Prediction models of hepatocellular carcinoma recurrence after liver transplantation: A comprehensive review

Article information

Clin Mol Hepatol. 2022;28(4):739-753
Publication date (electronic) : 2022 April 26
doi :
1Department of Surgery, Korea University College of Medicine, Seoul, Korea
2Division of Hepatobiliopancreas and Transplant Surgery, Korea University Ansan Hospital, Republic of Korea, Ansan, Korea
3Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
Corresponding author : Jong Man Kim Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea Tel: +82-2-3410-1719, Fax: +82-2-3410-0040, E-mail:

Editor: Ji Hoon Kim, Korea University Guro Hospital, Korea

Received 2022 March 1; Revised 2022 April 5; Accepted 2022 April 15.


Liver transplantation (LT) is one of the most effective treatments for hepatocellular carcinoma (HCC). Although LT eliminates HCC and greatly reduces recurrence, some patients experience recurrence after LT. Criteria and models for screening patients with a high probability of HCC recurrence after LT, starting with the Milan criteria, have been published. These models have changed over time, but a standard has not been established. We summarized HCC prediction models after LT by focusing on the application of radiologic, serologic, and pathologic factors and recent trends. This review will look at studies that are based on living donor LT and deceased donor LT, as well as studies that downstaging procedures have been performed preoperatively. This ultimately aims to help make decisions for evaluating the HCC state and selecting candidates for LT according to the circumstances of each transplantation center.


Liver transplantation (LT) has been widely used for endstage liver diseases, such as acute or chronic liver failure, as well as for patients with hepatocellular carcinoma (HCC). Approximately 25% of LTs are performed for underlying HCC in Western countries, with an increasing proportion of nonalcoholic steatohepatitis (NASH) cases, while hepatitis C virus (HCV) is decreasing [1,2]. With a high prevalence of hepatitis B virus (HBV), HCC also accounts for a high proportion of LTs in Asia (17–42%), especially in China [3,4]. LT can completely remove HCC from the liver by replacing the underlying liver, which is the basis of HCC development.

However, LT for patients with HCC still bears the risk of recurrence, leading to patient death, especially when the HCC is at an advanced stage [5,6]. To evaluate the risk of HCC recurrence after LT, the Milan criteria (MC), which employs simple guidelines using tumor size and numbers to perform LT, were introduced in 1996 and adopted by the United Network for Organ Sharing (UNOS) in 2002 [7]. Although the application of MC showed good post-LT recurrence-free survival, the indication for this criterion is relatively narrow for the majority of HCC patients; thus, an extended guideline for LT was published by the University of California, San Francisco (UCSF), in 2001 [8].

Although these criteria significantly contributed to clinical practice at the beginning with high prognostic power and led to the revival of LT, they are restricted, leaving out some patients who can benefit from LT. In addition, these criteria are based only on the radiological aspect and do not reflect various factors that can affect HCC recurrence. Practically, preoperative imaging evaluations differ in the accuracy of actual discrimination of HCC according to examination methods such as magnetic resonance imaging (MRI) or computed tomography (CT), as well as according to the individuality of the interpreter [9]. Although the Liver Imaging Reporting and Data System was developed to standardize the interpretation of liver lesions and showed great effects, a recent meta-analysis of 2,056 patients showed a sensitivity of only 67% and specificity of 92% compared to those of pathologic reports, suggesting low accuracy in detecting HCC before performing LT [10]. Therefore, the addition of several approaches, including multiple non-radiologic factors, such as serologic or pathologic factors, into the criteria for LT in patients with HCC, has been proposed (Fig. 1). This article aims to review previously published prediction models for HCC recurrence after LT and aid in the application of these models in clinical practice.

Figure 1.

Prediction models based on recruited factors. UCSF, University of California, San Francisco; AMC, Asan Medical Center; AFP, alpha-fetoprotein; SMC, Samsung Medical Center; RETREAT, Risk Estimation of Tumor Recurrence After Transplant; LiTES-HCC, Liver Transplant Expected Survival-hepatocellular carcinoma.


The main concept behind the selection criteria for LT in patients with HCC is to exclude patients with HCC with vascular invasion or poor differentiation, which may lead to HCC recurrence and patient death [11]. The tumor size and number are closely related to these two factors [12].

Mazzaferro et al. [7] at the National Cancer Institute in Milan, presented the MC, the most monumental criterion for LT for patients with HCC in 1996, after analyzing the explant pathology of 48 patients. The criteria included single tumor up to 5 cm in diameter or two or three tumors, each smaller than 3 cm in diameter. Patients who met these criteria showed excellent 4-year overall survival and recurrence-free survival after transplantation (85.0% and 92.0%, respectively), whereas those who did not meet the criteria showed poor survival (50.0% and 59.0%, respectively). After this publication, several centers following the MC also showed favorable outcomes and the MC became the standard guideline for patients with HCC. The same LT center also reviewed 90 articles and applied a meta-analysis of 25 articles analyzing the outcomes of patients within MC, showing similar favorable survival rates after LT (5-year patient survival of at least 70%) [13].

The UCSF criteria, which were published in 2001, presented a requirement slightly different from that of MC based on the explant pathology of 70 patients (Table 1) [8]: a solitary tumor ≤6.5 cm, or ≤3 nodules with the largest lesion being ≤4.5 cm and a total tumor diameter of ≤8 cm. These extended criteria led to a favorable 5-year patient survival rate of 75.2%, which enabled the LT center to recruit more candidates whose HCC status was beyond the MC. Mazzaferro et al. [14] also presented simple criteria in 2009 (up-to-seven) designed for patients who did not meet the MC, including those with cumulative tumor number and diameter (cm) of the largest tumor ≤7. This study was based on 1,156 patients from 20 countries in Europe, the USA, and Brazil who showed a 5-year patient survival of 71.2% among those who met the criteria.

Criteria based on deceased donor liver transplantation

The above criteria were developed in the West and were analyzed and presented in a deceased donor liver transplantation (DDLT) setting. The need for standard criteria for living donor liver transplantation (LDLT) was raised, and the 5-5 rule and Asan Medical Center criteria were introduced in Japan and Korea in 2007 and 2008, respectively (Table 2). According to these criteria, the maximum tumor size must be less than 5 cm, and the maximum number of tumors should be 5 or 6 for each criterion. Each study reported favorable recurrence-free survival in patients who met the criteria [15,16].

Criteria based on living donor liver transplantation

The above studies were based on analyzed pathological data; however, the criteria depended on preoperative radiologic images. These early models contributed significantly to good outcomes after LT, and thereafter, efforts to include a large number of candidates using serological markers began to emerge.


Alpha-fetoprotein (AFP) is a marker for HCC differentiation and vascular invasion [11]. In a study that developed the UCSF criteria, AFP levels >1,000 ng/mL were shown to be related to poor outcomes [8].

In 2012, the Liver Transplantation French Group proposed an AFP scores using radiologic features and AFP levels [17]. By scoring factors according to criteria such as tumor numbers greater than 4, tumor sizes 3–6 cm or >6 cm, and AFP levels of 100–1,000 ng/mL or greater, patients with AFP scores greater than two showed poorer 5-year survival and higher 5-year recurrence rates (47.5% and 50.6%, respectively) than patients with AFP scores of 0–2 (67.8% and 8.8%, respectively) in the validation cohort of 435 patients (Table 1). This model was additionally validated in several different populations, including Asian and LDLT populations, showing its favorable usefulness in predicting HCC recurrence after LT [18-21].

The transplantation center of the University of Milan, which proposed the MC, recently suggested a new criteria, the Metroticket 2.0 criteria, which include AFP levels as selection factors [22]. This study included 1,018 patients from three centers in Italy as the training cohort and 341 patients in China as the validation cohort; the demographic characteristics, including the hepatitis etiology, were relatively different between the two groups; HCV dominated in Italy and HBV dominated in China. These criteria suggested the limitation of radiological features according to the AFP level: if the AFP level is lower than 200 ng/mL, the sum of the tumor number and size should be ≤7; if the AFP level is between 200 and 400 ng/mL, the sum of the tumor number and size should be ≤5; and if the AFP level is ≥400 and <1,000, the sum of the tumor number and size should be ≤4. Patients who met these criteria showed excellent 5-year patient survival and recurrence-free survival in the training (79.7% and 89.6%, respectively) and validation cohorts (80.8% and 86.4%, respectively).

In the LDLT era, the Samsung Medical Center criteria were presented in Korea by applying both the tumor size, number, and AFP levels (largest tumor size ≤6 cm, number ≤7, and AFP level ≤1,000 ng/mL). In addition, more restrictive criteria, the 5-5-500 rule (tumor diameter ≤5 cm, tumor number ≤5, and AFP ≤500 ng/mL), were presented in Japan, and both showed comparable results [23,24].

While the role of prothrombin-induced by vitamin K absence-II (PIVKA-II) in the detection of HCC has been growing, attempts to use this marker for LT selection have also been undertaken. Some reports have shown that PIVKA-II is better than AFP for detecting advanced HCC with poor differentiation and microvascular invasion [25,26]. The Kyushu criteria and the Kyoto criteria were announced at around the same time for LDLT patients in Japan, with PIVKA-II levels within 300 mAU/mL and 400 mAU/mL, respectively, included as the criteria (Table 2). Unlike the Kyoto criteria, in which all three conditions of tumor size (≤5 cm), number (≤10 tumors), and PIVKA level (≤400 mAU/mL) must be met, the Kyushu criteria suggest that LT is feasible if only one of the two conditions (tumor diameter ≤5 cm or PIVKA-II levels ≤300 mAU/mL) is satisfied, presenting very broad criteria for LT indication [27,28].

These criteria combining radiological factors with AFP levels contribute to expanding LT candidates beyond the MC and are easily applied with simple calculations of tumor size and number and AFP levels; thus, they are currently widely used [11].

In addition, a model to predict tumor recurrence after LDLT (MoRAL, Korea) was developed in Korea, which included only two serologic factors, AFP and PIVKA-II, as LT selection criteria (MoRAL score = 11 × √PIVKA-II + 2 × √AFP) [29]. The basis for this is that while diffuse or infiltrative HCC is difficult to identify using radiologic methods, AFP, which reflects maximal tumor size, and PIVKA-II, which reflects the number and type of a tumor, are objective and reproducible values. Patients with a MoRAL score within 314.8 showed a 5-year recurrence rate of 75.9%. When stratified by the MC and a MoRAL score cut-off of 314.8, the recurrence-free survival of patients decreased in the following order: low MoRAL score within MC > low MoRAL score beyond MC > high MoRAL score within MC > high MoRAL score beyond MC. Even in patients whose radiologic findings were beyond the MC, the overall survival and recurrence-free survival rates were relatively high when the MoRAL scores were ≤314.8 (82.6% and 66.3%, respectively). The authors suggest that the use of MoRAL scores along with MC is valuable for the selection of LT candidates.


Along with radiological, serological factors, and pathological factors are known to be powerful predictive factors for HCC recurrence after LT as they directly show microvascular invasion and tumor differentiation. It is a standard procedure to confirm explant pathology after LT; however, pathological diagnosis before LT is not routinely performed. In any case, pre-LT biopsy is used for a more accurate prediction of HCC recurrence. One study assessed only moderate or well-differentiated HCC cases confirmed by pre-LT biopsy; these patients received LT and had favorable 5-year survival of 75% and recurrence-free survival of 92% [30]. From a similar point of view, the expanded Toronto criteria suggested that pre-LT biopsy should be performed for patients beyond the MC to exclude poorly differentiated tumor types. They also suggested that the center should not limit patients within MC who show no vascular invasion or systemic symptoms by size and number of tumors [31]. These criteria may be a good way to expand the pool for LT candidates; however, preoperative liver biopsy may be difficult to perform in some patients, and there is also the risk of cancer seeding [32]. In addition, sonography-guided needle biopsy of the liver has a relatively lower accuracy of tumor differentiation than explant pathology [33].

Explant pathology may aid in predicting HCC recurrence after LT effectively, aiding in the determination of the HCC evaluation interval, thus reducing unnecessary radiation exposure and costs [34]. The Risk Estimation of Tumor Recurrence After Transplant (RETREAT) scoring system, which uses microvascular invasion, the sum of tumor sizes, and the number of explant pathologies for its score calculation, was published in 2017 based on a training cohort of 721 patients and a validation cohort of 341 patients in the USA [35]. With scores ranging from 0 to 8, the study showed a very high 5-year recurrence rate of 75.2% in patients with scores of 5 or greater, while only 2.9% of the patients scored 0. The authors suggested applying different HCC surveillance intervals and adjusting the levels of immunosuppressants and mammalian target of rapamycin (mTOR) inhibitors, which have antineoplastic effects, based on patients’ RETREAT scores.

Halazun et al. [36] in the USA presented a HCC prediction score system using both pre- and post-operative factors such as AFP, neutrophil-to-lymphocyte ratio (NLR), radiological tumor size, and explant tumor specificity in both the pre-LT and post-LT periods. This new Model Of Recurrence After Liver transplantation (MORAL, USA) score uses a similar abbreviation to the HCC prediction model (MoRAL, Korea), which is based on LDLT patients and uses only AFP and PIVKA as predictive factors. In this score, preoperative AFP levels >200 ng/mL, NLRs ≥5, and largest tumor size >3 cm (pre-MORAL score) were significant risk factors in the pre-LT period, while tumor grade 4, vascular invasion, size >3 cm, and number >3 on explant pathology (post-MORAL score) may aid prediction during the post-LT period. The low-risk group (score 0–2) had a 5-years recurrence-free survival rate of 98.5%, while the very-high-risk group (score >10) had a 1-year recurrence-free survival rate of only 17.9%. They also suggested the combo-MORAL score, a combined version of both pre- and post-MORAL scores with high prediction power and a c-statistic of 0.91. Notably, in this scoring system, an NLR ≥5 was regarded as one of the most important factors affecting HCC recurrence, along with a tumor grade of 4 (adding 6+ score).

A recent study published a method for predicting patient survival using the Liver Transplant Expected Survival-HCC (LiTES-HCC) score based on 6,502 DDLT patients registered in the USA’s Organ Procurement and Transplantation Network/UNOS [37]. In this study, 11 HCC-related and non-related factors were combined into the score calculation: age, bilirubin, chronic kidney disease, INR, diabetes, etiology of liver disease, change in tumor diameter, AFP change from waiting to transplant time, pre-transplant location, ventilation, interaction between diabetes mellitus and age, and interaction between chronic kidney disease and NASH. The 5-year survival rates in the highest and lowest score groups were 86.3% and 67.0%, respectively, and the 10-year survival rates were 72.7% and 47.7%, respectively. HCC recurrence was not confirmed in the UNOS data; therefore, this study has limitations in that it did not show recurrence-free survival data, and it only included patients with DDLT who had been waiting for ≥6 months. However, an attempt to predict survival by considering numerous HCC-related and non-related factors would be highly significant. In addition, the survival curve could be obtained by inputting patient data into the website (, which may be helpful in determining LT.


The technique of locoregional therapy (LRT), which is traditionally performed for inoperable HCC patients with advanced liver cirrhosis, has recently been advancing. This includes traditional trans-arterial chemoembolization, radiofrequency ablation, the newest 3D-conformal radiation therapy, trans-arterial radioembolization, and stereotactic body radiotherapy, and helps reduce tumor activity [38,39]. Recently, the LT paradigm has been changed to make it suitable for LT by downstaging HCC beyond the MC or for more advanced HCC.

The goal of downstaging is different in each study; however, the first goal is often to meet the MC (MC-IN) [40,41]. The European Association for the Study of the Liver recommends LT only for patient with MC-IN after downstaging. The UCSF group presents slightly different criteria that can benefit from LRT before LT through the UCSF downstaging protocol and criteria for defining the ‘success of downstaging’ (Table 3) [42]. According to these criteria, the UNOS T2 criteria are recommended as a goal for downstaging before DDLT, and it is recommended that LDLT be performed only when the already known UCSF criteria have been met. A study that included three centers in California and used the same UCSF downstaging protocol showed comparable outcomes of downstaging followed by LT. Both studies showed similar 5-year survival rates (77.8–80.0%) and 5-year recurrence-free survival rates (87.0–90.8%). However, the success rate of downstaging was 58.0–65.3%, and the risk of downstaging failure was particularly high in those with AFP ≥1,000 ng/mL or Child B or C [41].

Downstaging procedures before liver transplantation

In addition to absolute criteria such as MC-IN, tumor responses, such as complete response (CR) or partial response (PR) according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST), are good indicators for HCC prediction, while progressive disease (PD) is associated with poor outcomes (Supplementary Table 1) [43]. The study by the European Hepatocellular Cancer Liver Transplant Study group considered two factors as high-risk factors for HCC recurrence after LT: 1) AFP slope >15 ng/mL/month and 2) tumor progression even after LRT. Regardless of whether the MC criteria were met, patients’ survival rates were very poor if there was even one risk factor present. In addition, MC-IN patients had slightly better survival if there were no risk factors present [44]. This study also showed that tumor recurrence after LT is higher when the AFP change over time is >15 ng/mL/month compared with AFP value at a specific time point. Since it is difficult for individuals waiting for DDLT to have their AFP levels confirmed at the time of their operation, this AFP trend can be greatly significant for transplantation decisions.

Both the quality of the response and duration of surveillance are important considerations. One study that included 6,160 patients from the UNOS database showed that the survival rate after LT was better in a cohort with a long waiting time (WT), which is thought to be because it is difficult to confirm early recurrence of HCC when the interval to LT is short [45]. Some downstaging studies mainly maintained 3- or 6-month intervals and showed reasonable results [42]. Therefore, the guidelines of the European Association for the Study of the Liver (2018) and American Association for the Study of Liver Disease (2018) recommend a minimum of 3 to 6 months of surveillance [46,47].

Taking all the above into consideration, Lai et al. [48] presented the time-radiological-response-alpha-fetoprotein-inflammation (TRAIN) score in 2016 by combining various factors, including tumor response, AFP change, NLR, and WT after LRT. The score equation is as follows: TRAIN score = 0.988 (if mRECIST-PD) + 0.838 (if AFP slope ≥15.0 ng/mL/month) + 0.452 (if NLR ≥5.0) – 0.03 × WT (month). With the greatest effects observed from the mRECIST-PD or high AFP slopes, even after LRT, this study revealed the poorest patient survival and recurrence-free survival when the score was ≥1.0. This score is significant in that the criteria are applied by actively using time-dependent variables in situations in which many patients wait without receiving LT immediately. In addition, the score calculation is quite simple.

Mazzaferro et al. [49] recently performed a randomized controlled trial (XXL criteria) of a downstaging procedure followed by LT in patients with HCC who were beyond the MC at nine Italian transplantation centers. The inclusion criteria for the downstaging procedure were: age between 18 and 65 years, expected 5-year survival after LT of at least 50%, and liver function of Child-Pugh A-B7. Patients with mRECIST-PR or CR after a 3-month observation period were randomly assigned to either the LT therapy group or the non-LT group with only LRT (among 74 initially enrolled patients, 29 dropped out, 23 were assigned to the LT group, and 22 were assigned to the control group). The 5-year recurrence-free survival and overall survival rates were much higher in the LT group than in the control group (76.8% vs. 18.3% and 77.5% vs. 31.2%, respectively; P=0.035). This result showed that patients with PR or CR within the 3-month interval after LRT may receive a huge survival benefit from transplantation

Specific criteria of AFP, RETREAT and MORAL (USA) models

Macro-vascular invasion was not included in the aforementioned criteria for LT. Traditionally, cases with macro-vascular invasion are not suitable for LT, and the European Association for the Study of the Liver guidelines (2018) specified it as an absolute contraindication. However, recent cases of HCC with vascular invasion, including portal vein tumor thrombosis, showed favorable outcomes with a downstaging procedure followed by LT [50]. However, there are few studies on this topic, and more trials are required for LT in HCC with vascular invasion.


Some approaches that use artificial intelligence (AI), including deep learning models, exist in the field of HCC. One study including 48,151 electronic healthcare records of HCV patients, developed recurrent neural network models for predicting HCC occurrence at 3 years of follow-up [51]. Saillard et al. [52] used the pathological slides of 194 patients with resected HCC to develop a deep learning model for predicting HCC recurrence and validated the model with 328 patients. Recently, in the transplantation era, three large LT centers in Korea have developed an HCC recurrence prediction model using a deep neural network, denoted as MoRAL-AI. This model was developed using radiologic, serologic, and biologic factors (maximum tumor diameter, AFP, age, PIVKA-II, portal vein invasion, and tumor number) in a derivation cohort of 349 LDLT patients and was validated with 214 LDLT patients, which showed a better discrimination function (c-index, 0.75) than previously developed models [53]. Notably, the relative significance of portal vein tumor thrombosis for HCC recurrence was not higher than that of tumor diameter, AFP, age, and PIVKA-II. The rate of preoperative portal vein invasion was 14.7%, and the center used the peeling-off technique in these cases during transplantation [54].


Since the introduction of MC, various other models have been proposed to guide LT in patients with HCC. The models that mainly assessed only radiologic factors in the beginning, gradually added serological factors and considered pathologic factors before and after surgery; they tend to consider the tumor response to LRT and wait for downstaging [11]. The limits of tumor number and size vary in range, sometimes according to serological factors. AFP levels with cut-off values of 200–500 ng/mL are widely used, and values >1,000 ng/mL are regarded as extremely critical. PIVKA-II levels are used less frequently, with a cut-off value of 300 or 400 mAU/mL, and this factor was used in combination with AFP levels in the MoRAL (Korea) model. A preoperative NLR ≥5 was regarded as a very high-risk factor for HCC recurrence in the MORAL (USA) model. The pathological factors considered mainly focused on microvascular invasion and tumor differentiation, with precise calculation of the size and number of explant livers. Validation studies were attempted for each of the models both internally and externally, and one systematic review article mentioned that the AFP model was well validated without considerable differences in five studies across the West and East [34].

HCC models should be considered depending on whether LDLT or DDLT is used. Donor recruitment is mainly influenced by sociocultural or administrative backgrounds, rather than by differences in tumor biology itself. LDLT is practiced at a high rate in Asia, particularly Korea, Japan, and India [55]. The choice of DDLT or LDLT affects the interval between the first HCC detection and the operation. As mentioned by the author who presented the TRAIN score, the longer the WT, the greater the tendency of increase in dropouts due to HCC metastasis. Conversely, the UNOS survey reported that the shorter the WT, the lower the number of dropouts, but with the possibility of HCC recurrence bound to increase [49,56]. In Asian countries with a high LDLT rate, WT may be shorter than that in Western countries, and the recurrence rate may instead increase.

Hepatitis, either by HCV or HBV, is known to contribute to HCC recurrence after LT [57,58]. However, several of the models in the above studies were developed in the West, and most of them had higher rates of HCV infection than those in the East. An important point to consider for HCV is that with the development of direct-acting antiviral agents (DAAs), HCV treatment has become more effective. Approved as a treatment for HCV in 2013, DAA may improve the cure rates for HCV and affect HCC prevention. However, the effect of DAAs on the reduction of HCC recurrence after LT remains controversial. One multicenter study of 875 HCV-HCC recipients showed no association between DAA and HCC recurrence, while another study with 171 HCV-HCC recipients showed a trend of decreased HCC recurrence in patients receiving DAAs (hazard ratio, 0.38; P=0.07) [59,60]. These studies had the limitation of a relatively short follow-up period; therefore, more studies are needed to confirm the relationship between DAAs and HCC recurrence. Conversely, as HBV is predominant in the East, the potential differences in the effects of HBV and HCV on recurrence after LT should be considered. Considering the differences between these two etiologies, a study on the LiTES-HCC score was conducted in 6,502 patients (HCV rate: 43.0%) after excluding patients with HCV who had received LT before DAA administration. In addition, by conducting training and validation sets in the West (Italy) and East (China), which have different ratios of HBV and HCV infections, Metroticket 2.0 showed usefulness in both regions.

However, the basis for applying these criteria depending on the region, is unclear. Rather, the criteria should be applied while considering the situation of deceased donor poor, the preference and rate of LDLT, the WT of HCC patients, and the number of downstaging procedures in each center and country. In the case of DDLT, the Model for End-stage Liver Disease (MELD) score of patients should also be considered for the possibility of receiving a graft. The MELD score was a topic that came out while studying the 90-day survival rate of cirrhosis patients who initially received a transjugular intrahepatic portosystemic shunt [61]. This has been used as a criterion for DDLT selection by UNOS since 2002, reducing WT and death rate, and has been applied not only in the USA but also in many countries around the world [62]. The original MELD score was determined based on bilirubin, INR, creatinine, and whether dialysis was performed. Since 2016, the MELD-Na+ score, including the sodium level, has been used in the USA, and research has shown that the prognostic ability is better for HCC patients than the original MELD [63].

However, the sodium level has a severe limitation in that it fluctuates greatly depending on the patient’s volume state and diuretics use. In addition, there are some opinions that the HCC factors should be incorporated into the MELD score. Guerrini et al. [64] suggested the HCC-MELD score which consists of AFP level, tumor size, and MELD score. Abdel-Wahab et al. [65] proposed the MELD-insulin-like growth factor-1 (IGF-1) score, which is based on studies showing that lower baseline IGF-1 is related to worse survival outcomes in HCC patients. Although these new-MELD scores showed better predictive power and may be useful for priority assignment, more studies are needed to validate their reproducibility. There are also administrative and ethical issues to consider in the application of MELD and new HCC-associated MELD scores separately for non-HCC and HCC patients.

While radiologic examination methods for diagnosing HCC mainly use CT or MRI, some studies have shown the usefulness of positron emission tomography (PET)/CT in deciding the treatment plan for HCC [66,67]. This depends on the phenomenon that well-differentiated HCC shows PET-negativity due to similar fluoro-deoxyglucose metabolism as a normal liver, whereas poorly differentiated HCC has a further decrease in glucose-6-phosphatase activity, leading to a high PET-positivity similar to metastasis. One study showed that the 5-year recurrence rate was 19% in the subgroup of patients with AFP <115 ng/mL and PET-negativity even though they were beyond the MC which was very low compared to the observed 53% in the group with high AFP levels or PET-positivity [68]. Additionally, molecular or genetic analyses may be helpful in predicting HCC recurrence after LT. Several studies have shown that the results of miRNA analysis and post-LT outcomes are related; however, these techniques are still too technically difficult to perform before LT [69-71]. The number of patients included in these studies is not sufficient, and more studies are needed to confirm the use of PET or molecular analysis for HCC prediction after LT.

Additionally, technical advances, such as AI, which lead to higher sensitivity and specificity in detecting HCC via radiological imaging, should be considered. Recent studies have shown that deep learning methods that analyze CT or MRI may help detect HCC more accurately [72]. In these methods, the criteria used for LT selection based on existing radiologic factors will have a greater impact, or new radiologic factors that predict poor prognosis beyond tumor size or number may be applied to the criteria. For example, a recent study analyzing CT and MRI as deep learning methods presented a model that can detect a relatively high prediction rate (area under curve, 0.78–0.85) of microvascular invasion [73].

Independent of the criteria selection, a combination of immunosuppressants and mTOR inhibitors may be considered to reduce HCC recurrence after LT [74]. mTOR inhibitors such as sirolimus are known to have anticancer effects, whereas calcineurin inhibitors can promote cancer growth [75,76]. The recently published SiLVER (Sirolimus in Liver Transplant Recipients with HCC study) trial was a randomized control trial involving 508 patients, which aimed to analyze the effect of sirolimus on HCC recurrence. Overall survival and disease-free survival were significantly better when sirolimus was used for ≥3 months after LT, and these results were even more pronounced in patients with AFP levels <10 ng/mL [77].


The application of the MC has led to good LT rates, and several expanded criteria for selecting and treating people who do not meet MC have been published. Serological factors such as AFP and PIVKA-II levels and their change patterns can also be considered, and tumor differentiation in pathologic reports can also be considered if possible. It would be desirable to consider both downstaging and tumor response after LRT, especially in regions where WTs are long after registering for DDLT. Even after transplantation, there are models that can help determine the use of immunosuppressants and surveillance interval according to the tumor characteristics of the explant pathology. In addition, as LRT develops, LT is likely to be increasingly attempted after downstaging in far more advanced HCC patients, including patients with portal vein tumor thrombosis, in the future. It is expected that more sophisticated models that can save many patients will be developed based on diagnostic methods and AI technology.


Authors’ contributions

Sang Jin Kim: Design of the work, Collect the articles, Write the manuscript; Jong Man Kim: Supervision of design, Critical revision of the article

Conflicts of Interest

The authors have no conflicts to disclose.





artificial intelligence


complete response


computed tomography


direct-acting antiviral agent


deceased donor liver transplantation


hepatitis B virus


hepatocellular carcinoma


hepatitis C virus


insulin-like growth factor-1


living donor liver transplantation


Liver Transplant Expected Survival-HCC


locoregional therapy


liver transplantation


Milan criteria


Model for End-stage Liver Disease


modified Response Evaluation Criteria in Solid Tumors


magnetic resonance imaging


mammalian target of rapamycin


nonalcoholic steatohepatitis


neutrophil-to-lymphocyte ratio


progressive disease


positron emission tomography


prothrombin-induced by vitamin K absence-II


partial response


Risk Estimation of Tumor Recurrence After Transplant


Sirolimus in Liver Transplant Recipients with HCC


transjugular intrahepatic portosystemic shunt




University of California


United Network for Organ Sharing


waiting time


Supplementary material is available at Clinical and Molecular Hepatology website (

Supplementary Table 1.

mRECIST criteria


1. Wong RJ, Singal AK. Trends in liver disease etiology among adults awaiting liver transplantation in the United States, 2014-2019. JAMA Netw Open 2020;3e1920294.
2. Bertot LC, Adams LA. Trends in hepatocellular carcinoma due to non-alcoholic fatty liver disease. Expert Rev Gastroenterol Hepatol 2019;13:179–187.
3. Kim JM, Kim DG, Kim J, Lee K, Lee KW, Ryu JH, et al. Outcomes after liver transplantation in Korea: incidence and risk factors from Korean transplantation registry. Clin Mol Hepatol 2021;27:451–462.
4. Lu TF, Hua XW, Cui XL, Xia Q. Liver transplantation for hepatocellular carcinoma: recent advances in China. J Dig Dis 2014;15:51–53.
5. Iwatsuki S, Starzl TE, Sheahan DG, Yokoyama I, Demetris AJ, Todo S, et al. Hepatic resection versus transplantation for hepatocellular carcinoma. Ann Surg 1991;214:221–229.
6. Ringe B, Pichlmayr R, Wittekind C, Tusch G. Surgical treatment of hepatocellular carcinoma: experience with liver resection and transplantation in 198 patients. World J Surg 1991;15:270–285.
7. Mazzaferro V, Regalia E, Doci R, Andreola S, Pulvirenti A, Bozzetti F, et al. Liver transplantation for the treatment of small hepatocellular carcinomas in patients with cirrhosis. N Engl J Med 1996;334:693–699.
8. Yao FY, Ferrell L, Bass NM, Watson JJ, Bacchetti P, Venook A, et al. Liver transplantation for hepatocellular carcinoma: expansion of the tumor size limits does not adversely impact survival. Hepatology 2001;33:1394–1403.
9. Toniutto P, Fornasiere E, Fumolo E, Bitetto D. Risk factors for hepatocellular carcinoma recurrence after liver transplantation. Hepatoma Res 2020;6:50.
10. Lee S, Kim SS, Roh YH, Choi JY, Park MS, Kim MJ. Diagnostic performance of CT/MRI liver imaging reporting and data system v2017 for hepatocellular carcinoma: a systematic review and meta-analysis. Liver Int 2020;40:1488–1497.
11. Toniutto P, Fumolo E, Fornasiere E, Bitetto D. Liver transplantation in patients with hepatocellular carcinoma beyond the milan criteria: a comprehensive review. J Clin Med 2021;10:3932.
12. Shah SA, Tan JC, McGilvray ID, Cattral MS, Levy GA, Greig PD, et al. Does microvascular invasion affect outcomes after liver transplantation for HCC? A histopathological analysis of 155 consecutive explants. J Gastrointest Surg 2007;11:464–471.
13. Mazzaferro V, Bhoori S, Sposito C, Bongini M, Langer M, Miceli R, et al. Milan criteria in liver transplantation for hepatocellular carcinoma: an evidence-based analysis of 15 years of experience. Liver Transpl 2011;17 Suppl 2:S44–S57.
14. Mazzaferro V, Llovet JM, Miceli R, Bhoori S, Schiavo M, Mariani L, et al. Predicting survival after liver transplantation in patients with hepatocellular carcinoma beyond the Milan criteria: a retrospective, exploratory analysis. Lancet Oncol 2009;10:35–43.
15. Sugawara Y, Tamura S, Makuuchi M. Living donor liver transplantation for hepatocellular carcinoma: Tokyo University series. Dig Dis 2007;25:310–312.
16. Lee SG, Hwang S, Moon DB, Ahn CS, Kim KH, Sung KB, et al. Expanded indication criteria of living donor liver transplantation for hepatocellular carcinoma at one large-volume center. Liver Transpl 2008;14:935–945.
17. Duvoux C, Roudot-Thoraval F, Decaens T, Pessione F, Badran H, Piardi T, et al. Liver transplantation for hepatocellular carcinoma: a model including α-fetoprotein improves the performance of Milan criteria. Gastroenterology 2012;143:986–994.e3. quize14-e15.
18. Notarpaolo A, Layese R, Magistri P, Gambato M, Colledan M, Magini G, et al. Validation of the AFP model as a predictor of HCC recurrence in patients with viral hepatitis-related cirrhosis who had received a liver transplant for HCC. J Hepatol 2017;66:552–559.
19. Rhu J, Kim JM, Choi GS, Kwon CHD, Joh JW. Validation of the α-fetoprotein model for hepatocellular carcinoma recurrence after transplantation in an Asian population. Transplantation 2018;102:1316–1322.
20. Degroote H, Callebout E, Iesari S, Dekervel J, Schreiber J, Pirenne J, et al. Extended criteria for liver transplantation in hepatocellular carcinoma. A retrospective, multicentric validation study in Belgium. Surg Oncol 2020;33:231–238.
21. Piñero F, Tisi Baña M, de Ataide EC, Hoyos Duque S, Marciano S, Varón A, et al. Liver transplantation for hepatocellular carcinoma: evaluation of the alpha-fetoprotein model in a multicenter cohort from Latin America. Liver Int 2016;36:1657–1667.
22. Mazzaferro V, Sposito C, Zhou J, Pinna AD, De Carlis L, Fan J, et al. Metroticket 2.0 model for analysis of competing risks of death after liver transplantation for hepatocellular carcinoma. Gastroenterology 2018;154:128–139.
23. Kim JM, Kwon CH, Joh JW, Park JB, Lee JH, Kim GS, et al. Expanded criteria for liver transplantation in patients with hepatocellular carcinoma. Transplant Proc 2014;46:726–729.
24. Shimamura T, Akamatsu N, Fujiyoshi M, Kawaguchi A, Morita S, Kawasaki S, et al. Expanded living-donor liver transplantation criteria for patients with hepatocellular carcinoma based on the Japanese nationwide survey: the 5-5-500 rule - a retrospective study. Transpl Int 2019;32:356–368.
25. Okuda H, Nakanishi T, Takatsu K, Saito A, Hayashi N, Yamamoto M, et al. Comparison of clinicopathological features of patients with hepatocellular carcinoma seropositive for alpha-fetoprotein alone and those seropositive for des-gamma-carboxy prothrombin alone. J Gastroenterol Hepatol 2001;16:1290–1296.
26. Poté N, Cauchy F, Albuquerque M, Voitot H, Belghiti J, Castera L, et al. Performance of PIVKA-II for early hepatocellular carcinoma diagnosis and prediction of microvascular invasion. J Hepatol 2015;62:848–854.
27. Taketomi A, Sanefuji K, Soejima Y, Yoshizumi T, Uhciyama H, Ikegami T, et al. Impact of des-gamma-carboxy prothrombin and tumor size on the recurrence of hepatocellular carcinoma after living donor liver transplantation. Transplantation 2009;87:531–537.
28. Takada Y, Uemoto S. Liver transplantation for hepatocellular carcinoma: the Kyoto experience. J Hepatobiliary Pancreat Sci 2010;17:527–532.
29. Lee JH, Cho Y, Kim HY, Cho EJ, Lee DH, Yu SJ, et al. Serum tumor markers provide refined prognostication in selecting liver transplantation candidate for hepatocellular carcinoma patients beyond the Milan criteria. Ann Surg 2016;263:842–850.
30. Cillo U, Vitale A, Bassanello M, Boccagni P, Brolese A, Zanus G, et al. Liver transplantation for the treatment of moderately or well-differentiated hepatocellular carcinoma. Ann Surg 2004;239:150–159.
31. DuBay D, Sandroussi C, Sandhu L, Cleary S, Guba M, Cattral MS, et al. Liver transplantation for advanced hepatocellular carcinoma using poor tumor differentiation on biopsy as an exclusion criterion. Ann Surg 2011;253:166–172.
32. Silva MA, Hegab B, Hyde C, Guo B, Buckels JA, Mirza DF. Needle track seeding following biopsy of liver lesions in the diagnosis of hepatocellular cancer: a systematic review and meta-analysis. Gut 2008;57:1592–1596.
33. Sparchez Z, Mocan T. Contemporary role of liver biopsy in hepatocellular carcinoma. World J Hepatol 2018;10:452–461.
34. Al-Ameri AAM, Wei X, Wen X, Wei Q, Guo H, Zheng S, et al. Systematic review: risk prediction models for recurrence of hepatocellular carcinoma after liver transplantation. Transpl Int 2020;33:697–712.
35. Mehta N, Heimbach J, Harnois DM, Sapisochin G, Dodge JL, Lee D, et al. Validation of a risk estimation of tumor recurrence after transplant (RETREAT) score for hepatocellular carcinoma recurrence after liver transplant. JAMA Oncol 2017;3:493–500.
36. Halazun KJ, Najjar M, Abdelmessih RM, Samstein B, Griesemer AD, Guarrera JV, et al. Recurrence after liver transplantation for hepatocellular carcinoma: a new MORAL to the story. Ann Surg 2017;265:557–564.
37. Goldberg D, Mantero A, Newcomb C, Delgado C, Forde KA, Kaplan DE, et al. Predicting survival after liver transplantation in patients with hepatocellular carcinoma using the LiTES-HCC score. J Hepatol 2021;74:1398–1406.
38. Oh D, Lim DH, Park HC, Paik SW, Koh KC, Lee JH, et al. Early three-dimensional conformal radiotherapy for patients with unresectable hepatocellular carcinoma after incomplete transcatheter arterial chemoembolization: a prospective evaluation of efficacy and toxicity. Am J Clin Oncol 2010;33:370–375.
39. Silva JP, Berger NG, Tsai S, Christians KK, Clarke CN, Mogal H, et al. Transarterial chemoembolization in hepatocellular carcinoma with portal vein tumor thrombosis: a systematic review and meta-analysis. HPB (Oxford) 2017;19:659–666.
40. Ravaioli M, Grazi GL, Piscaglia F, Trevisani F, Cescon M, Ercolani G, et al. Liver transplantation for hepatocellular carcinoma: results of down-staging in patients initially outside the Milan selection criteria. Am J Transplant 2008;8:2547–2557.
41. Mehta N, Guy J, Frenette CT, Dodge JL, Osorio RW, Minteer WB, et al. Excellent outcomes of liver transplantation following down-staging of hepatocellular carcinoma to within Milan criteria: a multicenter study. Clin Gastroenterol Hepatol 2018;16:955–964.
42. Yao FY, Mehta N, Flemming J, Dodge J, Hameed B, Fix O, et al. Downstaging of hepatocellular cancer before liver transplant: long-term outcome compared to tumors within Milan criteria. Hepatology 2015;61:1968–1977.
43. Lencioni R, Llovet JM. Modified RECIST (mRECIST) assessment for hepatocellular carcinoma. Semin Liver Dis 2010;30:52–60.
44. Lai Q, Avolio AW, Graziadei I, Otto G, Rossi M, Tisone G, et al. Alpha-fetoprotein and modified response evaluation criteria in solid tumors progression after locoregional therapy as predictors of hepatocellular cancer recurrence and death after transplantation. Liver Transpl 2013;19:1108–1118.
45. Halazun KJ, Patzer RE, Rana AA, Verna EC, Griesemer AD, Parsons RF, et al. Standing the test of time: outcomes of a decade of prioritizing patients with hepatocellular carcinoma, results of the UNOS natural geographic experiment. Hepatology 2014;60:1957–1962.
46. Heimbach JK, Kulik LM, Finn RS, Sirlin CB, Abecassis MM, Roberts LR, et al. AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology 2018;67:358–380.
47. European Association for the Study of the Liver. EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2018;69:182–236.
48. Lai Q, Nicolini D, Inostroza Nunez M, Iesari S, Goffette P, Agostini A, et al. A novel prognostic index in patients with hepatocellular cancer waiting for liver transplantation: time-radiologicalresponse-alpha-fetoprotein-inflammation (TRAIN) score. Ann Surg 2016;264:787–796.
49. Mazzaferro V, Citterio D, Bhoori S, Bongini M, Miceli R, De Carlis L, et al. Liver transplantation in hepatocellular carcinoma after tumour downstaging (XXL): a randomised, controlled, phase 2b/3 trial. Lancet Oncol 2020;21:947–956.
50. Kim SJ, Kim JM. Liver transplantation for hepatocellular carcinoma with portal vein tumor thrombosis. J Liver Cancer 2021;21:105–112.
51. Ioannou GN, Tang W, Beste LA, Tincopa MA, Su GL, Van T, et al. Assessment of a deep learning model to predict hepatocellular carcinoma in patients with hepatitis C cirrhosis. JAMA Netw Open 2020;3e2015626.
52. Saillard C, Schmauch B, Laifa O, Moarii M, Toldo S, Zaslavskiy M, et al. Predicting survival after hepatocellular carcinoma resection using deep learning on histological slides. Hepatology 2020;72:2000–2013.
53. Nam JY, Lee JH, Bae J, Chang Y, Cho Y, Sinn DH, et al. Novel model to predict HCC recurrence after liver transplantation obtained using deep learning: a multicenter study. Cancers (Basel) 2020;12:2791.
54. Cho JY, Suh KS, Shin WY, Lee HW, Yi NJ, Lee KU. Thrombosis confined to the portal vein is not a contraindication for living donor liver transplantation. World J Surg 2008;32:1731–1737.
55. Trotter JF, Cárdenas A. Liver transplantation around the world. Liver Transpl 2016;22:1059–1061.
56. Samoylova ML, Dodge JL, Yao FY, Roberts JP. Time to transplantation as a predictor of hepatocellular carcinoma recurrence after liver transplantation. Liver Transpl 2014;20:937–944.
57. Bozorgzadeh A, Orloff M, Abt P, Tsoulfas G, Younan D, Kashyap R, et al. Survival outcomes in liver transplantation for hepatocellular carcinoma, comparing impact of hepatitis C versus other etiology of cirrhosis. Liver Transpl 2007;13:807–813.
58. Wu TJ, Chan KM, Chou HS, Lee CF, Wu TH, Chen TC, et al. Liver transplantation in patients with hepatitis B virus-related hepatocellular carcinoma: the influence of viral characteristics on clinical outcome. Ann Surg Oncol 2013;20:3582–3590.
59. Tse CS, Yang JD, Mousa OY, Nelson KM, Pungpapong S, Keaveny A, et al. Direct-acting antiviral therapy in liver transplant patients with hepatocellular carcinoma and hepatitis C. Transplant Direct 2020;7e635.
60. Gorgen A, Galvin Z, Huang AC, Vinaixa C, O’Rourke JM, Francoz C, et al. The impact of direct-acting antivirals on overall mortality and tumoral recurrence in patients with hepatocellular carcinoma listed for liver transplantation: an international multicenter study. Transplantation 2020;104:2087–2096.
61. Malinchoc M, Kamath PS, Gordon FD, Peine CJ, Rank J, ter Borg PC. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 2000;31:864–871.
62. Bernardi M, Gitto S, Biselli M. The MELD score in patients awaiting liver transplant: strengths and weaknesses. J Hepatol 2011;54:1297–1306.
63. Kim KM, Shim SG, Sinn DH, Song JE, Kim BS, Kim HG. ChildPugh, MELD, MELD-Na, and ALBI scores: which liver function models best predicts prognosis for HCC patient with ascites? Scand J Gastroenterol 2020;55:951–957.
64. Guerrini GP, Pinelli D, Marini E, Corno V, Guizzetti M, Zambelli M, et al. Value of HCC-MELD score in patients with hepatocellular carcinoma undergoing liver transplantation. Prog Transplant 2018;28:63–69.
65. Abdel-Wahab R, Hassan MM, George B, Carmagnani Pestana R, Xiao L, Lacin S, et al. Impact of integrating insulin-like growth factor 1 levels into model for end-stage liver disease score for survival prediction in hepatocellular carcinoma patients. Oncology 2020;98:836–846.
66. Cho CW, Kim JM, Lee BH, Lee DS, Yun SS, Choi GS, et al. Clinical impact of anatomical resection on long-term outcomes after hepatectomy for primary solitary hepatocellular carcinoma with or without preoperative positron emission tomography positivity. Ann Transl Med 2020;8:1377.
67. Lee SD, Kim SH, Kim SK, Kim YK, Park SJ. Clinical impact of 18f-fluorodeoxyglucose positron emission tomography/computed tomography in living donor liver transplantation for advanced hepatocellular carcinoma. Transplantation 2015;99:2142–2149.
68. Takada Y, Kaido T, Shirabe K, Nagano H, Egawa H, Sugawara Y, et al. Significance of preoperative fluorodeoxyglucose-positron emission tomography in prediction of tumor recurrence after liver transplantation for hepatocellular carcinoma patients: a Japanese multicenter study. J Hepatobiliary Pancreat Sci 2017;24:49–57.
69. Pavel MC, Fuster J. Expansion of the hepatocellular carcinoma Milan criteria in liver transplantation: future directions. World J Gastroenterol 2018;24:3626–3636.
70. Liese J, Peveling-Oberhag J, Doering C, Schnitzbauer AA, Herrmann E, Zangos S, et al. A possible role of microRNAs as predictive markers for the recurrence of hepatocellular carcinoma after liver transplantation. Transpl Int 2016;29:369–380.
71. Barry CT, D’Souza M, McCall M, Safadjou S, Ryan C, Kashyap R, et al. Micro RNA expression profiles as adjunctive data to assess the risk of hepatocellular carcinoma recurrence after liver transplantation. Am J Transplant 2012;12:428–437.
72. Kim J, Min JH, Kim SK, Shin SY, Lee MW. Detection of hepatocellular carcinoma in contrast-enhanced magnetic resonance imaging using deep learning classifier: a multi-center retrospective study. Sci Rep 2020;10:9458.
73. Liu SC, Lai J, Huang JY, Cho CF, Lee PH, Lu MH, et al. Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals. Cancer Imaging 2021;21:56.
74. Rajendran L, Ivanics T, Claasen MP, Muaddi H, Sapisochin G. The management of post-transplantation recurrence of hepatocellular carcinoma. Clin Mol Hepatol 2022;28:1–16.
75. Vivarelli M, Cucchetti A, La Barba G, Ravaioli M, Del Gaudio M, Lauro A, et al. Liver transplantation for hepatocellular carcinoma under calcineurin inhibitors: reassessment of risk factors for tumor recurrence. Ann Surg 2008;248:857–862.
76. Koehl GE, Andrassy J, Guba M, Richter S, Kroemer A, Scherer MN, et al. Rapamycin protects allografts from rejection while simultaneously attacking tumors in immunosuppressed mice. Transplantation 2004;77:1319–1326.
77. Schnitzbauer AA, Filmann N, Adam R, Bachellier P, Bechstein WO, Becker T, et al. mTOR inhibition is most beneficial after liver transplantation for hepatocellular carcinoma in patients with active tumors. Ann Surg 2020;272:855–862.

Article information Continued

Figure 1.

Prediction models based on recruited factors. UCSF, University of California, San Francisco; AMC, Asan Medical Center; AFP, alpha-fetoprotein; SMC, Samsung Medical Center; RETREAT, Risk Estimation of Tumor Recurrence After Transplant; LiTES-HCC, Liver Transplant Expected Survival-hepatocellular carcinoma.

Table 1.

Criteria based on deceased donor liver transplantation

Study Criterion, country No. of patients Hepatitis Study period Risk factor
Post-LT survival within criteria*
Category (No.) Eligibility criteria Overall Recurrence-related
Mazzaferro et al. [7] (1996) Milan, Italy 48 HCV 70.8% 1991 to Radiologic (2) Solitary tumor ≤5 cm; or 2–3 tumors ≤3 cm 85.0% at 4-years vs. 50.0% 92.0% at 4-years RFS vs. 59.0%
HBV 27.1% 1994
Yao et al. [8] (2001) UCSF, USA 70 HCV 50.0% 1988 to Radiologic (2) Solitary tumor ≤6.5 cm; or 2–3 tumors ≤4.5 cm and total diameter ≤8 cm 75.2% at 5-years
HBV 18.6% 2000
Mazzaferro et al. [14] (2009) Up-to-seven, Europe/USA 1,556 1984 to Radiologic (2) Sum of number of tumors and diameter (cm) of the largest tumor ≤7 71.2% at 5-years vs. 48.1% 9.1% of 5-years RR
DuBay et al. [31] (2011) e-Toronto, Canada 294 HCV 52.0% 1996 to 2008 Radiologic (1) No tumor size or number restriction 79.0% at 5-years vs. 61.0% 76.0% at 5-years RFS vs. 58.0%
HBV 23.0% Pathologic (1) No systemic symptoms and macro-VI
Not poorly differentiated cancer (if beyond MC)
Duvoux et al. [17] (2012) AFP, France 972 Hepatitis 50.9% 1988 to 2004 Radiologic (2) Score ranged from 0 to 9 using AFP level, tumor diameter and number 67.8% at 5-years vs. 47.5% 8.8% of 5-years RR vs. 50.6%
Serologic (1)
Mehta et al. [35] (2017) RETREAT, USA 1,062 HCV 58.0% 2000 to Serologic (1) Score ranged from 0 to 8 using AFP, mVI, tumor diameter and number of explant 2.9% of 5-years RR vs. 75.2% (score 0 vs. ≥5)
HBV 18.3% 2012 Pathologic (3)
Halazunet al. [36] (2017) MORAL, USA 339 HCV 69.3% 2001 to 2012 Radiologic (1) Pre-MORAL: NLR, maximum AFP and tumor size; post-MORAL: tumor grade, vascular invasion, tumor size and number on pathology Pre-MORAL: 98.6% at 5-years RFS in low risk
HBV 15.3% Serologic (2)
Pathologic (4)
Mazzaferro et al. [22] (2018) Metroticket 2.0, Italy/China 1,359 HCV 56.9% 2000 to 2013 Radiologic (2) 1. If AFP <200 ng/mL, sum of number and size ≤7 79.7% at 5-years vs. 51.2% 89.6% at 5-years RFS vs. 46.8%
HBV 21.1%§ Serologic (1) 2. If 200≤ AFP <400 ng/mL, sum of number and size ≤5
3. If 400≤ AFP <1,000 ng/mL, sum of number and size ≤4
Goldberg et al. [37] (2021) LiTES-HCC, USA 6,502 HCV 43.0% 2002 to 2018 11 variables including liver related and non-related factors 86.3% at 5-years (highest score)

All criteria require no macrovascular invasion.

LT, liver transplantation; HCV, hepatitis C virus; HBV, hepatitis B virus; RFS, recurrence-free survival; UCSF, University of California, San Francisco; RR, recurrence rate; VI, vascular invasion; MC, Milan criteria; AFP, alpha-fetoprotein; AFP, alpha-fetoprotein; RETREAT, Risk Estimation of Tumor Recurrence After Transplant; mVI, microvascular invasion; NLR, neutrophil-tolymphocyte ratio; LiTES-HCC, Liver Transplant Expected Survival-hepatocellular carcinoma.


Survival of patients who met the criteria (compared with patients who did not meet the criteria).

Detailed criteria for AFP, RETREAT, and MORAL (USA) scores are summarized in Table 4.

Survival of the patients beyond Milan criteria but within up-to-seven criteria and beyond Milan criteria but within Toronto criteria, each.


Training set (Italy): HCV 56.9%, HBV 21.1%; validation set (China): HCV 2.6%, HBV 96.2%.

Table 2.

Criteria based on living donor liver transplantation

Study Criterion name Country No. of patients Hepatitis Study period Risk factor
Post-LT survival within criteria*
Category (No.) Eligibility criteria Overall Recurrence-free
Sugawara et al. [15] (2007) 5-5 rule (Tokyo) Japan 78 HCV 62% 1996 to 2005 Radiologic (2) Number ≤5, maximum diameter ≤5 cm 94.0% at 3-years vs. 50%
Lee et al. [16] (2008) AMC Korea 221 HCV 6.8% 1997 to 2004 Radiologic (2) Largest tumor diameter ≤5 cm; number ≤6 76.3% at 5-years vs. 18.9%
HBV 93.2%
Taketomi et al. [27] (2009) Kyushu Japan 90 HCV 76.7% 1996 to 2007 Radiologic (1) Tumor diameter ≤5 cm, or PIVKA-II ≤300 mAI/mL 82.7% at 5-years 87.0% at 5-years
HBV 13.3% Serologic (1)
Takada and Uemoto [28] (2010) Kyoto Japan 136 HCV 55.9% 1999 to 2006 Radiologic (2) ≤10 tumors; all ≤5 cm in diameter and PIVKA-II ≤400 mAU/mL 87.0% at 5-years vs. 36.0% 97.0% at 5-years vs. 47.0%
HBV 34.6% Serologic (1)
Kim et al. [23] (2014) SMC Korea 180 HCV 6.7% 2002 to 2008 Radiologic (2) Largest tumor size ≤6 cm, number ≤7, and AFP ≤1,000 ng/mL 90.0% at 5-years vs. 47.6%
HBV 87.2% Serologic (1)
Lee et al. [29] (2016) MoRAL (Korea) Korea 566 HCV 6.9% 2001 to 2013 Serologic (2) MoRAL score ≤314.8 66.3% at 5-years 82.6% at 5-years
HBV 87.8% Score calculation = 11 × √PIVKA-II + 2 × √AFP
Shimamura et al. [24] (2019) 5-5-500 rule Japan 965 HCV 29.2% 1998 to 2009 Radiologic (2) Tumor diameter ≤5 cm, tumor number ≤5, AFP ≤500 ng/mL 75.8% at 5-years 73.2% at 5-years
HBV 60.3% Serologic (1)
Nam et al. [53] (2020) MoRAL-AI Korea 563 2001 to 2013 Radiologic (3) Risk stratification by deep neural network
Serologic (2) Using maximal tumor diameter, AFP, age, PIVKA-II, portal VI and tumor number
Chronologic (1)

All criteria require no macrovascular invasion.

LT, liver transplantation; HCV, hepatitis C virus; AMC, Asan Medical Center; HBV, hepatitis B virus; PIVKA-II, prothrombin induced by vitamin K absence-II; SMC, Samsung Medical Center; AFP, alpha-fetoprotein; VI, vascular invasion.


Survival of patients who met the criteria (compared with patients who did not meet the criteria).

Survival of the patients beyond MC but within MoRAL score ≤314.8.

Table 3.

Downstaging procedures before liver transplantation

Study Criterion name, country No. of patients (drop-out rate) Hepatitis Study period Criteria
DS inclusion Transplantation factor
Lai et al. [44] (2013) Not named, Europe (6 centers) 422 HCV 45.5% 1999 to 2010 Beyond MC After downstaging, no risk of 1) AFP slope >15 mg/mL/month; or 2) progressive disease mRECIST)
HBV 15.9%
Yao et al. [42] (2015) UCSF down-staging, USA DS: 118 (34.7%) vs. LT only: 488 HCV 56% 2002 to 2012 Single lesion: >5 cm and ≤8 cm DDLT: within UNOS criteria T2
HBV 27% 2–3 lesions: at least one lesion >3 cm and ≤5 cm, total diameter ≤8 cm LDLT: within UCSF criteria
4–5 lesions: each ≤3 cm, total diameter ≤8 cm
Lai et al. [48] (2016) TRAIN, Italy/Belgium 289 HCV 47.1% 2000 to 2014 Beyond MC TRAIN score ≤1.0 recommended
HBV 18.0% Train score = 0.988 (if mRECIST-PD) + 0.838 (if AFP slope 15.0 ng/mL/month) + 0.452 (if NLR ≥5.0) – 0.03 × WT (month)
Mazzaferro et al. [49] (2020) XXL criteria, Italy DS: 74 (39.1%) HCV 62.2% 2011 to 2015 Beyond MC, age 18–65 years, Child-Pugh A–B (7), no MacroVI or extrahepatic spread Complete response or partial response
HBV 15.6%

DS, downstaging; HCV, hepatitis C virus; HBV, hepatitis B virus; MC, Milan criteria; AFP, alpha-fetoprotein; RECIST, Response Evaluation Criteria in Solid Tumors; UCSF, University of California, San Francisco; LT, liver transplantation; DDLT, deceased donor liver transplantation; UNOS, United Network for Organ Sharing; LDLT, living donor liver transplantation; TRAIN, time-radiological-response-alpha-fetoprotein-inflammation; PD, progressive disease; NLR, neutrophil-to-lymphocyte ratio; WT, waiting time; VI, vascular invasion.

Table 4.

Specific criteria of AFP, RETREAT and MORAL (USA) models

AFP model Total score >2: 50.6% of 5-year recurrence rate
 Tumor diameter
  ≤3 cm 0
  3–6 cm 1
  >6 cm 4
 Number of tumors
  1–3 0
  ≥4 2
  ≤100 ng/mL 0
  100–1,000 ng/mL 2
  >1,000 ng/mL 3
RETREAT Score 5 or more: 75.2% of 5-year recurrence rate
 AFP at LT
  0–20 ng/mL 0
  21–99 ng/mL 1
  100–999 ng/mL 2
  ≥1,000 ng/mL 3
 Micro-vascular invasion
  Present 2
 Largest diameter + No. of viable tumors on explant
  ≤1 cm 0
  1.1–4.9 cm 1
  5–9.9 cm 2
  ≥10 cm 3
 Pre-MORAL Score >10: 17.9% of 1-year RFS
  Preoperative NLR, ≥5 6
  Maximum AFP, >200 ng/mL 4
  Largest tumor size, >3 cm 3
 Post-MORAL (pathology) Score >10: 22.1% of 5-year RFS
  Grade 4 tumors, present 6
  Vascular invasion, present 2
  Largest size, >3 cm 3
  Tumor number, >3 2

AFP, alpha-fetoprotein; RETREAT, Risk Estimation of Tumor Recurrence After Transplant; LT, liver transplantation; NLR, neutrophil-tolymphocyte ratio; RFS, recurrence-free survival.