DocumentCode
583223
Title
Improved biomarker performance for the detection of hepatocellular carcinoma by inclusion of clinical parameters
Author
Wang, Mengjun ; Block, Timothy M. ; Marrero, Jorge ; Bisceglie, Adrian M Di ; Devarajan, Karthik ; Mehta, Anand
Author_Institution
Drexel Univ. Coll. of Med., Doylestown, PA, USA
fYear
2012
fDate
4-7 Oct. 2012
Firstpage
1
Lastpage
5
Abstract
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 detection of cancer. 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.
Keywords
biomedical materials; cancer; liver; medical computing; molecular biophysics; patient diagnosis; proteins; regression analysis; HCC diagnosis; alpha fetoprotein; cancer detection; cirrhosis diagnosis; hepatocellular carcinoma detection; improved algorithms; improved biomarker performance; inclusion clinical parameters; probability; Biological system modeling; Cancer; Data models; Educational institutions; Logistics; Predictive models; Regression tree analysis; Hepatitis B virus; Hepatocellular Carcinoma; biomarkers; classification and regression trees; logistic regression; penalized logistic regression;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on
Conference_Location
Philadelphia, PA
Print_ISBN
978-1-4673-2559-2
Electronic_ISBN
978-1-4673-2558-5
Type
conf
DOI
10.1109/BIBM.2012.6392612
Filename
6392612
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