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Evaluating screening approaches for hepatocellular carcinoma in a cohort of HCV related cirrhosis patients from the Veteran’s Affairs Health Care System

Overview of attention for article published in BMC Medical Research Methodology, January 2018
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Title
Evaluating screening approaches for hepatocellular carcinoma in a cohort of HCV related cirrhosis patients from the Veteran’s Affairs Health Care System
Published in
BMC Medical Research Methodology, January 2018
DOI 10.1186/s12874-017-0458-6
Pubmed ID
Authors

Nabihah Tayob, Peter Richardson, Donna L. White, Xiaoying Yu, Jessica A. Davila, Fasiha Kanwal, Ziding Feng, Hashem B. El-Serag

Abstract

Hepatocellular carcinoma (HCC) has limited treatment options in patients with advanced stage disease and early detection of HCC through surveillance programs is a key component towards reducing mortality. The current practice guidelines recommend that high-risk cirrhosis patients are screened every six months with ultrasonography but these are done in local hospitals with variable quality leading to disagreement about the benefit of HCC surveillance. The well-established diagnostic biomarker α-Fetoprotein (AFP) is used widely in screening but the reported performance varies widely across studies. We evaluate two biomarker screening approaches, a six-month risk prediction model and a parametric empirical Bayes (PEB) algorithm, in terms of their ability to improve the likelihood of early detection of HCC compared to current AFP alone when applied prospectively in a future study. We used electronic medical records from the Department of Veterans Affairs Hepatitis C Clinical Case Registry to construct our analysis cohort, which consists of serial AFP tests in 11,222 cirrhosis control patients and 902 HCC cases prior to their HCC diagnosis. The six-month risk prediction model incorporates routinely measured laboratory tests, age, the rate of change in AFP over the past year with the current AFP. The PEB algorithm incorporates prior AFP screening values to identify patients with a significant elevated level of AFP at their current screen. We split the analysis cohort into independent training and validation datasets. All model fitting and parameter estimation was performed using the training data and the algorithm performance was assessed by applying each approach to patients in the validation dataset. When the screening-level false positive rate was set at 10%, the patient-level true positive rate using current AFP alone was 53.88% while the patient-level true positive rate for the six-month risk prediction model was 58.09% (4.21% increase) and PEB approach was 63.64% (9.76% increase). Both screening approaches identify a greater proportion of HCC cases earlier than using AFP alone. The two approaches show greater potential to improve early detection of HCC compared to using the current AFP only and are worthy of further study.

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Mendeley readers

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The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 19%
Student > Bachelor 5 12%
Other 4 9%
Student > Master 4 9%
Student > Ph. D. Student 3 7%
Other 5 12%
Unknown 14 33%
Readers by discipline Count As %
Medicine and Dentistry 8 19%
Nursing and Health Professions 3 7%
Computer Science 3 7%
Business, Management and Accounting 2 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 8 19%
Unknown 18 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 January 2018.
All research outputs
#17,925,346
of 23,015,156 outputs
Outputs from BMC Medical Research Methodology
#1,693
of 2,029 outputs
Outputs of similar age
#310,716
of 442,576 outputs
Outputs of similar age from BMC Medical Research Methodology
#43
of 53 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,029 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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