The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers

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The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers. / Johnson, Philip J; Pirrie, Sarah J; Cox, Trevor F; Berhane, Sarah; Teng, Mabel; Palmer, Daniel; Morse, Janet; Hull, Diana; Patman, Gillian; Kagebayashi, Chiaki; Hussain, Syed; Graham, Janine; Reeves, Helen; Satomura, Shinji.

In: Cancer Epidemiology, Biomarkers & Prevention, Vol. 23, No. 1, 01.2014, p. 144-153.

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Johnson, Philip J ; Pirrie, Sarah J ; Cox, Trevor F ; Berhane, Sarah ; Teng, Mabel ; Palmer, Daniel ; Morse, Janet ; Hull, Diana ; Patman, Gillian ; Kagebayashi, Chiaki ; Hussain, Syed ; Graham, Janine ; Reeves, Helen ; Satomura, Shinji. / The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers. In: Cancer Epidemiology, Biomarkers & Prevention. 2014 ; Vol. 23, No. 1. pp. 144-153.

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@article{899a3655f57f48f18439f57dc7adea74,
title = "The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers",
abstract = "BACKGROUND: Hepatocellular carcinoma is a common complication of chronic liver disease (CLD), and is conventionally diagnosed by radiological means. We aimed to build a statistical model that could determine the risk of hepatocellular carcinoma in individual patients with CLD using objective measures, particularly serological tumor markers.METHODS: A total of 670 patients with either CLD alone or hepatocellular carcinoma were recruited from a single UK center into a case-control study. Sera were collected prospectively and specifically for this study. A logistic regression analysis was used to determine independent factors associated with hepatocellular carcinoma and a model built and assessed in terms of sensitivity, specificity, and proportion of correct diagnoses.RESULTS: The final model involving gender, age, AFP-L3, α fetoprotein (AFP), and des-carboxy-prothrombin ({"}GALAD{"}) was developed in a {"}discovery{"} data set and validated in independent data sets both from the same institution and from an external institution. When optimized for sensitivity and specificity, the model gave values of more than 0.88 irrespective of the disease stage.CONCLUSIONS: The presence of hepatocellular carcinoma can be detected in patients with CLD on the basis of a model involving objective clinical and serological factors. It is now necessary to test the model's performance in a prospective manner and in a routine clinical practice setting, to determine if it may replace or, more likely, enhance current radiological approaches.IMPACT: Our data provide evidence that an entirely objective serum biomarker-based model may facilitate the detection and diagnosis of hepatocellular carcinoma and form the basis for a prospective study comparing this approach with the standard radiological approaches.",
keywords = "Aged, Biomarkers, Tumor, Carcinoma, Hepatocellular, Case-Control Studies, Female, Humans, Liver Neoplasms, Logistic Models, Male, Middle Aged, Prospective Studies, Reproducibility of Results",
author = "Johnson, {Philip J} and Pirrie, {Sarah J} and Cox, {Trevor F} and Sarah Berhane and Mabel Teng and Daniel Palmer and Janet Morse and Diana Hull and Gillian Patman and Chiaki Kagebayashi and Syed Hussain and Janine Graham and Helen Reeves and Shinji Satomura",
year = "2014",
month = jan,
doi = "10.1158/1055-9965.EPI-13-0870",
language = "English",
volume = "23",
pages = "144--153",
journal = "Cancer Epidemiology, Biomarkers & Prevention",
issn = "1055-9965",
publisher = "American Association for Cancer Research",
number = "1",

}

RIS

TY - JOUR

T1 - The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers

AU - Johnson, Philip J

AU - Pirrie, Sarah J

AU - Cox, Trevor F

AU - Berhane, Sarah

AU - Teng, Mabel

AU - Palmer, Daniel

AU - Morse, Janet

AU - Hull, Diana

AU - Patman, Gillian

AU - Kagebayashi, Chiaki

AU - Hussain, Syed

AU - Graham, Janine

AU - Reeves, Helen

AU - Satomura, Shinji

PY - 2014/1

Y1 - 2014/1

N2 - BACKGROUND: Hepatocellular carcinoma is a common complication of chronic liver disease (CLD), and is conventionally diagnosed by radiological means. We aimed to build a statistical model that could determine the risk of hepatocellular carcinoma in individual patients with CLD using objective measures, particularly serological tumor markers.METHODS: A total of 670 patients with either CLD alone or hepatocellular carcinoma were recruited from a single UK center into a case-control study. Sera were collected prospectively and specifically for this study. A logistic regression analysis was used to determine independent factors associated with hepatocellular carcinoma and a model built and assessed in terms of sensitivity, specificity, and proportion of correct diagnoses.RESULTS: The final model involving gender, age, AFP-L3, α fetoprotein (AFP), and des-carboxy-prothrombin ("GALAD") was developed in a "discovery" data set and validated in independent data sets both from the same institution and from an external institution. When optimized for sensitivity and specificity, the model gave values of more than 0.88 irrespective of the disease stage.CONCLUSIONS: The presence of hepatocellular carcinoma can be detected in patients with CLD on the basis of a model involving objective clinical and serological factors. It is now necessary to test the model's performance in a prospective manner and in a routine clinical practice setting, to determine if it may replace or, more likely, enhance current radiological approaches.IMPACT: Our data provide evidence that an entirely objective serum biomarker-based model may facilitate the detection and diagnosis of hepatocellular carcinoma and form the basis for a prospective study comparing this approach with the standard radiological approaches.

AB - BACKGROUND: Hepatocellular carcinoma is a common complication of chronic liver disease (CLD), and is conventionally diagnosed by radiological means. We aimed to build a statistical model that could determine the risk of hepatocellular carcinoma in individual patients with CLD using objective measures, particularly serological tumor markers.METHODS: A total of 670 patients with either CLD alone or hepatocellular carcinoma were recruited from a single UK center into a case-control study. Sera were collected prospectively and specifically for this study. A logistic regression analysis was used to determine independent factors associated with hepatocellular carcinoma and a model built and assessed in terms of sensitivity, specificity, and proportion of correct diagnoses.RESULTS: The final model involving gender, age, AFP-L3, α fetoprotein (AFP), and des-carboxy-prothrombin ("GALAD") was developed in a "discovery" data set and validated in independent data sets both from the same institution and from an external institution. When optimized for sensitivity and specificity, the model gave values of more than 0.88 irrespective of the disease stage.CONCLUSIONS: The presence of hepatocellular carcinoma can be detected in patients with CLD on the basis of a model involving objective clinical and serological factors. It is now necessary to test the model's performance in a prospective manner and in a routine clinical practice setting, to determine if it may replace or, more likely, enhance current radiological approaches.IMPACT: Our data provide evidence that an entirely objective serum biomarker-based model may facilitate the detection and diagnosis of hepatocellular carcinoma and form the basis for a prospective study comparing this approach with the standard radiological approaches.

KW - Aged

KW - Biomarkers, Tumor

KW - Carcinoma, Hepatocellular

KW - Case-Control Studies

KW - Female

KW - Humans

KW - Liver Neoplasms

KW - Logistic Models

KW - Male

KW - Middle Aged

KW - Prospective Studies

KW - Reproducibility of Results

U2 - 10.1158/1055-9965.EPI-13-0870

DO - 10.1158/1055-9965.EPI-13-0870

M3 - Article

C2 - 24220911

VL - 23

SP - 144

EP - 153

JO - Cancer Epidemiology, Biomarkers & Prevention

JF - Cancer Epidemiology, Biomarkers & Prevention

SN - 1055-9965

IS - 1

ER -