Refining early detection of hepatocellular carcinoma: The promise of the GALAD score

Abstract

This letter discusses the original article by Villa et al, published in the World Journal of Gastroenterology. Our primary focus is on the GALAD score, its components, standardization, and population-specific variations. We also attempted to discuss the current applications of GALAD score and how combining it with imaging modalities like ultrasound could improve it. Hepatocellular carcinoma (HCC) is still one of the leading causes of cancer death, and early detection is crucial to its prognosis. Current surveillance methods, like alpha-fetoprotein (AFP) and ultrasound, are not very specific, especially when it comes to metabolic-associated steatotic liver disease. Gender, age, AFP, AFP-L3, and des-gamma-carboxy prothrombin are all included in the operator-independent, non-invasive GALAD score, which has become a promising biomarker-based diagnostic tool for HCC. Population-specific cut-points with high sensitivity and specificity have been proposed by multicenter studies like Villa et al, particularly for differentiating between HCC and cirrhosis and healthy controls. However, there is no universal threshold due to variation across etiology, population, and assay technology. GALAD must be a context-sensitive auxiliary in the clinical setting, guiding surveillance intervals and imaging choices while improving predictive performance through serial measurement. Early detection is further improved by integration with imaging modalities, such as the GALADUS score. Standardized biomarker techniques and prospective, multi-ethnic validation are required for broad clinical use and optimal HCC surveillance.

Key Words: Hepatocellular carcinoma; GALAD score; Alpha-fetoprotein; Des-gamma-carboxy prothrombin; Early detection; Biomarker algorithms; Liver cancer surveillance

Core Tip: Compared to alpha-fetoprotein (AFP) and ultrasonography alone, the GALAD score, which takes into account age, sex, AFP, AFP-L3, and des-gamma-carboxy prothrombin, shows superior diagnostic effectiveness for hepatocellular carcinoma. However, different groups have different best cut-offs, which supports the idea that a global criterion is inappropriate. Future multi-ethnic prospective studies and integration with imaging (e.g., GALADUS) are necessary for the standardized, cost-effective detection of early hepatocellular carcinoma.

TO THE EDITOR

Hepatocellular carcinoma (HCC) is still among the major causes of cancer death globally. In 2022, liver cancer was the sixth most frequently diagnosed cancer with approximately 865000 new cases and the third most common cause of cancer death with approximately 758000 deaths worldwide[1]. Treatment and prognosis continue to be largely dependent on the stage at presentation even with developments in antiviral treatment and curative surgery. Presently guidelines suggest HCC screening using abdominal ultrasound and alpha-fetoprotein (AFP) for the screening of HCC[2]. Abdominal ultrasound, the reigning corner stone of HCC surveillance now, is operator dependent and equipment quality-limited, whereas AFP is unreliable and non-specific; with the increasing worldwide burden of HCC fuelled by metabolic-associated steatotic liver disease (MASLD), there is a critical need for more accurate, non-invasive screening modalities for early diagnosis and better prognosis.

The GALAD score is a recently proposed non-invasive algorithm for HCC diagnosis that incorporates gender, age, AFP, AFP-L3, and des-gamma-carboxy prothrombin (DCP). Although it has shown promising results across multiple studies, its optimal cut-off values in cirrhotic and non-cirrhotic populations remained unclear[3-5]. The recent study “Insights into the GALAD score: A new optimal cut-off for hepatocellular carcinoma” by Villa et al[6] is discussed in this letter. It is a significant step toward increasing diagnostic accuracy through more dependable cut-offs.

GALAD score in HCC: Defining a new optimal cut-off

AFP in conjunction with ultrasound is the most widely utilized technique for the early detection of HCC. Tzartzeva et al’s meta-analysis[7] revealed that ultrasonography using AFP has a 63% sensitivity for identifying early-stage HCC. The GALAD score, a novel biomarker-based algorithm for HCC detection, is calculated using patient age, gender, and serum biomarkers (AFP, AFP-L3, and DCP) through the equation: Z = -10.08 + (0.09 × age) + (1.67 × male sex) + (2.34 × log AFP) + (0.04 × AFP-L3) + (1.33 × log DCP)[5].

In the recent issue of World Journal of Gastroenterology, published a study by Villa et al[6], “Insights into the GALAD score: A new optimal cut-off for hepatocellular carcinoma” was a prospective multicenter cross-sectional analysis that included four cohorts: Patients with cirrhosis or HCC from centers in Germany and Italy, as well as the MICOL (Multicenter Italian Cohort on Liver) population study. The eligible subjects had to be at least 18 years old, give their consent, and have maintained liver function (Child-Pugh A/B, model for end-stage liver disease < 15) for chronic liver disease (CLD) without a recent liver mass. The exclusion criteria included major comorbidities, prior transplantation, recent cancer, or warfarin therapy. Baseline data included biobanked blood samples, medical history, liver function tests, and demographics. The severity of CLD was assessed using Child-Pugh and model for end-stage liver disease scores, and it was classified as viral, alcoholic, MASLD, or other. Participants were classified as having no CLD, compensated cirrhosis, or HCC, with diagnoses and follow-up determined through blood tests and imaging in accordance with guidelines-based surveillance. The GALAD score was calculated using the established formula after serum AFP, AFP-L3, and DCP levels were measured using the Fujifilm TASWakoTM i30 analyzer.

Villa et al[6] analyze a large, multicenter cohort of 1431 subjects and show that a GALAD cut-off of -0.77 yields a sensitivity of 78.17% and a specificity of 89.55% when comparing HCC to patients with cirrhosis, while a cut-off of -1.67 achieves a sensitivity of 89.77% and a specificity of 97.59% when separating HCC from healthy controls. These results demonstrate the score’s strong diagnostic capabilities, especially in excluding HCC (high negative predictive value), and its potential to supplement or perhaps surpass current methods. These findings are noteworthy for their multicenter design, thorough statistical validation, and sizable sample size, but they are also in line with earlier smaller-scale reports. Crucially, the diagnostic performance held up well for early-stage cancers, which is the segment where monitoring biomarkers need to demonstrate their worth.

One of the study’s main advantages is the size and diversity of its multicenter cohort from Germany and Italy, which includes both population-based and hospital-based samples. This improves the findings’ external validity and generalizability. A realistic estimate of predictive performance is provided by the meticulous use of 10-fold cross-validation, which also reduces the possibility of overfitting and boosts confidence in the determined cut-offs. Crucially, the study bridges a significant gap in the clinical use of the GALAD score, namely, the lack of established reference ranges, by defining realistic thresholds, potentially enabling its integration into standard practice.

The study contains a number of shortcomings in spite of its advantages. The GALAD score cannot be evaluated in a longitudinal surveillance setting, which is the most clinically relevant context for actual HCC screening programs, due to the cross-sectional design of the study. Furthermore, the results are limited in their ability to be applied to a variety of populations because they only rely on internal validation and do not have an independent external cohort. Applicability is further limited by the lack of risk-adapted thresholds stratified by age, sex, and underlying liver disease aetiology, particularly in light of known biomarker variability influenced by hepatic functional and demographic variations. In order to better define GALAD’s ideal role, whether as a supplementary, triage, or integrated tool, within current surveillance algorithms, these limitations require cautious interpretation and emphasize the need for future prospective studies incorporating external validation, longitudinal follow-up, and etiology-specific analyses.

GALAD score cut-offs, why one threshold won’t fit all

A preliminary review of the GALAD literature reveals significant diversity in ideal thresholds and operating features by cohort, etiology, illness prevalence, and study methodology - a finding that strongly recommends against using a one-size-fits-all cutoff today. In an international non-alcoholic steatohepatitis population, Best et al[8] identified an optimal cut-off of -0.63 for the diagnosis of HCC using Milan criteria [area under the curve (AUC) 0.91; 68% sensitivity, 95% specificity]. Marsh et al[9] employed -1.36 (optimized at 82% specificity) and had 62% sensitivity 12 months previous to HCC diagnosis, outperforming AFP. Vo et al[10] found an ideal value (about -0.52) and an excellent AUC (approximately 0.91) in a cirrhosis population.

Meta-analysis shows that different research utilize different cut-offs, with -0.63 being a common but not universal cut-off[11]. However, aggregated accuracy scores still disguise heterogeneity between investigations. GALAD cut-offs vary due to differences in reference populations (HCC vs healthy vs cirrhosis), underlying etiology and stage mix, statistical targets (Youden vs sensitivity-targeting thresholds), assay/platform variability, and study design (cross-sectional vs prospective), all of which influence score distributions and best thresholds. The heterogeneity in optimal cut-offs across populations confirms that a universal GALAD threshold is currently inappropriate; interpretation must remain population-specific and assay-dependent.

Practical implications of GALAD in the current era

GALAD should be used as a context-sensitive adjunct, not as a standalone diagnostic, with higher values indicating urgent imaging or shorter surveillance intervals. Fixed global cut-offs are not indicated; instead, risk-adaptive criteria established locally for diagnosis and triage for surveillance are proposed. Standardization of the AFP-L3 and DCP tests is required for accurate interpretation. Serial measures and longitudinal trends can boost predictive power, reinforcing the importance of prospective research to guide trajectory-based decision-making.

Future perspectives

Given the heterogeneity across age, ethnicity, and underlying liver disease etiology, future research must prioritize prospective, multi-ethnic validation of the GALAD score in addition to strict standardization of biomarker assay protocols, reporting techniques, and cut-off determinations in order to maximize early HCC detection. Yang et al[12] showed that combining ultrasound with GALAD as the GALADUS score increased HCC identification (AUC 0.98, 95% sensitivity, 91% specificity), demonstrating the importance of combining biomarker algorithms with imaging. Future research should include systematic integration of GALAD with imaging modalities, such as through the GALADUS score. International agreement on reporting standards and clinical thresholds must also be informed by thorough cost-effectiveness analyses and head-to-head comparisons with newly developed biomarker panels. These initiatives are particularly crucial for directing the practical application of GALAD-based strategies in settings with limited resources and guaranteeing their clinical efficacy and global applicability.

Conclusion

Before being used more widely in the clinic, prospective multi-ethnic studies must confirm the GALAD score’s sensitivity and specificity across a number of groups, such as cirrhotic, non-alcoholic steatohepatitis/MASLD, and general populations. Standardized protocols, reporting, and thresholds are necessary due to varying etiologies, age groups, and ethnicities. Future studies should incorporate imaging into their very fabric, as well as head-to-head comparisons with developing biomarker panels and cost-effectiveness analyses. International agreement on reporting criteria and limits will help to guide implementation and improve early detection of HCC. Although the GALAD score has a lot of potential for early HCC identification, its implementation in low- and middle-income nations is hampered by restricted assay access and cost issues. Prior to normal implementation, local validation and resource-adapted solutions are required.