Given this, it becomes crucial to identify those patients who are at a higher risk of developing HCC, to ensure they receive timely and effective care. Effective risk stratification can play a pivotal role in this regard, allowing for HCC surveillance and potentially improving outcomes. In this context, a meta-analysis by Jin et al. [6] has provided interesting insights on the efficacy of transient elastography (TE) as a non-invasive test (NIT) for predicting HCC development in this patient population.

TE performed using the Fibroscan is a well validated NIT for assessing liver fibrosis in CHB [7] and is recommended in various guidelines [3,8]. TE measures liver stiffness in kPa, providing a quantitative evaluation of the extent of the liver fibrosis.

In their systematic review and meta-analysis, Jin and colleagues identified 10 studies (including a total of 18,150 patients) that assessed the risk of HCC development and used TE for stratifying liver fibrosis in CHB patients. Seven of these studies were retrospective and three were prospective. Antiviral treatment was received by all patients in four studies and by some in the remaining six. There were no data on HBeAg status and viral load and/or viral suppression. Remarkably, all studies were performed in Asia, and nine of them were performed in South Korea. According to the results of the meta-analysis, the authors found that a liver stiffness measurement (LSM) of ≥11 kPa was associated with a hazard ratio (HR) of 3.3 for the development of HCC, thus providing a practical cut-off for identifying high-risk patients [6]. This finding is potentially important for refining surveillance strategies and improving CHB patient outcomes.

Although the results are important, there are also limitations that need to be taken into account. The fact that all included studies came from Asia, raises questions about the generalizability of these findings to other populations. A critical aspect not considered in the analysis was the duration of antiviral treatment, which is inversely correlated with the risk of HCC. Prolonged antiviral therapy has been shown to reduce HCC risk in CHB patients [9], and also the specific antiviral molecule used in therapy can have a role [10], consequently these variables could significantly influence the study outcomes. Additionally, the meta-analysis did not consider the HBeAg status, which is a known risk factor for HCC [1,3], which further complicates the interpretation of the results. Thus, it is difficult to interpret the finding that the HR for HCC development was higher in the studies where all patients received antiviral treatment compared to the studies where only a subset of patients were receiving treatment. Finally, the lack of randomized controlled trials (RCTs) and the presence of potential confounders in retrospective studies are also factors that suggest caution in interpreting these results. For instance, the attributable risk conferred by alcohol misuse or the presence of metabolic risk factors could not be quantified.

Regarding the use of TE as a predictive tool, the sensitivity and specificity (61% and 78%) of the 11 kPa cut-offs were rather moderate which means that it cannot be used as a standalone test but needs to be complemented by other prognostic methods or incorporated in existing HCC prediction scores (Fig. 1). Combining TE with other established HCC prediction factors for CHB patients, such as age, gender, platelets count, diabetic status, HBV DNA levels, could enhance the accuracy of predicting which CHB patients are at risk of developing HCC and would benefit most from surveillance. Therefore, in terms of future directions, a reasonable next step would be to integrate TE into existing HCC risk prediction models for HBV. Several models have been developed, including GAG-HCC and HCCCU scores (from Hong-Kong cohorts) [11,12], REACH-B score (in Asian CHB populations without cirrhosis) [13], THRI (from a Toronto cohort of cirrhotic patients) [14], PAGE-B score (in Caucasian CHB populations on entecavir/tenofovir) [15,16], mPAGE-B score (in Asian CHB patients on antiviral therapy) [17], PLAN-B prediction model (developed using artificial intelligence, in South Korean CHB patients on antiviral teraphy) [18], and the recently proposed PAGED-B score (from South Korean CHB patients treated with entecavir/tenofovir) (summarised in Table 1) [19]. However, further work is needed to incorporate LSMs into these or new models, particularly by including populations from other continents to enhance the generalizability and applicability across diverse populations.

Increasingly, the use of concordant independent NITs (such as TE and other NITs for liver fibrosis, such as serum-based scores like fibrosis-4, aminotransferase to platelet ratio index, and ELF) is recommended to increase the confidence of a positive diagnosis of cirrhosis [20]. This would further increase the ability to stratify risk and customize surveillance strategies for CHB patients. While TE focuses on liver stiffness, serum-based tests offer additional “layers” of risk assessment, contributing to a more complete approach to managing CHB patients. Combining these NITs with imaging techniques can improve the accu-racy of risk prediction and facilitate more personalized patient management [1,21-23].

While RCTs could offer a wider perspective, they may not be essential. Instead, future research should focus on the development of robust prediction models with comprehensive derivation and external validation, across different, heterogeneous populations, evaluating TE and other established risk factors. Such models would allow for more accurate risk stratification and tailored surveillance strategies, ultimately improving patient outcomes. Future research should also consider the overall effects of antiviral therapy on TE results and the overall risk of HCC development, and the engagement and adherence of the patients to surveillance protocols. Public health initiatives which aim at increasing awareness and access to TE and NITs could contribute to better management of CHB and reduce the global burden of HBV-related liver cancer.

In conclusion, while TE has demonstrated to be a valuable tool for assessing the risk of HCC development in patients with, its integration within existing risk scores will be pivotal in advancing patient care.