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Accepted (AM)Open Access (License Unspecified), Open
Journal article
The Doylestown Algorithm: A Test to Improve the Performance of AFP in the Detection of Hepatocellular Carcinoma
Cancer prevention research (Philadelphia, Pa.), v 9(2), pp 172-179
Feb 2016
PMID: 26712941
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Biomarkers for the early diagnosis of hepatocellular carcinoma (HCC) are needed to decrease mortality from this cancer. However, as new biomarkers have been slow to be brought to clinical practice, we have developed a diagnostic algorithm that utilizes commonly used clinical measurements in those at risk of developing HCC. Briefly, as α-fetoprotein (AFP) is routinely used, an algorithm that incorporated AFP values along with four other clinical factors was developed. Discovery analysis was performed on electronic data from patients who had liver disease (cirrhosis) alone or HCC in the background of cirrhosis. The discovery set consisted of 360 patients from two independent locations. A logistic regression algorithm was developed that incorporated log-transformed AFP values with age, gender, alkaline phosphatase, and alanine aminotransferase levels. We define this as the Doylestown algorithm. In the discovery set, the Doylestown algorithm improved the overall performance of AFP by 10%. In subsequent external validation in over 2,700 patients from three independent sites, the Doylestown algorithm improved detection of HCC as compared with AFP alone by 4% to 20%. In addition, at a fixed specificity of 95%, the Doylestown algorithm improved the detection of HCC as compared with AFP alone by 2% to 20%. In conclusion, the Doylestown algorithm consolidates clinical laboratory values, with age and gender, which are each individually associated with HCC risk, into a single value that can be used for HCC risk assessment. As such, it should be applicable and useful to the medical community that manages those at risk for developing HCC.
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Details
- Title
- The Doylestown Algorithm: A Test to Improve the Performance of AFP in the Detection of Hepatocellular Carcinoma
- Creators
- Mengjun Wang - Drexel UniversityKarthik Devarajan - Fox Chase Cancer CenterAmit G Singal - The University of Texas Southwestern Medical CenterJorge A Marrero - The University of Texas Southwestern Medical CenterJianliang Dai - The University of Texas MD Anderson Cancer CenterZiding Feng - The University of Texas MD Anderson Cancer CenterJo Ann S Rinaudo - Cancer Biomarkers Research Group, Division of Cancer Prevention, NCI, Bethesda, Maryland.Sudhir Srivastava - National Institutes of HealthAlison Evans - Drexel UniversityHie-Won Hann - Thomas Jefferson UniversityYinzhi Lai - Thomas Jefferson UniversityHushan Yang - Thomas Jefferson UniversityTimothy M Block - Baruch S. Blumberg InstituteAnand Mehta - Drexel University
- Publication Details
- Cancer prevention research (Philadelphia, Pa.), v 9(2), pp 172-179
- Publisher
- American Association for Cancer Research (AACR)
- Grant note
- P30 CA016672 / NCI NIH HHS R01 CA120206 / NCI NIH HHS P30 CA006927 / NCI NIH HHS R21 CA159047 / NCI NIH HHS R03 CA153099 / NCI NIH HHS U01 CA168856 / NCI NIH HHS P30 CA 06927 / NCI NIH HHS R01 AI104636 / NIAID NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:000372006100008
- Scopus ID
- 2-s2.0-84957971663
- Other Identifier
- 991019168847804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Oncology