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Searching for New Biomarkers and the Use of Multivariate Analysis in Gastric Cancer Diagnostics
R. Kucera, D. Smid, O. Topolcan, M. Karlikova, O. Fiala, D. Slouka, T. Skalicky, V. Treska, V. Kulda, V. Simanek, M. Safanda, M. Pesta,
Jazyk angličtina Země Řecko
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
Free Medical Journals
od 2004 do Před 2 roky
Open Access Digital Library
od 2004-01-01
PubMed
27069188
Knihovny.cz E-zdroje
- MeSH
- antigeny sacharidové asociované s nádorem krev MeSH
- dospělí MeSH
- Helicobacter pylori imunologie MeSH
- imunoglobulin G krev MeSH
- infekce vyvolané Helicobacter pylori imunologie MeSH
- karcinoembryonální antigen krev MeSH
- lidé středního věku MeSH
- lidé MeSH
- matrixová metaloproteinasa 7 krev MeSH
- multivariační analýza MeSH
- nádorové biomarkery krev MeSH
- nádory žaludku krev diagnóza MeSH
- pepsinogen A krev MeSH
- protilátky bakteriální krev MeSH
- rizikové faktory MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- teoretické modely * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
AIM: The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. PATIENTS AND METHODS: We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. RESULTS: The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CONCLUSION: CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer.
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- $a Kucera, Radek $u Laboratory of Immunoanalysis, Department of Nuclear Medicine, Medical School and Teaching Hospital in Pilsen, Charles University in Prague, Pilsen, Czech Republic.
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- $a Searching for New Biomarkers and the Use of Multivariate Analysis in Gastric Cancer Diagnostics / $c R. Kucera, D. Smid, O. Topolcan, M. Karlikova, O. Fiala, D. Slouka, T. Skalicky, V. Treska, V. Kulda, V. Simanek, M. Safanda, M. Pesta,
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- $a AIM: The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. PATIENTS AND METHODS: We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. RESULTS: The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CONCLUSION: CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer.
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