Sarah Berhane1, Hidenori Toyoda2, Toshifumi Tada2, Takashi Kumada2, Chiaki Kagebayashi3, Shinji Satomura3, Nora Schweitzer4, Arndt Vogel4, Michael P Manns4, Julia Benckert5, Thomas Berg5, Maria Ebker6, Jan Best7, Alexander Dechêne7, Guido Gerken7, Joerg F Schlaak8, Arndt Weinmann9, Marcus A Wörns9, Peter Galle10, Winnie Yeo11, Frankie Mo11, Stephen L Chan11, Helen Reeves12, Trevor Cox13, Philip Johnson14. 1. Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom. 2. Department of Gastroenterology and Hepatology, Ogaki Municipal Hospital, Gifu, Japan. 3. Wako Life Sciences, Inc, Mountain View, California. 4. Clinic of Gastroenterology, Hepatology and Endocrinology, Hannover Medical High School, Hannover, Germany. 5. Department of Gastroenterology and Rheumatology, Section of Hepatology, University Hospital, Leipzig, Germany. 6. Universität Leipzig, Referat Lehre Medizin, Leipzig, Germany. 7. Department of Gastroenterology and Hepatology, University Hospital Essen, University Duisburg-Essen, Essen, Germany. 8. Department of Gastroenterology and Hepatology, Evangelisches Krankenhaus Duisburg-Nord, Duisburg, Germany. 9. Department of Medicine I, University Medical Center Johannes Gutenberg University, Mainz, Germany; Clinical Registry Unit, University Medical Center Johannes Gutenberg University, Mainz, Germany. 10. Department of Medicine I, University Medical Center Johannes Gutenberg University, Mainz, Germany. 11. State Key Laboratory in Oncology in South China, Sir Y. K. Pao Centre for Cancer, Department of Clinical Oncology, Chinese University of Hong Kong, Hong Kong Cancer Institute, Hong Kong, China. 12. Northern Institute for Cancer Research, Medical School, Newcastle upon Tyne, United Kingdom; The Hepatopancreatobiliary Multidisciplinary Team, Newcastle upon Tyne NHS Foundation Trust, The Freeman Hospital, Newcastle upon Tyne, Tyne and Wear, United Kingdom. 13. Liverpool Cancer Research UK Centre, Liverpool Cancer Trials Unit, University of Liverpool, Liverpool, United Kingdom. 14. Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom; The Clatterbridge Cancer Centre NHS Foundation Trust, Bebington, Wirral, United Kingdom. Electronic address: Philip.Johnson@liverpool.ac.uk.
Abstract
BACKGROUND & AIMS: GALAD and BALAD-2 are statistical models for estimating the likelihood of the presence of hepatocellular carcinoma (HCC) in individual patients with chronic liver disease and the survival of patients with HCC, respectively. Both models use objective measures, particularly the serum markers α-fetoprotein (AFP), AFP-L3, and des-γ-carboxyprothrombin. We aimed to validate these models in an international cohort of patients with HCC and assess their clinical performance. METHODS: We collected data on cancer diagnosis and outcomes of 6834 patients (2430 with HCC and 4404 with chronic liver disease) recruited from Germany, Japan, and Hong Kong. We also collected data from 229 patients with other hepatobiliary tract cancers (cholangiocarcinoma or pancreatic adenocarcinoma) and 92 healthy individuals (controls). For reference, the original UK cohort (on which the GALAD model initially was built and BALAD-2 was validated) was included in the analysis. We assessed the effects of tumor size and etiology on GALAD model performance, and its ability to correctly discriminate HCC from other hepatobiliary cancers. We assessed the performance of BALAD-2 in patients with different stages of HCC. RESULTS: In all cohorts, the area under the receiver operating characteristic curve (AUROC), quantifying the ability of GALAD to discriminate patients with HCC from patients with chronic liver disease, was greater than 0.90-similar to the series on which the model originally was built (AUROC, 0.97). GALAD discriminated patients with HCC from those with other hepatobiliary cancers with an AUROC value of 0.95; values were slightly lower for patients with small unifocal HCCs, ranging from 0.85 to 0.95. Etiology and treatment of chronic viral hepatitis had no effect on the performance of this model. BALAD-2 analysis assigned patients with HCC to 4 distinct prognostic groups-overall and when patients were stratified according to disease stage. CONCLUSIONS: We validated the performance of the GALAD and BALAD-2 models for the diagnosis of HCC and predicting patient survival, respectively (based on levels of the serum markers AFP, AFP-L3, and des-γ-carboxyprothrombin), in an international cohort of almost 7000 patients. These systems might be used in HCC surveillance and determination of patient prognosis.
BACKGROUND & AIMS: GALAD and BALAD-2 are statistical models for estimating the likelihood of the presence of hepatocellular carcinoma (HCC) in individual patients with chronic liver disease and the survival of patients with HCC, respectively. Both models use objective measures, particularly the serum markers α-fetoprotein (AFP), AFP-L3, and des-γ-carboxyprothrombin. We aimed to validate these models in an international cohort of patients with HCC and assess their clinical performance. METHODS: We collected data on cancer diagnosis and outcomes of 6834 patients (2430 with HCC and 4404 with chronic liver disease) recruited from Germany, Japan, and Hong Kong. We also collected data from 229 patients with other hepatobiliary tract cancers (cholangiocarcinoma or pancreatic adenocarcinoma) and 92 healthy individuals (controls). For reference, the original UK cohort (on which the GALAD model initially was built and BALAD-2 was validated) was included in the analysis. We assessed the effects of tumor size and etiology on GALAD model performance, and its ability to correctly discriminate HCC from other hepatobiliary cancers. We assessed the performance of BALAD-2 in patients with different stages of HCC. RESULTS: In all cohorts, the area under the receiver operating characteristic curve (AUROC), quantifying the ability of GALAD to discriminate patients with HCC from patients with chronic liver disease, was greater than 0.90-similar to the series on which the model originally was built (AUROC, 0.97). GALAD discriminated patients with HCC from those with other hepatobiliary cancers with an AUROC value of 0.95; values were slightly lower for patients with small unifocal HCCs, ranging from 0.85 to 0.95. Etiology and treatment of chronic viral hepatitis had no effect on the performance of this model. BALAD-2 analysis assigned patients with HCC to 4 distinct prognostic groups-overall and when patients were stratified according to disease stage. CONCLUSIONS: We validated the performance of the GALAD and BALAD-2 models for the diagnosis of HCC and predicting patient survival, respectively (based on levels of the serum markers AFP, AFP-L3, and des-γ-carboxyprothrombin), in an international cohort of almost 7000 patients. These systems might be used in HCC surveillance and determination of patient prognosis.
Authors: Kelly A Borges; Jianliang Dai; Neehar D Parikh; Myron Schwartz; Mindie H Nguyen; Lewis R Roberts; Alex S Befeler; Sudhir Srivastava; Jo Ann Rinaudo; Ziding Feng; Jorge A Marrero; K Rajender Reddy Journal: Contemp Clin Trials Date: 2018-11-12 Impact factor: 2.226