• Something wrong with this record ?

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

ZX. Li, LL. Huang, C. Liu, L. Formichella, Y. Zhang, YM. Wang, L. Zhang, JL. Ma, WD. Liu, K. Ulm, JX. Wang, L. Zhang, M. Bajbouj, M. Li, M. Vieth, M. Quante, T. Zhou, LH. Wang, S. Suchanek, E. Soutschek, R. Schmid, M. Classen, WC. You, M....

. 2017 ; 7 (1) : 2072. [pub] 20170518

Language English Country England, Great Britain

Document type Journal Article, Research Support, Non-U.S. Gov't, Validation Study

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.

References provided by Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc19001255
003      
CZ-PrNML
005      
20191118124424.0
007      
ta
008      
190107s2017 enk f 000 0|eng||
009      
AR
024    7_
$a 10.1038/s41598-017-02180-7 $2 doi
035    __
$a (PubMed)28522798
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a enk
100    1_
$a Li, Zhe-Xuan $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
245    10
$a Cut-off optimization for 13C-urea breath test in a community-based trial by mathematic, histology and serology approach / $c ZX. Li, LL. Huang, C. Liu, L. Formichella, Y. Zhang, YM. Wang, L. Zhang, JL. Ma, WD. Liu, K. Ulm, JX. Wang, L. Zhang, M. Bajbouj, M. Li, M. Vieth, M. Quante, T. Zhou, LH. Wang, S. Suchanek, E. Soutschek, R. Schmid, M. Classen, WC. You, M. Gerhard, KF. Pan,
520    9_
$a 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.
650    _2
$a dospělí $7 D000328
650    12
$a algoritmy $7 D000465
650    _2
$a dechové testy $x metody $7 D001944
650    _2
$a izotopy uhlíku $7 D002247
650    _2
$a klinické zkoušky jako téma $7 D002986
650    _2
$a ženské pohlaví $7 D005260
650    _2
$a infekce vyvolané Helicobacter pylori $x diagnóza $7 D016481
650    _2
$a lidé $7 D006801
650    _2
$a limita detekce $7 D057230
650    _2
$a mužské pohlaví $7 D008297
650    _2
$a lidé středního věku $7 D008875
650    _2
$a teoretické modely $7 D008962
650    _2
$a diagnostické techniky molekulární $x normy $7 D025202
650    _2
$a nádory žaludku $x diagnóza $x mikrobiologie $7 D013274
650    _2
$a močovina $7 D014508
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
655    _2
$a validační studie $7 D023361
700    1_
$a Huang, Lei-Lei $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Liu, Cong $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Formichella, Luca $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany.
700    1_
$a Zhang, Yang $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Wang, Yu-Mei $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Zhang, Lian $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Ma, Jun-Ling $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Liu, Wei-Dong $u Healthy Bureau of Linqu County, Shandong, China.
700    1_
$a Ulm, Kurt $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany.
700    1_
$a Wang, Jian-Xi $u Healthy Bureau of Linqu County, Shandong, China.
700    1_
$a Zhang, Lei $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Bajbouj, Monther $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany.
700    1_
$a Li, Ming $u Healthy Bureau of Linqu County, Shandong, China.
700    1_
$a Vieth, Michael $u Institute of Pathology, Klinikum Bayreuth, Preuschwitzer Str. 101, 95445, Bayreuth, Germany.
700    1_
$a Quante, Michael $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany.
700    1_
$a Zhou, Tong $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Wang, Le-Hua $u Healthy Bureau of Linqu County, Shandong, China.
700    1_
$a Suchanek, Stepan $u Charles University, Central Military Hospital Prague, Ovocný trh 3-5, Prague, 11636, Czech Republic.
700    1_
$a Soutschek, Erwin $u Mikrogen GmbH, Floriansbogen 2-4, Neuried, Munich, 82061, Germany.
700    1_
$a Schmid, Roland $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany.
700    1_
$a Classen, Meinhard, $d 1936-2019 $7 nlk20030128123 $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany. International Digestive Cancer Alliance, 81541, Munich, Germany.
700    1_
$a You, Wei-Cheng $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China.
700    1_
$a Gerhard, Markus $u Technische Universität München, Klinikum rechts der Isar, Trogerstr. 30, 81675, Munich, Germany. Markus.Gerhard@tum.de. German Centre of Infection Research, partner site Munich, Munich, Germany. Markus.Gerhard@tum.de.
700    1_
$a Pan, Kai-Feng $u Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fu-cheng Road, Hai-dian District, Beijing, 100142, China. pankaifeng2002@yahoo.com.
773    0_
$w MED00182195 $t Scientific reports $x 2045-2322 $g Roč. 7, č. 1 (2017), s. 2072
856    41
$u https://pubmed.ncbi.nlm.nih.gov/28522798 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y a $z 0
990    __
$a 20190107 $b ABA008
991    __
$a 20191118124705 $b ABA008
999    __
$a ok $b bmc $g 1365145 $s 1039378
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2017 $b 7 $c 1 $d 2072 $e 20170518 $i 2045-2322 $m Scientific reports $n Sci Rep $x MED00182195
LZP    __
$a Pubmed-20190107

Find record

Citation metrics

Loading data ...

Archiving options

Loading data ...