Cut-off optimization for 13C-urea breath test in a community-based trial by mathematic, histology and serology approach View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Zhe-Xuan Li, Lei-Lei Huang, Cong Liu, Luca Formichella, Yang Zhang, Yu-Mei Wang, Lian Zhang, Jun-Ling Ma, Wei-Dong Liu, Kurt Ulm, Jian-Xi Wang, Lei Zhang, Monther Bajbouj, Ming Li, Michael Vieth, Michael Quante, Tong Zhou, Le-Hua Wang, Stepan Suchanek, Erwin Soutschek, Roland Schmid, Meinhard Classen, Wei-Cheng You, Markus Gerhard, Kai-Feng Pan

ABSTRACT

The performance of diagnostic tests in intervention trials of Helicobacter pylori (H.pylori) eradication is crucial, since even minor inaccuracies can have major impact. To determine the cut-off point for 13C-urea breath test (13C-UBT) and to assess if it can be further optimized by serologic testing, mathematic modeling, histopathology and serologic validation were applied. A finite mixture model (FMM) was developed in 21,857 subjects, and an independent validation by modified Giemsa staining was conducted in 300 selected subjects. H.pylori status was determined using recomLine H.pylori assay in 2,113 subjects with a borderline 13C-UBT results. The delta over baseline-value (DOB) of 3.8 was an optimal cut-off point by a FMM in modelling dataset, which was further validated as the most appropriate cut-off point by Giemsa staining (sensitivity = 94.53%, specificity = 92.93%). In the borderline population, 1,468 subjects were determined as H.pylori positive by recomLine (69.5%). A significant correlation between the number of positive H.pylori serum responses and DOB value was found (rs = 0.217, P < 0.001). A mathematical approach such as FMM might be an alternative measure in optimizing the cut-off point for 13C-UBT in community-based studies, and a second method to determine H.pylori status for subjects with borderline value of 13C-UBT was necessary and recommended. More... »

PAGES

2072

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-017-02180-7

DOI

http://dx.doi.org/10.1038/s41598-017-02180-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085430984

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28522798


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