Use of the GALAD score for serological prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) continues to be one of the leading causes of death among cancer patients worldwide. HCC occurs in well-defined at-risk populations, with curative therapy possible only for small tumors, making it a potential target for creating new screening techniques. Imaging in conjunction with serum biomarker measurements have been the hallmark of HCC diagnosis, but have shown limited use as a surveillance tool. An objective, GALAD score is a serum biomarker-based statistical model that predicts the probability of having HCC in patients with chronic liver disease. Consisting of gender, age, AFP, AFP-L3, and des-ɤ-carboxyprothrombin (DCP), the GALAD model improves upon prior biomarker measurements by analyzing an AFP glycoform more specific to malignant tumors and HCC inflammation, and a prothrombin precursor able to differentiate HCC from non-malignant liver disease. This retrospective study is focused on validating the use of the GALAD model as a potential HCC screening tool. Patients at risk for HCC who had AFP total & L3% and DCP measurements will be included in the study. HCC diagnosis will be made by imaging criteria and/or pathology when available. Etiologies of liver disease including hepatitis B, hepatitis C, alcohol, and non-alcoholic fatty liver disease will also be recorded. Comparison with existing GALAD model results will help demonstrate GALAD’s utility as an HCC screening tool in the San Diego and international populations. Background Hepatocellular carcinoma (HCC) ranks as one of the most common types of cancer worldwide, 5 among men and 9 among women, with highest incidence among individuals aged 30-50 particularly in low-income populations (Mittal 2013, Ferlay 2015). HCC represents a dire complication of cirrhosis with risk factors that include hepatitis B and C infection, alcohol, and non-alcoholic fatty liver diseases. From 2003-2012, HCC incidence and mortality increased by 38% and 56%, making it the second leading cause of death from cancer (Group 2016). Signs and symptoms of HCC include jaundice, ascites, weight loss, nausea, abdominal pain, fatigue, or thrombocytopenia manifesting as easy bruising; however, their late-onset and nonspecific nature decrease their utility as screening signs (R 1995, Chalasani N 1999, El-Serag HB 1999). However, if detected early, HCC can be potentially cured by surgical resection, liver transplantation or local ablation (Njei B 2015). Preventive efforts, screening, surveillance, and early diagnosis are most important to improve outcome for HCC patients (Schlageter M 2014). One randomized controlled trial from China showed HCC related mortality was reduced by 37% in the surveillance arm with ultrasound and AFP every 6 months compared to the control arm with no surveillance (Zhang BH 2004). Screening and surveillance are therefore recommended in high risk patients including cirrhosis from any etiology and certain HBV patients without cirrhosis (Bruix J 2011). The recommended screening tools include ultrasound with or without use of biomarker AFP. However, ultrasound has limited sensitivity of ~60% to detect early HCC, but it is the only imaging modality proven effective in a RCT, and the only imaging modality that is cost-effective (Yu NC 2011). Unfortunately, AFP has poor sensitivity (41-65%) and specificity (80%) when used alone (Arrieta O 2007, ZHAO 2013). A literature review of studies investigating imaging alone and imaging in conjunction with serum biomarkers found the latter to be more cost-effective for identification of HCC amongst cirrhotic patients, and helped infer incidence, prevalence, and HCC risk factors (ZHAO 2013, Chang TS 2015). However, the large amount of resources utilized still yielded little benefit for overall patient survival (Ruggeri 2012, Chang TS 2015). The issues regarding cost, subjectivity, and level of expertise required to interpret images remained. Given HCC’s persistence, particularly in low-income areas, it has been imperative to develop and validate a new model for detection of HCC. Recently, a completely objective serum biomarker-based model for the detection of HCC was developed based on: gender, age, AFP, AFP-L3, and des-ɤ-carboxyprothrombin (Johnson PJ 2014, Berhane S 2016). Called “GALAD,” it has performed well in retrospective settings in patient cohorts with early disease (tumor size < 5cm) as well as advanced disease. In all cohorts, the ability to discriminate patients with HCC from chronic liver disease and hepatobiliary disease patients (defined by AUROC) was greater than 0.90 (Berhane S 2016). These early studies have largely looked at patients from the UK, Germany, Japan, and Hong Kong. With further validation in an international setting, the GALAD model has the potential to be an objective, cost-effective tool in the screening/surveillance setting. Improved screening will in turn yield earlier treatment and better prognosis for HCC patients. Definition AFP has been the most widely used serum biomarker for the early detection of HCC (Arrieta O 2007, Rodriguez-Diaz JL 2007). It is a protein produced during the embryonic period by the visceral endoderm, and later by the liver. Increased AFP production in patients have been suggested to reflect abnormal or altered liver cell regeneration. AFP levels diagnostic for HCC, as defined by the American Association for the Study of Liver Diseases is a level >200ng/mL (Trape J 2003). While these guidelines have helped diagnose HCC, particularly when combined with US results, there are limitations. The positive rate of AFP in HCC is only 60-80% leading to many false-negatives, and AFP results may be positive in other states including pregnancy, active non-HCC liver disease, and certain embryonic and gastrointestinal tumors (Farinati F 2006, Arrieta O 2007). Discovery of AFP heterogeneity and its three glycoforms (AFP-L1, AFPL2, and AFP-L3) may allow for increased sensitivity and specificity. Whereas AFP-L1 is a major glycoform in benign liver disease, AFP-L3 exists only in serum of HCC patients. Furthermore, it does not correlate with AFP allowing it to be used independently for early diagnosis of HCC (Singhal A 2012). The GALAD model was designed to make use of these serum biomarkers to better predict the probability of HCC in a patient at risk. Improving the ability to predict HCC would in turn lead to earlier diagnosis, therapy, and prognosis for a disease with growing mortality rates that is currently difficult to screen for. While early studies of GALAD have demonstrated its ability to discriminate patients with HCC from those with other liver pathology, the goal of this project is to validate the use of GALAD as a screening tool in a patient cohort in the United States (which may differ from previously studied cohorts in demographics, etiology, risk factors, etc). Additionally, we will aim to do further analysis to compare with imaging results with LIRADS (the Liver Imaging Reporting and Data System), prediction of macrovascular invasion. The student will perform an initial literature review relevant to the above goals. He will also complete the chart review in its entirety and be responsible for identifying and selecting the appropriate patients for inclusion. Additional duties will include participating in statistical analysis and interpretation of results with the help of the committee, organizing these results into a written form (abstract, poster, or manuscript) for final presentation. The proposed work will be carried out starting the summer of 2017 and finalized during the 2 months of ISP time during the fourth year of medical school. Methods The goals stated above were the foundation for the chart review. The retrospective medical chart review was conducted at UCSD Medical Center. Records for patients with chronic liver disease and AFP total, AFP L3%, and DCP measurements from March 2010 to January 2016 were included in the study. Inclusion criteria included at least one set of serum triple tumor biomarkers, and imaging/clinical follow ups. Exclusion criteria included patients who had a history of prior HCC diagnosis (diagnosis >3 months prior to first biomarker measurements) and patients with non-HCC liver malignancy. Demographic data (age, gender) was recorded. Etiologies of liver disease including Hepatitis B (HBsAg and HBV DNA), Hepatitis C (HCV Ab and HCV RNA), alcohol abuse, non-alcoholic steatohepatitis, were recorded. Patients’ BMI (body mass index) and presence of type II diabetes mellitus were also recorded. Presence of HCC diagnosis, date of diagnosis and last clinic visits, imaging results with LI-RADS categorization, staging, pathology, and lab results for total AFP, AFP-L3, DCP at baseline and follow-up visits were recorded. GALAD scores (Z) were calculated using the following equation: Z = 10.08 + 0.09 ∗ (age) + 1.67 ∗ (sex) + 2.34 ∗ log10(total AFP) +0.04 ∗ (AFPL3) + 1.33 ∗ log10(DCP) where sex = 1 for male and 0 for female. HCC probability (PrHCC) were calculated based off the GALAD scores: