GALAD Score for HCC Screening and Surveillance

Chinese expert consensus statement on the clinical application of AFP/AFP-L3%/DCP using GALAD and GALAD-like algorithm in HCC

BACKGROUND

Primary hepatocellular carcinoma (HCC) is one of the most prevalent world-wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high-risk surveillance and early diagnosis are pivotal for improving 5-year survival. Constructing the scientific non-invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow-up.

RESULTS

Based on the Chinese and international guidelines, expert consensus statements, literatures and evidence-based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple-biomarker (AFP, AFP-L3%, DCP) based GALAD, GALAD like models for liver cancer.

CONCLUSIONS

The compile of this consensus statement aims to address and push the reasonable application of the triple-biomarker (AFP, AFP-L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.

Galad Score as a Prognostic Marker for Patients with Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) accounts for more than 75% of primary liver cancers, which are the second leading cause of cancer-related deaths. The GALAD (gender, age, AFP-L3, AFP, and des-carboxy-prothrombin) score is a diagnostic tool developed based on gender, age, alpha-fetoprotein, alpha-fetoprotein L3, and des-gamma-carboxy prothrombin, originally designed as a diagnostic tool for HCC in high-risk patients.

METHODS

We analyzed 212 patients with and without cirrhosis. The population study was divided into patients with liver cirrhosis without evidence of HCC at the time of serum sample collection for GALAD score determination and patients with liver cirrhosis and a confirmed diagnosis of HCC at the time of serum sample collection for GALAD score determination. Patients were followed up until death or liver transplantation. The association between variables and HCC mortality risk was performed, and the results were presented as hazard ratio (HR). The receiver operating characteristic (ROC) curve was used to assess the performance of the GALAD HCC diagnosis. The survival probability was explored using the non-parametric test, and the equality of survival amongst categories was assessed with the log-rank test.

RESULTS

Biomarkers were higher in the HCC group compared to cirrhosis. Kaplan-Meier survival probability analysis for individual GALAD categories revealed that a high GALAD level was associated with decreased survival during follow-up, and the difference between the curves was statistically significant (p = 0.01).

CONCLUSIONS

Our findings suggest that the GALAD score has promise as a prognostic tool, with implications for improving patient management and treatment strategies for HCC.

A Statistical Approach to the Diagnosis and Prediction of HCC Using CK19 and Glypican 3 Biomarkers

Various statistical models predict the probability of developing hepatocellular carcinoma (HCC) in patients with cirrhosis, with GALAD being one of the most extensively studied scores. Biomarkers like alpha-fetoprotein (AFP), AFP-L3, and des-g-carboxyprothrombin (DCP) are widely used alone or in conjunction with ultrasound to screen for HCC. Our study aimed to compare the effectiveness of Cytokeratin 19 (CK19) and Glypican-3 (GPC3) as standalone biomarkers and in a statistical model to predict the likelihood of HCC. We conducted a monocentric prospective study involving 154 participants with previously diagnosed liver cirrhosis, divided into two groups: 95 patients with confirmed HCC based on clinical, biological, and imaging features and 59 patients without HCC. We measured the levels of AFP, AFP-L3, DCP, GPC3, and CK19 in both groups. We used univariate and multivariate statistical analyses to evaluate the ability of GPC3 and CK19 to predict the presence of HCC and incorporated them into a statistical model-the GALKA score-which was then compared to the GALAD score. AFP performed better than AFP-F3, DCP, GPC3, and CK19 in predicting the presence of HCC in our cohort. Additionally, GPC3 outperformed CK19. We used multivariate analysis to compute the GALKA score to predict the presence of HCC. Using these predictors, the following score was formulated: 0.005*AFP-L3 + 0.00069*AFP + 0.000066*GPC3 + 0.01*CK19 + 0.235*Serum Albumin-0.277. The optimal cutoff was >0.32 (AUROC = 0.98, sensitivity: 96.8%, specificity: 93%, positive predictive value-95.8%, negative predictive value-94.8%). The GALKA score had a similar predictive value to the GALAD score for the presence of HCC. In conclusion, AFP, AFP-L3, and DCP were the best biomarkers for predicting the likelihood of HCC. Our score performed well overall and was comparable to the GALAD score.

Updating the Clinical Application of Blood Biomarkers and Their Algorithms in the Diagnosis and Surveillance of Hepatocellular Carcinoma: A Critical Review

The most common primary liver cancer is hepatocellular carcinoma (HCC), and its mortality rate is increasing globally. The overall 5-year survival of patients with liver cancer is currently 10-20%. Moreover, because early diagnosis can significantly improve prognosis, which is highly correlated with tumor stage, early detection of HCC is critical. International guidelines advise using α-FP biomarker with/without ultrasonography for HCC surveillance in patients with advanced liver disease. However, traditional biomarkers are sub-optimal for risk stratification of HCC development in high-risk populations, early diagnosis, prognostication, and treatment response prediction. Since about 20% of HCCs do not produce α-FP due to its biological diversity, combining α-FP with novel biomarkers can enhance HCC detection sensitivity. There is a chance to offer promising cancer management methods in high-risk populations by utilizing HCC screening strategies derived from new tumor biomarkers and prognostic scores created by combining biomarkers with distinct clinical parameters. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker in HCC. When combined with other clinical parameters, the detection of some biomarkers has higher sensitivity and specificity in comparison with a single biomarker. Therefore, newer biomarkers and models, such as the Lens culinaris agglutinin-reactive fraction of Alpha-fetoprotein (α-FP), α-FP-L3, Des-γ-carboxy-prothrombin (DCP or PIVKA-II), and the GALAD score, are being used more frequently in the diagnosis and prognosis of HCC. Notably, the GALAD algorithm was effective in HCC prevention, particularly for cirrhotic patients, regardless of the cause of their liver disease. Although the role of these biomarkers in surveillance is still being researched, they may provide a more practical alternative to traditional imaging-based surveillance. Finally, looking for new diagnostic/surveillance tools may help improve patients' survival. This review discusses the current roles of the most used biomarkers and prognostic scores that may aid in the clinical management of HCC patients.

Circulating Biomarkers for the Early Diagnosis and Management of Hepatocellular Carcinoma with Potential Application in Resource-Limited Settings

Hepatocellular carcinoma (HCC) is among the world's third most lethal cancers. In resource-limited settings (RLS), up to 70% of HCCs are diagnosed with limited curative treatments at an advanced symptomatic stage. Even when HCC is detected early and resection surgery is offered, the post-operative recurrence rate after resection exceeds 70% in five years, of which about 50% occur within two years of surgery. There are no specific biomarkers addressing the surveillance of HCC recurrence due to the limited sensitivity of the available methods. The primary goal in the early diagnosis and management of HCC is to cure disease and improve survival, respectively. Circulating biomarkers can be used as screening, diagnostic, prognostic, and predictive biomarkers to achieve the primary goal of HCC. In this review, we highlighted key circulating blood- or urine-based HCC biomarkers and considered their potential applications in resource-limited settings, where the unmet medical needs of HCC are disproportionately highly significant.

Circulating Metabolic Markers Related to the Diagnosis of Hepatocellular Carcinoma

Primary liver carcinoma is the sixth most common cancer worldwide, while hepatocellular carcinoma (HCC) is the most dominant cancer type. Chronic hepatitis B and C virus infections and aflatoxin exposure are the main risk factors, while nonalcoholic fatty liver disease caused by obesity, diabetes, and metabolic syndrome are the more common risk factors for HCC. Metabolic disorders caused by these high-risk factors are closely related to the tumor microenvironment of HCC, revealing a possible cause-and-effect relationship between the two. These metabolic disorders involve many complex metabolic pathways, such as carbohydrate, lipid, lipid derivative, amino acid, and amino acid derivative metabolic processes. The resulting metabolites with significant abnormal changes in the concentration level in circulating blood may be used as biomarkers to guide the diagnosis, treatment, or prognosis of HCC. At present, there are high-throughput technologies that can quickly detect small molecular metabolites in many samples. Compared to tissue biopsy, blood samples are easier to obtain, and patients' willingness to participate is higher, which makes it possible to study blood HCC biomarkers. Over the past few years, a substantial body of research has been performed worldwide, and other potential biomarkers have been identified. Unfortunately, due to the limitations of each study, only a few markers have been widely verified and are suitable for clinical use. This review briefly summarizes the potential blood metabolic markers related to the diagnosis of HCC, mainly focusing on amino acids and their derivative metabolism, lipids and their derivative metabolism, and other possible related metabolisms.