Prof Teerha Piratvisuth shares key recommendations from the Asia Pacific Consensus Statement on HCC early detection – Expert Insights from LEAD 2025, the leading APAC Liver Disease Expert Meeting

This is a verbatim transcript of an interview conducted with Prof Teerha Piratvisuth in June 2025. The transcript has been lightly edited for clarity.

Introduction

I’m Professor Teerha Piratvisuth, Division of Gastroenterology, Hepatology, Prince of Songkla University, Thailand. Currently, I’m the president of the Gastroenterological Association of Thailand and also the director of the Liver Institute in Bangkok.

Can you explain the current landscape of biomarker-based algorithms in early hepatocellular carcinoma (HCC) detection?

If we talk about biomarkers, clearly we mainly focus on GALAD and GAAD score. These two algorithms have some differences. They are combinations of gender, age, and two or three biomarkers for GAAD and GALAD, respectively.

GAAD does not require L3 fraction. That’s really practical in Southeast Asia, because many centres cannot do L3 fraction assay. And on the other hand, it’s less expensive than GALAD, because we don’t require the L3 fractions. This algorithm can allow us to detect early stage of HCC.

From the study, we found that GAAD had good performance comparable with GALAD, with area under the curve >91% and sensitivity of 71% and specificity of 90%, and that can detect the early stage of HCC, leading to curative options and better long-term survival. And due to [the fact that] GAAD and GALAD had comparable efficacy and performance, so it would be less expensive by using GAAD algorithm.

Why is there a need for this Asia-Pacific expert consensus on HCC early detection?

HCC is usually asymptomatic. So in the literature, you can see that more than 50% of them have advanced-stage HCC at the time of diagnosis, and that leads to a really poor survival – 5-year survival of less than 5–10%. So to do this guideline because we want to educate people and also guide all general practitioners and physicians or hepatologists to have awareness on surveillance for HCC in order to detect early stages of HCC, and that can improve curative treatment and long-term survival.

What are some key recommendations for improving HCC detection from the current consensus?

There are 16 experts from eight countries working together in this consensus, because we want to improve our HCC surveillance. The current tools for HCC surveillance mainly are ultrasound and alpha-fetoprotein, and these two have a lot of limitations.

Starting with ultrasound: ultrasound is operator-dependent and difficult to look at the small lesions among underlying echogenic or coarse liver parenchyma. And partly, nowadays, as you know, the MAFLD or obesity has become the leading – one of the leading causes of liver cancer. Ultrasound even has limitations to see the image clearly.

I give you the number: for BMI >40, you know, about >40% of patients have visualisation limitation by ultrasound. And lastly is the waiting time. So, in the Asia-Pacific region, normally the waiting time for ultrasound, it can be more than 6 months. In Thailand, it’s about 7–9 months. In some countries, like Hong Kong, it can be more than 2 years.

And lastly, ultrasound can have high false positives. When you have high positives, you not only expand the problem to increase more investigations, but it also has psychological harm to the patient when they are being told that, “Oh, you have a lesion in the ultrasound.”

For biomarker, alpha-fetoprotein alone has a lot of limitations. Sensitivity is just about 40%, and when you look at the specificity, it can be found in some conditions. So these are unmet needs.

We recommend GAAD as one of the best surveillance tools, because GAAD, from our study, demonstrated that it had really good performance, with area under the curve >91% for detecting small HCC lesions or early stage of HCC, with a sensitivity up to 72% and also the specificity up to 90%, and this algorithm can detect the early-stage HCC regardless of aetiologies, lesion, presence/absence of cirrhosis.

So therefore, we would like to develop the consensus in order to guide physicians to use GAAD algorithm for HCC surveillance. Last but not the least, some countries performed health economic study to look at cost-effectiveness, including Thailand, China, and the UK. All confirmed that GAAD is cost-effective to detect early stage of HCC and much better than alpha-fetoprotein and ultrasound.

In some countries, like Thailand, we found that GAAD is cost-saving, not only effective. I mean, spend less money to buy one quality-adjusted life year gain. I think as we work together at the expert consensus, this should guide all countries in the Asia-Pacific region to work with their policy makers to understand that we need a better tool for HCC surveillance and really cost-effective.

What strategies would you recommend to effectively integrate these recommendations into routine clinical practice?

I think we should recommend GAAD algorithm into the clinical practice guideline for HCC surveillance. As I mentioned earlier, it provides really good performance – high sensitivity and specificity – for detecting early-stage HCC.

And it also has better performance and also cost-effectiveness when you compare it with the current tools: ultrasound and alpha-fetoprotein. The best strategy is to work with the local societies to update the guidelines and put GAAD into the guideline, and then people in that country can follow this guideline.

And the best way is not only local. We may have to work with the region. This is GAAD, and put it into the guideline of Asia-Pacific region, the APASL. The most important thing to talk with them, to show or demonstrate that not only good performance but also really cost-effective.

The problem, one thing that I learned, is we are experts to develop consensus, but you know, many general practitioners, patients, and even physicians still do not understand what GAAD is. So our duty is then to educate the general practitioners or patients to understand what GAAD algorithm means, and what is the importance of GAAD, and how can we use GAAD properly in order to improve the outcomes from HCC.

The views and opinions expressed by Prof Teerha Piratvisuth are his own views and opinions. Roche disclaims all liability in relation to these views and opinions.

Reference:

Polpichai N, Maneenil C, Danpanichkul P, et al. Current and new strategies for hepatocellular carcinoma surveillance. Gastroenterol Rep (Oxf). 2025;13:goaf045. doi:10.1093/gastro/goaf045