Diagnostic model for pancreatic cancer using a multi-biomarker panel
10.4174/astr.2021.100.3.144
- Author:
Yoo Jin CHOI
1
;
Woongchang YOON
;
Areum LEE
;
Youngmin HAN
;
Yoonhyeong BYUN
;
Jae Seung KANG
;
Hongbeom KIM
;
Wooil KWON
;
Young-Ah SUH
;
Yongkang KIM
;
Seungyeoun LEE
;
Junghyun NAMKUNG
;
Sangjo HAN
;
Yonghwan CHOI
;
Jin Seok HEO
;
Joon Oh PARK
;
Joo Kyung PARK
;
Song Cheol KIM
;
Chang Moo KANG
;
Woo Jin LEE
;
Taesung PARK
;
Jin-Young JANG
Author Information
1. Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
- Publication Type:ORIGINAL ARTICLE
- From:Annals of Surgical Treatment and Research
2021;100(3):144-153
- CountryRepublic of Korea
- Language:English
-
Abstract:
Purpose: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.
Methods:Individual LRG1, TTR, and CA 19-9 panels were combined into a single automated ELISA panel and tested on 728 plasma samples, including PDAC (n = 381) and normal samples (n = 347). The consistency between individual panels of 3 biomarkers and the automated multi-panel ELISA kit were accessed by correlation. The diagnostic model was developed using logistic regression according to the automated ELISA kit to predict the risk of pancreatic cancer (high-, intermediate-, and low-risk groups).
Results:The Pearson correlation coefficient of predicted values between the triple-marker automated ELISA panel and the former individual ELISA was 0.865. The proposed model provided reliable prediction results with a positive predictive value of 92.05%, negative predictive value of 90.69%, specificity of 90.69%, and sensitivity of 92.05%, which all simultaneously exceed 90% cutoff value.
Conclusion:This diagnostic model based on the triple ELISA kit showed better diagnostic performance than previous markers for PDAC. In the future, it needs external validation to be used in the clinic.
