Improve discrimination power of serum markers for diagnosis of cholangiocarcinoma using data mining-based approach

Sirorat Pattanapairoj; Atit Silsirivanit; Kanha Muisuk; Wunchana Seubwai; Ubon Cha'on; Kulthida Vaeteewoottacharn; Kanlayanee Sawanyawisuth; Danaipong Chetchotsak; Sopit Wongkham

doi:10.1016/j.clinbiochem.2015.03.022

Improve discrimination power of serum markers for diagnosis of cholangiocarcinoma using data mining-based approach

Clin Biochem. 2015 Jul;48(10-11):668-73. doi: 10.1016/j.clinbiochem.2015.03.022. Epub 2015 Apr 9.

Authors

Sirorat Pattanapairoj¹, Atit Silsirivanit², Kanha Muisuk³, Wunchana Seubwai³, Ubon Cha'on², Kulthida Vaeteewoottacharn², Kanlayanee Sawanyawisuth², Danaipong Chetchotsak⁴, Sopit Wongkham⁵

Affiliations

¹ Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand; System Modeling for Industry Research Group, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand.
² Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Liver Fluke and Cholangiocarcinoma Research Center, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
³ Department of Forensic Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Liver Fluke and Cholangiocarcinoma Research Center, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
⁴ Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand; System Modeling for Industry Research Group, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand. Electronic address: [email protected].
⁵ Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Liver Fluke and Cholangiocarcinoma Research Center, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand. Electronic address: [email protected].

PMID: 25863112
DOI: 10.1016/j.clinbiochem.2015.03.022

Abstract

Objective: Cholangiocarcinoma (CCA) is usually fatal because of the absence of tests for early detection and lack of effective therapy. Tumor markers with adequate diagnostic values are of clinical significance. This study is aimed to improve the diagnostic power of serum markers using the computational data mining technique to develop a combined diagnostic model that yielded the best diagnostic values for CCA.

Design and methods: Eight CCA-associated markers-carcinoembryonic antigen, carbohydrate antigen 19-9, alkaline phosphatase (ALP), and gamma glutamyl transferase, biliary-ALP, mucin5AC, CCA-associated carbohydrate antigen (CCA-CA) and CA-S27-were used as the inputs for the C4.5 decision tree classification model and the selected model was confirmed by ANN analyses. Eight serum markers for CCA were determined in the training set of 85 histologically proven-CCA patients and 82 control subjects. The chosen set of combined markers that gave the best diagnostic values for CCA was then validated in the testing set of 22 CCA patients and 60 controls.

Results: A decision tree diagram built by the C4.5 algorithm suggested the serial analysis of CCA-CA and ALP for distinguishing CCA patients from non-CCA subjects with all diagnostic parameters ≥95%. The combined tests showed a precise diagnosis in the testing set.

Conclusions: The C4.5 model indicates the combined markers of CCA-CA and ALP that produced the more precise diagnosis for CCA.

Keywords: ALP; C4.5 decision tree; Combined analysis; Hepatobiliary; Mucin; Single neural network; Tumor markers.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Bile Duct Neoplasms / blood*
Bile Duct Neoplasms / diagnosis*
Biomarkers, Tumor / blood*
Cholangiocarcinoma / blood*
Cholangiocarcinoma / diagnosis*
Data Mining / methods*
Female
Humans
Male
Middle Aged

Substances

Biomarkers, Tumor