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Improved biomarker performance for the detection of hepatocellular carcinoma by inclusion of clinical parameters
Journal article   Open access

Improved biomarker performance for the detection of hepatocellular carcinoma by inclusion of clinical parameters

Mengjun Wang, Timothy M. Block, Jorge Marrero, Adrian M. Di Bisceglie, Karthik Devarajan, Anand Mehta and Min Wang
Proceedings (IEEE International Conference on Bioinformatics and Biomedicine), v 2012, pp 1-5
01 Dec 2012
DOI: https://doi.org/10.1109/BIBM.2012.6392612
PMID: 24307972
url
https://doi.org/10.1016/j.polymer.2020.122644View
Accepted (AM)Open Access (License Unspecified),  Open

Abstract

biomarkers classification and regression trees Hepatitis B virus Hepatocellular Carcinoma logistic regression penalized logistic regression
We have previously identified several biomarkers of hepatocellular carcinoma (HCC). The levels of three of these biomarkers were analyzed individually and in combination with the currently used marker, alpha fetoprotein (AFP), for the ability to distinguish between a diagnosis of cirrhosis (n=113) and HCC (n=164). We have utilized several novel biostatistical tools, along with the inclusion of clinical factors such as age and gender, to determine if improved algorithms could be used to increase the probability of cancer detection. Using several of these methods, we are able to detect HCC in the background of cirrhosis with an AUC of at least 0.95. The use of clinical factors in combination with biomarker values to detect HCC is discussed.

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