(Xpert Ultra适用于不同的标本类型,例如使用新的粪便处理方案和鼻咽抽吸物)重要的是,这些新的检测方法具有很大的潜力,可以通过规避培养的需要来提高儿科病例的检测,这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,允许筛查,确认或排除怀疑患有结核病的儿童的结核病,基于同时评估单个患者队列中多项测试的研究设计。通过亚组分析(例如,基于HIV或营养状况的敏感性分析)和对各种测试序列进行建模以识别新算法,将显著加强测试性能数据。
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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