Translating From Egg- to Antigen-Based Indicators for Schistosoma mansoni Elimination Targets: A Bayesian Latent Class Analysis Study.
Translating From Egg- to Antigen-Based Indicators for Schistosoma mansoni Elimination Targets: A Bayesian Latent Class Analysis Study.
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DOI：
10.3389/fitd.2022.825721
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发表时间：
2022-02-18
期刊：
影响因子：
--
通讯作者：
Prada JM
中科院分区：
文献类型：
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作者：
Clark J;Moses A;Nankasi A;Faust CL;Adriko M;Ajambo D;Besigye F;Atuhaire A;Wamboko A;Rowel C;Carruthers LV;Francoeur R;Tukahebwa EM;Lamberton PHL;Prada JM
血吸虫病是一种寄生虫病，影响着超过2.4亿人。世界卫生组织(WHO)消除曼氏血吸虫的目标是基于Kato-Katz虫卵计数，而没有转化为广泛使用的基于尿液的循环阴极抗原诊断(POC-CCA)。我们的目标是标准化POC-CCA评分解释，并将其转换为基于加藤-卡茨的标准，扩大正在走向淘汰的诊断实用程序。贝叶斯潜伏期模型适用于210名学龄儿童在治疗前到治疗后6个月的四个时间点的数据。我们使用1)Kato-Katz和建立POC-CCA评分(否定、跟踪、+和+)，以及2)Kato-Katz和G-Score(一种新的替代POC-CCA评分(G1到G10))。我们建立了Kato-Katz计数和POC-CCA评分之间的函数关系，以及与评分相关的真正感染的概率。结合敏感度、特异度和曲线下面积来确定最佳的POC-CCA评分系统和阳性阈值。用模型估计进行参数化的模拟建立了基于抗原的消除目标。真正的感染与≥+或≥G3的POC-CCA评分有关。POC-CCA评分不能预测加藤-卡茨计数，因为低感染强度使POC-CCA盒饱和。治疗后POC-CCA的敏感性/特异性波动表明卵子排泄和抗原水平(活虫)之间的关系发生了变化。淘汰目标可以通过群体中的POC-CCA分数分布来识别。≤为2%++/+或≤为0.5%G7及以上的人口表明实现了目前以加藤加茨为基础的消除目标。人群水平的POC-CCA评分可用于在治疗前评估世卫组织消除目标。应在个人一级和治疗后谨慎行事，因为POC-CCA缺乏区分世卫组织基于加藤卡茨的中度和高强度感染类别的决心，在某些环境和评估中的使用有限。
Schistosomiasis is a parasitic disease affecting over 240-million people. World Health Organization (WHO) targets for Schistosoma mansoni elimination are based on Kato-Katz egg counts, without translation to the widely used, urine-based, point-of-care circulating cathodic antigen diagnostic (POC-CCA). We aimed to standardize POC-CCA score interpretation and translate them to Kato-Katz-based standards, broadening diagnostic utility in progress towards elimination. A Bayesian latent-class model was fit to data from 210 school-aged-children over four timepoints pre- to six-months-post-treatment. We used 1) Kato-Katz and established POC-CCA scoring (Negative, Trace, +, ++ and +++), and 2) Kato-Katz and G-Scores (a new, alternative POC-CCA scoring (G1 to G10)). We established the functional relationship between Kato-Katz counts and POC-CCA scores, and the score-associated probability of true infection. This was combined with measures of sensitivity, specificity, and the area under the curve to determine the optimal POC-CCA scoring system and positivity threshold. A simulation parametrized with model estimates established antigen-based elimination targets. True infection was associated with POC-CCA scores of ≥ + or ≥G3. POC-CCA scores cannot predict Kato-Katz counts because low infection intensities saturate the POC-CCA cassettes. Post-treatment POC-CCA sensitivity/specificity fluctuations indicate a changing relationship between egg excretion and antigen levels (living worms). Elimination targets can be identified by the POC-CCA score distribution in a population. A population with ≤2% ++/+++, or ≤0.5% G7 and above, indicates achieving current WHO Kato-Katz-based elimination targets. Population-level POC-CCA scores can be used to access WHO elimination targets prior to treatment. Caution should be exercised on an individual level and following treatment, as POC-CCAs lack resolution to discern between WHO Kato-Katz-based moderate- and high-intensity-infection categories, with limited use in certain settings and evaluations.