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使用全血γ-干扰素释放试验(QuantiFERON-TB Gold In-Tube)进行潜伏性结核的系列检测:一种马尔可夫模型。

Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model.

作者信息

Moses Mark W, Zwerling Alice, Cattamanchi Adithya, Denkinger Claudia M, Banaei Niaz, Kik Sandra V, Metcalfe John, Pai Madhukar, Dowdy David

机构信息

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.

Department of Medicine, UCSF, San Francisco, USA.

出版信息

Sci Rep. 2016 Jul 29;6:30781. doi: 10.1038/srep30781.

Abstract

Healthcare workers (HCWs) in low-incidence settings are often serially tested for latent TB infection (LTBI) with the QuantiFERON-TB Gold In-Tube (QFT) assay, which exhibits frequent conversions and reversions. The clinical impact of such variability on serial testing remains unknown. We used a microsimulation Markov model that accounts for major sources of variability to project diagnostic outcomes in a simulated North American HCW cohort. Serial testing using a single QFT with the recommended conversion cutoff (IFN-g > 0.35 IU/mL) resulted in 24.6% (95% uncertainty range, UR: 23.8-25.5) of the entire population testing false-positive over ten years. Raising the cutoff to >1.0 IU/mL or confirming initial positive results with a (presumed independent) second test reduced this false-positive percentage to 2.3% (95%UR: 2.0-2.6%) or 4.1% (95%UR: 3.7-4.5%), but also reduced the proportion of true incident infections detected within the first year of infection from 76.5% (95%UR: 66.3-84.6%) to 54.8% (95%UR: 44.6-64.5%) or 61.5% (95%UR: 51.6-70.9%), respectively. Serial QFT testing of HCWs in North America may result in tremendous over-diagnosis and over-treatment of LTBI, with nearly thirty false-positives for every true infection diagnosed. Using higher cutoffs for conversion or confirmatory tests (for initial positives) can mitigate these effects, but will also diagnose fewer true infections.

摘要

在低发病率地区,医护人员(HCWs)常采用全血γ干扰素释放试验(QFT)对潜伏性结核感染(LTBI)进行系列检测,该检测结果常出现反复变化。这种变异性对系列检测的临床影响尚不清楚。我们使用了一个微观模拟马尔可夫模型,该模型考虑了主要变异来源,以预测北美医护人员模拟队列中的诊断结果。使用单一QFT并采用推荐的转换临界值(IFN-g>0.35 IU/mL)进行系列检测,结果显示在十年间,整个人口中有24.6%(95%不确定范围,UR:23.8 - 25.5)检测为假阳性。将临界值提高到>1.0 IU/mL或用(假定独立的)第二次检测确认初始阳性结果,可将假阳性率降至2.3%(95%UR:2.0 - 2.6%)或4.1%(95%UR:3.7 - 4.5%),但也将感染后第一年内检测到的真正新发感染比例从76.5%(95%UR:66.3 - 84.6%)分别降至54.8%(95%UR:44.6 - 64.5%)或61.5%(95%UR:51.6 - 70.9%)。北美医护人员的系列QFT检测可能导致LTBI的大量过度诊断和过度治疗,每诊断出一例真正感染,就会出现近30例假阳性。使用更高的转换临界值或确认性检测(针对初始阳性结果)可以减轻这些影响,但也会诊断出更少的真正感染。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c864/4965809/b0704be79795/srep30781-f1.jpg

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