Amsterdam Institute for Global Health and Development (AIGHD), Amsterdam, The Netherlands ; Department of Global Health, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
Social and Mathematical Epidemiology Group (SAME), Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
PLoS One. 2013 Dec 18;8(12):e82786. doi: 10.1371/journal.pone.0082786. eCollection 2013.
High costs are a limitation to scaling up the Xpert MTB/RIF assay (Xpert) for the diagnosis of tuberculosis in resource-constrained settings. A triaging strategy in which a sensitive but not necessarily highly specific rapid test is used to select patients for Xpert may result in a more affordable diagnostic algorithm. To inform the selection and development of particular diagnostics as a triage test we explored combinations of sensitivity, specificity and cost at which a hypothetical triage test will improve affordability of the Xpert assay.
In a decision analytical model parameterized for Uganda, India and South Africa, we compared a diagnostic algorithm in which a cohort of patients with presumptive TB received Xpert to a triage algorithm whereby only those with a positive triage test were tested by Xpert.
A triage test with sensitivity equal to Xpert, 75% specificity, and costs of US$5 per patient tested reduced total diagnostic costs by 42% in the Uganda setting, and by 34% and 39% respectively in the India and South Africa settings. When exploring triage algorithms with lower sensitivity, the use of an example triage test with 95% sensitivity relative to Xpert, 75% specificity and test costs $5 resulted in similar cost reduction, and was cost-effective by the WHO willingness-to-pay threshold compared to Xpert for all in Uganda, but not in India and South Africa. The gain in affordability of the examined triage algorithms increased with decreasing prevalence of tuberculosis among the cohort.
A triage test strategy could potentially improve the affordability of Xpert for TB diagnosis, particularly in low-income countries and with enhanced case-finding. Tests and markers with lower accuracy than desired of a diagnostic test may fall within the ranges of sensitivity, specificity and cost required for triage tests and be developed as such.
在资源有限的环境中,推广 Xpert MTB/RIF 检测(Xpert)来诊断结核病的成本较高。采用一种敏感性但不一定高度特异性的快速检测方法对患者进行分诊的策略,可能会使诊断算法更具成本效益。为了选择和开发特定的诊断方法作为分诊检测,我们探索了在何种敏感性、特异性和成本条件下,假设的分诊检测会提高 Xpert 检测的可负担性。
在一个针对乌干达、印度和南非的决策分析模型中,我们比较了一种诊断算法,即对疑似结核病患者进行 Xpert 检测,以及一种分诊算法,即仅对阳性分诊检测的患者进行 Xpert 检测。
在乌干达,一种与 Xpert 检测具有相同敏感性(75%)、特异性(75%)、检测成本为 5 美元/例的分诊检测,可使总诊断成本降低 42%;在印度和南非,其分别降低 34%和 39%。当我们探索敏感性较低的分诊算法时,使用一种与 Xpert 检测相比具有 95%敏感性、75%特异性和 5 美元检测成本的示例分诊检测,可使成本降低类似幅度,并且在乌干达,与 Xpert 相比,所有情况下均符合世卫组织的支付意愿阈值,具有成本效益,但在印度和南非则不然。所考察的分诊算法的可负担性提高幅度随着队列中结核病的流行率降低而增加。
分诊检测策略可能会提高 Xpert 检测诊断结核病的可负担性,特别是在低收入国家和增强病例发现的情况下。那些准确性不如诊断检测所需的检测和标志物,可能在敏感性、特异性和成本方面符合分诊检测的要求,并以此作为开发的基础。