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通过改良加藤厚涂片法和定量聚合酶链反应检测蛔虫感染强度时的变异来源。

Sources of variability in the measurement of Ascaris lumbricoides infection intensity by Kato-Katz and qPCR.

作者信息

Easton Alice V, Oliveira Rita G, Walker Martin, O'Connell Elise M, Njenga Sammy M, Mwandawiro Charles S, Webster Joanne P, Nutman Thomas B, Anderson Roy M

机构信息

Helminth Immunology Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD, 20814, USA.

Department of Infectious Disease Epidemiology and London Centre for Neglected Tropical Disease Research (LCNTDR), Faculty of Medicine, Imperial College London St Mary's Campus, London, W2 1PG, UK.

出版信息

Parasit Vectors. 2017 May 25;10(1):256. doi: 10.1186/s13071-017-2164-y.

DOI:10.1186/s13071-017-2164-y
PMID:28545561
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5445470/
Abstract

BACKGROUND

Understanding and quantifying the sources and implications of error in the measurement of helminth egg intensity using Kato-Katz (KK) and the newly emerging "gold standard" quantitative polymerase chain reaction (qPCR) technique is necessary for the appropriate design of epidemiological studies, including impact assessments for deworming programs.

METHODS

Repeated measurements of Ascaris lumbricoides infection intensity were made from samples collected in western Kenya using the qPCR and KK techniques. These data were combined with data on post-treatment worm expulsions. Random effects regression models were used to quantify the variability associated with different technical and biological factors for qPCR and KK diagnosis. The relative precision of these methods was compared, as was the precision of multiple qPCR replicates.

RESULTS

For both KK and qPCR, intensity measurements were largely determined by the identity of the stool donor. Stool donor explained 92.4% of variability in qPCR measurements and 54.5% of observed measurement variance for KK. An additional 39.1% of variance in KK measurements was attributable to having expelled adult A. lumbricoides worms following anthelmintic treatment. For qPCR, the remaining 7.6% of variability was explained by the efficiency of the DNA extraction (2.4%), plate-to-plate variability (0.2%) and other residual factors (5%). Differences in replicate measurements by qPCR were comparatively small. In addition to KK variability based on stool donor infection levels, the slide reader was highly statistically significant, although it only explained 1.4% of the total variation. In a comparison of qPCR and KK variance to mean ratios under ideal conditions, the coefficient of variation was on average 3.6 times larger for KK highlighting increased precision of qPCR.

CONCLUSIONS

Person-to-person differences explain the majority of variability in egg intensity measurements by qPCR and KK, with very little additional variability explained by the technical factors associated with the practical implementation of these techniques. qPCR provides approximately 3.6 times more precision in estimating A. lumbricoides egg intensity than KK, and could potentially be made more cost-effective by testing each sample only once without diminishing the power of a study to assess population-level intensity and prevalence.

摘要

背景

了解并量化使用改良加藤厚涂片法(KK)和新出现的“金标准”定量聚合酶链反应(qPCR)技术测量蠕虫卵强度时误差的来源及影响,对于包括驱虫项目影响评估在内的流行病学研究的合理设计是必要的。

方法

使用qPCR和KK技术对从肯尼亚西部采集的样本中蛔虫感染强度进行重复测量。这些数据与治疗后蠕虫排出的数据相结合。随机效应回归模型用于量化与qPCR和KK诊断的不同技术和生物学因素相关的变异性。比较了这些方法的相对精密度以及多个qPCR重复测量的精密度。

结果

对于KK和qPCR,强度测量在很大程度上由粪便提供者的身份决定。粪便提供者解释了qPCR测量中92.4%的变异性以及KK观察到的测量方差的54.5%。KK测量中另外39.1%的方差可归因于驱虫治疗后排出了成年蛔虫。对于qPCR,其余(7.6%)的变异性由DNA提取效率(2.4%)、板间变异性(0.2%)和其他残留因素(5%)解释。qPCR重复测量的差异相对较小。除了基于粪便提供者感染水平的KK变异性外,玻片阅片者具有高度统计学意义,尽管其仅解释了总变异的1.4%。在理想条件下比较qPCR和KK的方差与均值比时,KK的变异系数平均大3.6倍,突出了qPCR更高的精密度。

结论

个体差异解释了qPCR和KK测量虫卵强度时的大部分变异性,与这些技术实际应用相关的技术因素解释的额外变异性非常小。在估计蛔虫卵强度方面,qPCR的精密度比KK高约3.6倍,并且通过仅对每个样本进行一次检测,在不降低研究评估人群水平强度和患病率能力的情况下,有可能提高成本效益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/a25e2f7fe9aa/13071_2017_2164_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/fa020a0e98f2/13071_2017_2164_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/24e8a2acc192/13071_2017_2164_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/a4c4ab073708/13071_2017_2164_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/13567af14931/13071_2017_2164_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/e0ef9c4e9284/13071_2017_2164_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/a25e2f7fe9aa/13071_2017_2164_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/fa020a0e98f2/13071_2017_2164_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/24e8a2acc192/13071_2017_2164_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/a4c4ab073708/13071_2017_2164_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/13567af14931/13071_2017_2164_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/e0ef9c4e9284/13071_2017_2164_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/864e/5445470/a25e2f7fe9aa/13071_2017_2164_Fig6_HTML.jpg

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