Open AccessDiagnostic model for pancreatic cancer using a multi-biomarker panel
Author(s) -
Yoo Jin Choi,
Woongchang Yoon,
Areum Lee,
Youngmin Han,
Yoonhyeong Byun,
Jae Seung Kang,
Hongbeom Kim,
Wooil Kwon,
Young Ah Suh,
Yongkang Kim,
Seungyeoun Lee,
Junghyun Namkung,
Sang-Hyun Han,
Y. S. Choi,
Jin Seok Heo,
Joon Oh Park,
Joo Kyung Park,
Song Cheol Kim,
Chang Moo Kang,
Woojin Lee,
Taesung Park,
Jin Young Jang
Publication year - 2021
Publication title -
annals of surgical treatment and research
Language(s) - English
Resource type - Journals
eISSN - 2288-6796
pISSN - 2288-6575
DOI - 10.4174/astr.2021.100.3.144
Subject(s) - pancreatic cancer , medicine , biomarker , logistic regression , predictive value , oncology , correlation , pancreatic ductal adenocarcinoma , cancer , biology , biochemistry , geometry , mathematics
Diagnostic biomarkers of pancreatic ductal adenocarcinoma (PDAC) have been used for early detection to reduce its dismal survival rate. However, clinically feasible biomarkers are still rare. Therefore, in this study, we developed an automated multi-marker enzyme-linked immunosorbent assay (ELISA) kit using 3 biomarkers (leucine-rich alpha-2-glycoprotein [LRG1], transthyretin [TTR], and CA 19-9) that were previously discovered and proposed a diagnostic model for PDAC based on this kit for clinical usage.