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

Radiomics model based on contrast-enhanced computed tomography imaging for early recurrence monitoring after radical resection of AFP-negative hepatocellular carcinoma

BACKGROUND

Although radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. Emerging radiomics can reveal subtle structural changes in tumors by analyzing preoperative contrast-enhanced computer tomography (CECT) imaging data and may provide new ways to predict early recurrence (recurrence within 2 years) in AFP-negative HCC. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC.

PATIENTS AND METHODS

Patients with AFP-negative HCC who underwent radical resection were included in this study. A computerized tool was used to extract radiomic features from the tumor region of interest (ROI), select the best radiographic features associated with patient's postoperative recurrence, and use them to construct the radiomics score (RadScore), which was then combined with clinical and follow-up information to comprehensively evaluate the reliability of the model.

RESULTS

A total of 148 patients with AFP-negative HCC were enrolled in this study, and 1,977 radiographic features were extracted from CECT, 2 of which were the features most associated with recurrence in AFP-negative HCC. They had good predictive ability in both the training and validation cohorts, with an area under the ROC curve (AUC) of 0.709 and 0.764, respectively. Tumor number, microvascular invasion (MVI), AGPR and radiomic features were independent risk factors for early postoperative recurrence in patients with AFP-negative HCC. The AUCs of the integrated model in the training and validation cohorts were 0.793 and 0.791, respectively. The integrated model possessed the clinical value of predicting early postoperative recurrence in patients with AFP-negative HCC according to decision curve analysis, which allowed the classification of patients into subgroups of high-risk and low-risk for early recurrence.

CONCLUSION

The nomogram constructed by combining clinical and imaging features has favorable performance in predicting the probability of early postoperative recurrence in AFP-negative HCC patients, which can help optimize the therapeutic decision-making and prognostic assessment of AFP-negative HCC patients.

Which factors predict tumor recurrence and survival after curative hepatectomy in hepatocellular carcinoma? Results from a European institution

BACKGROUND

High tumor recurrence and dismal survival rates after curative intended resection for hepatocellular carcinoma (HCC) are still concerning. The primary goal was to assess predictive factors associated with disease-free (DFS) and overall survival (OS) in a subset of patients with HCC undergoing hepatic resection (HR).

METHODS

Between 08/2004-7/2021, HR for HCC was performed in 188 patients at our institution. Data allocation was conducted from a prospectively maintained database. The prognostic impact of clinico-pathological factors on DFS and OS was assessed by using uni- and multivariate Cox regression analyses. Survival curves were generated with the Kaplan Meier method.

RESULTS

The postoperative 1-, 3- and 5- year overall DFS and OS rates were 77.9%, 49.7%, 41% and 72.7%, 54.7%, 38.8%, respectively. Tumor diameter ≥ 45 mm [HR 1.725; (95% CI 1.091-2.727); p = 0.020], intra-abdominal abscess [HR 3.812; (95% CI 1.859-7.815); p < 0.0001], and preoperative chronic alcohol abuse [HR 1.831; (95% CI 1.102-3.042); p = 0.020] were independently predictive for DFS while diabetes mellitus [HR 1.714; (95% CI 1.147-2.561); p = 0.009), M-Stage [HR 2.656; (95% CI 1.034-6.826); p = 0.042], V-Stage [HR 1.946; (95% CI 1.299-2.915); p = 0.001, Sepsis [HR 10.999; (95% CI 5.167-23.412); p < 0.0001], and ISGLS B/C [HR 2.008; (95% CI 1.273-3.168); p = 0.003] were significant determinants of OS.

CONCLUSIONS

Despite high postoperative recurrence rates, an acceptable long-term survival in patients after curative HR could be achieved. The Identification of parameters related to OS and DFS improves patient-centered treatment and surveillance strategies.

Analytical validation and algorithm improvement of HepatoPredict kit to assess hepatocellular carcinoma prognosis before a liver transplantation

Objectives

To verify the analytical performance of the HepatoPredict kit, a novel tool developed to stratify Hepatocellular Carcinoma (HCC) patients according to their risk of relapse after a Liver Transplantation (LT).

Methods

The HepatoPredict tool combines clinical variables and a gene expression signature in an ensemble of machine-learning algorithms to forecast the benefit of a LT in HCC patients. To ensure the accuracy and reliability of this method, extensive analytical validation was conducted to verify its specificity and robustness. The experiments were designed following the guidelines for multi-target genomic assays such as ISO201395-2019, MIQE, CLSI-MM16, CLSI-MM17, and CLSI-EP17-A. The validation process included reproducibility between operators and between RNA extractions and RT-qPCR runs, and interference of input RNA levels or varying reagent levels. A recently retrained version of the HepatoPredict algorithms was also tested.

Results

The validation process demonstrated that the HepatoPredict kit met the required standards for robustness (p > 0.05), analytical specificity (inclusivity of 95 %), and sensitivity (LoB, LoD, linear range, and amplification efficiency between 90 and 110 %). The operator, equipment, input RNA, and reagents used had no significant effect on the HepatoPredict results. Additionally, the testing of a recently retrained version of the HepatoPredict algorithm, showed that this new version further improved the accuracy of the kit and performed better than existing clinical criteria in accurately identifying HCC patients who are more likely to benefit LT.

Conclusions

Even with the introduced variations in molecular and clinical variables, the HepatoPredict kit's prognostic information remains consistent. It can accurately identify HCC patients who are more likely to benefit from a LT. Its robust performance also confirms that it can be easily integrated into standard diagnostic laboratories.

From prediction to prevention: Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring

In this editorial, we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma. Hepatocellular carcinoma (HCC), which is characterized by high incidence and mortality rates, remains a major global health challenge primarily due to the critical issue of postoperative recurrence. Early recurrence, defined as recurrence that occurs within 2 years posttreatment, is linked to the hidden spread of the primary tumor and significantly impacts patient survival. Traditional predictive factors, including both patient- and treatment-related factors, have limited predictive ability with respect to HCC recurrence. The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research. The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence. Chall-enges persist, including sample size constraints, issues with handling data, and the need for further validation and interpretability. This study emphasizes the need for collaborative efforts, multicenter studies and comparative analyses to validate and refine the model. Overcoming these challenges and exploring innovative approaches, such as multi-omics integration, will enhance personalized oncology care. This study marks a significant stride toward precise, effi-cient, and personalized oncology practices, thus offering hope for improved patient outcomes in the field of HCC treatment.

Serum alpha-fetoprotein response as a preoperative prognostic indicator in unresectable hepatocellular carcinoma with salvage hepatectomy following conversion therapy: a multicenter retrospective study

Background

This study evaluates the efficacy of alpha-fetoprotein (AFP) response as a surrogate marker for determining recurrence-free survival (RFS) in patients with unresectable hepatocellular carcinoma (uHCC) who undergo salvage hepatectomy following conversion therapy with tyrosine kinase inhibitor (TKI) and anti-PD-1 antibody-based regimen.

Methods

This multicenter retrospective study included 74 patients with uHCC and positive AFP (>20 ng/mL) at diagnosis, who underwent salvage hepatectomy after treatment with TKIs and anti-PD-1 antibody-based regimens. The association between AFP response-defined as a ≥ 80% decrease in final AFP levels before salvage hepatectomy from diagnosis-and RFS post-hepatectomy was investigated.

Results

AFP responders demonstrated significantly better postoperative RFS compared to non-responders (P<0.001). The median RFS was not reached for AFP responders, with 1-year and 2-year RFS rates of 81.3% and 70.8%, respectively. In contrast, AFP non-responders had a median RFS of 7.43 months, with 1-year and 2-year RFS rates at 37.1% and 37.1%, respectively. Multivariate Cox regression analysis identified AFP response as an independent predictor of RFS. Integrating AFP response with radiologic tumor response facilitated further stratification of patients into distinct risk categories: those with radiologic remission experienced the most favorable RFS, followed by patients with partial response/stable disease and AFP response, and the least favorable RFS among patients with partial response/stable disease but without AFP response. Sensitivity analyses further confirmed the association between AFP response and improved RFS across various cutoff values and in patients with AFP ≥ 200 ng/mL at diagnosis (all P<0.05).

Conclusion

The "20-80" rule based on AFP response could be helpful for clinicians to preoperatively stratify the risk of patients undergoing salvage hepatectomy, enabling identification and management of those unlikely to benefit from this procedure.

Multidisciplinary Treatment of Hepatocellular Carcinoma in 2023: Italian practice Treatment Guidelines of the Italian Association for the Study of the Liver (AISF), Italian Association of Medical Oncology (AIOM), Italian Association of Hepato-Bilio-Pancreatic Surgery (AICEP), Italian Association of Hospital Gastroenterologists (AIGO), Italian Association of Radiology and Clinical Oncology (AIRO), Italian Society of Pathological Anatomy and Diagnostic Cytology (SIAPeC-IAP), Italian Society of Surgery (SIC), Italian Society of Gastroenterology (SIGE), Italian Society of Medical and Interventional Radiology (SIRM), Italian Organ Transplant Society (SITO), and Association of Patients with Hepatitis and Liver Disease (EpaC) - Part I - Surgical treatments

Worldwide, hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. The remarkable improvements in treating HCC achieved in the last years have increased the complexity of HCC management. Following the need to have updated guidelines on the multidisciplinary treatment management of HCC, the Italian Scientific Societies involved in the management of this cancer have promoted the drafting of a new dedicated document. This document was drawn up according to the GRADE methodology needed to produce guidelines based on evidence. Here is presented the first part of guidelines, focused on the multidisciplinary tumor board of experts and surgical treatments of HCC.

Molecular profiling in the management of hepatocellular carcinoma

PURPOSE OF REVIEW

The purpose of this review is to both summarize the current knowledge of hepatocellular carcinoma molecular biology and to suggest a framework in which to prospectively translate this knowledge into patient care. This is timely as recent guidelines recommend increased use of these technologies to advance personalized liver cancer care.

RECENT FINDINGS

The main themes covered here address germline and somatic genetic alterations recently discovered in hepatocellular carcinoma, largely owing to next generation sequencing technologies, and nascent efforts to translate these into contemporary practice.

SUMMARY

Early efforts of translating molecular profiling to hepatocellular carcinoma care demonstrate a growing number of potentially actionable alterations. Still lacking are a consensus on what biomarkers and technologies to adopt, at what scale and cost, and how to integrate them most effectively into care.

PIVKA-II combined with tumor burden score to predict long-term outcomes of AFP-negative hepatocellular carcinoma patients after liver resection

BACKGROUND

This study aimed to establish a simple prognostic scoring model based on tumor burden score (TBS) and PIVKA-II to predict long-term outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients.

METHODS

511 patients were divided into the training cohort (n = 305) and the validation cohort (n = 206) at a ratio of 6:4. Receiver operating characteristic curves (ROC) were established to identify cutoff values of TBS and PIVKA-II. Kaplan-Meier curves were used to analyze survival outcomes. The multivariable Cox regression was used to identify variables independently associated with survival outcomes. The predictive performance of the TBS-PIVKA II score (TPS) model was compared with Barcelona clinic liver cancer (BCLC) stage and American Joint Committee on Cancer (AJCC TNM) stage.

RESULTS

The present study established the TPS model using a simple scoring system (0, 1 for low/high TBS [cutoff value: 4.1]; 0, 1 for low/high PIVKA-II [cutoff value: 239 mAU/mL]). The TPS scoring model was divided into three levels according to the summation of TBS score and PIVKA-II score: TPS 0, TPS 1, and TPS 2. The TPS scoring model was able to stratify OS (training: p < 0.001, validation: p < 0.001) and early recurrence (training: p < 0.001; validation: p = 0.001) in the training cohort and the validation cohort. The TPS score was independently associated with OS (TPS 1 vs. 0, HR: 2.28, 95% CI: 1.01-5.17; TPS 2 vs. 0, HR: 4.21, 95% CI: 2.01-8.84) and early recurrence (TPS 1 vs. 0, HR: 3.50, 95% CI: 1.71-7.16; TPS 2 vs. 0, HR: 3.79, 95% CI: 1.86-7.75) in the training cohort. The TPS scoring model outperformed BCLC stage and AJCC TNM stage in predicting OS and early recurrence in the training cohort and the validation cohort. But the TPS scoring model was unable to stratify the late recurrence in the training cohort (p = 0.872) and the validation cohort (p = 0.458).

CONCLUSIONS

The TPS model outperformed the BCLC stage and AJCC TNM stage in predicting OS and early recurrence of AFP-negative HCC patients after liver resection, which might better assist surgeons in screening AFP-negative HCC patients who may benefit from liver resection.

Prognostic implications of alpha-fetoprotein and C-reactive protein elevation in hepatocellular carcinoma following resection (PACE): a large cohort study of 2770 patients

BACKGROUND

Routine clinical staging for hepatocellular carcinoma (HCC) incorporates liver function, general health, and tumor morphology. Further refinement of prognostic assessments and treatment decisions may benefit from the inclusion of tumor biological marker alpha-fetoprotein (AFP) and systemic inflammation indicator C-reactive protein (CRP).

METHODS

Data from a multicenter cohort of 2770 HCC patients undergoing hepatectomy were analyzed. We developed the PACE risk score (Prognostic implications of AFP and CRP Elevation) after initially assessing preoperative AFP and CRP's prognostic value. Subgroup analyzes were performed in BCLC cohorts A and B using multivariable Cox analysis to evaluate the prognostic stratification ability of the PACE risk score and its complementary utility for BCLC staging.

RESULTS

Preoperative AFP ≥ 400ng/mL and CRP ≥ 10 mg/L emerged as independent predictors of poorer prognosis in HCC patients who underwent hepatectomy, leading to the creation of the PACE risk score. PACE risk score stratified patients into low, intermediate, and high-risk groups with cumulative 5-year overall (OS) and recurrence-free survival (RFS) rates of 59.6%/44.9%, 43.9%/38.4%, and 20.6%/18.0% respectively (all P < 0.001). Increased PACE risk scores correlated significantly with early recurrence and extrahepatic metastases frequency (all P < 0.001). The multivariable analysis identified intermediate and high-risk PACE scores as independently correlating with poor postoperative OS and RFS. Furthermore, the PACE risk score proficiently stratified the prognosis of BCLC stages A and B patients, with multivariable analyses demonstrating it as an independent prognostic determinant for both stages.

CONCLUSION

The PACE risk score serves as an effective tool for postoperative risk stratification, potentially supplementing the BCLC staging system.

Incorporation of protein induced by vitamin K absence or antagonist-II into transplant criteria expands beneficiaries of liver transplantation for hepatocellular carcinoma: a multicenter retrospective cohort study in China

INTRODUCTION

In order to maximize the utilization of precious donor liver, precisely determining potential hepatocellular carcinoma (HCC) candidates who will benefit from liver transplantation (LT) is essential. As a crucial diagnostic biomarker for HCC, protein induced by vitamin K absence or antagonist-II (PIVKA-II) has become one of the key indicators for assessing tumor recurrence risk after LT. This study aims to investigate the role of PIVKA-II in recipient selection and prognostic stratification.

METHODS

The clinicopathologic data of HCC patients undergoing LT from 2015 to 2020 in six Chinese transplant centers were collected. Univariate and multivariate analyses were performed to determine risk factors for disease free survival (DFS). Based on these risk factors, survival analysis was made by Kaplan-Meier method and their value in prognostic stratification was assessed.

RESULTS

A total of 522 eligible HCC patients with pre-LT PIVKA-II records were finally included in this study. Tumor burden>8 cm, α-fetoprotein>400 ng/ml, histopathologic grade III and PIVKA-II>240 mAU/ml were identified as independent risk factors for DFS. DFS of patients with PIVKA-II≤240 mAU/ml ( N =288) were significantly higher than those with PIVKA-II>240 mAU/ml ( N =234) (1-year, 3-year, and 5-year DFS: 83.2, 77.3, and 75.9% vs. 75.1, 58.5, and 50.5%; P <0.001). Compared with Hangzhou criteria ( N =305), incorporating PIVKA-II into Hangzhou criteria (including tumor burden, α-fetoprotein, and histopathologic grade) increased the number of patients with eligibility for LT by 21.6% but achieved comparable DFS and overall survival.

CONCLUSIONS

Incorporating PIVKA-II into existing LT criteria could increase the number of eligible HCC patients without compromising post-LT outcomes.

Transplant Oncology: An Emerging Discipline of Cancer Treatment

Transplant oncology is an emerging concept of cancer treatment with a promising prospective outcome. The applications of oncology, transplant medicine, and surgery are the core of transplant oncology to improve patients' survival and quality of life. The main concept of transplant oncology is to radically cure cancer by removing the diseased organ and replacing it with a healthy one, aiming to improve the survival outcomes and quality of life of cancer patients. Subsequently, it seeks to expand the treatment options and research for hepatobiliary malignancies, which have seen significantly improved survival outcomes after the implementation of liver transplantation (LT). In the case of colorectal cancer (CRC) in the transplant setting, where the liver is the most common site of metastasis of patients who are considered to have unresectable disease, initial studies have shown improved survival for LT treatment compared to palliative therapy interventions. The indications of LT for hepatobiliary malignancies have been slowly expanded over the years beyond Milan criteria in a stepwise manner. However, the outcome improvements and overall patient survival are limited to the specifics of the setting and systematic intervention options. This review aims to illustrate the representative concepts and history of transplant oncology as an emerging discipline for the management of hepatobiliary malignancies, in addition to other emerging concepts, such as the uses of immunotherapy in a peri-transplant setting as well as the use of circulating tumor DNA (ctDNA) for surveillance post-transplantation.

European Society of Organ Transplantation (ESOT) Consensus Report on Downstaging, Bridging and Immunotherapy in Liver Transplantation for Hepatocellular Carcinoma

Liver transplantation offers the best chance of cure for most patients with non-metastatic hepatocellular carcinoma (HCC). Although not all patients with HCC are eligible for liver transplantation at diagnosis, some can be downstaged using locoregional treatments such as ablation and transarterial chemoembolization. These aforementioned treatments are being applied as bridging therapies to keep patients within transplant criteria and to avoid them from dropping out of the waiting list while awaiting a liver transplant. Moreover, immunotherapy might have great potential to support downstaging and bridging therapies. To address the contemporary status of downstaging, bridging, and immunotherapy in liver transplantation for HCC, European Society of Organ Transplantation (ESOT) convened a dedicated working group comprised of experts in the treatment of HCC to review literature and to develop guidelines pertaining to this cause that were subsequently discussed and voted during the Transplant Learning Journey (TLJ) 3.0 Consensus Conference that took place in person in Prague. The findings and recommendations of the working group on Downstaging, Bridging and Immunotherapy in Liver Transplantation for Hepatocellular Carcinoma are presented in this article.

Management of early-stage hepatocellular carcinoma: challenges and strategies for optimal outcomes

Although hepatocellular carcinoma (HCC) is associated with a poor prognosis, management of early-stage HCC is often successful with highly efficacious treatment modalities such as liver transplantation, surgical resection, and radiofrequency ablation. However, unfavorable clinical outcomes have been observed under certain circumstances, even after efficient treatment. Factors that predict unsuitable results after treatment include tumor markers, inflammatory markers, imaging findings reflecting tumor biology, specific outcome indicators for each treatment modality, liver functional reserve, and the technical feasibility of the treatment modalities. Various strategies may overcome these challenges, including the application of reinforced treatment indication criteria with predictive markers reflecting tumor biology, compensation for technical issues with up-to-date technologies, modification of treatment modalities, downstaging with locoregional therapies (such as transarterial chemotherapy or radiotherapy), and recently introduced combination immunotherapies. In this review, we discuss the challenges to achieving optimal outcomes in the management of early-stage HCC and suggest strategies to overcome these obstacles.

Multiparametric MRI-based model for prediction of local progression of hepatocellular carcinoma after thermal ablation

PURPOSE

To develop a deep learning radiomics of multiparametric magnetic resonance imaging (DLRMM)-based model that incorporates preoperative and postoperative signatures for prediction of local tumor progression (LTP) after thermal ablation (TA) in hepatocellular carcinoma (HCC).

METHODS

From May 2017 to October 2021, 417 eligible patients with HCC were retrospectively enrolled from three hospitals (one primary cohort [PC, n = 189] and two external test cohorts [ETCs][n = 135, 93]). DLRMM features were extracted from T1WI + C, T2WI, and DWI using ResNet18 model. An integrative model incorporating the DLRMM signature with clinicopathologic variables were further built to LTP risk stratification. The performance of these models were compared by areas under receiver operating characteristic curve (AUC) using DeLong test.

RESULTS

A total of 1668 subsequences and 31,536 multiparametric MRI slice including T1WI, T2WI, and DWI were collected simultaneously. The DLRMM signatures were extracted from tumor and ablation zone, respectively. Ablative margin, multiple tumors, and tumor abutting major vessels were regarded as risk factors for LTP in clinical model. The AUC of DLRMM model were 0.864 in PC, 0.843 in ETC1, and 0.858 in ETC2, which was higher significantly than those in clinical model (p < 0.001). After integrating clinical variable, DLRMM model obtained significant improvement with AUC of 0.870-0.869 in three cohorts (all, p < 0.001), which can provide the risk stratification for overall survival of HCC patients.

CONCLUSIONS

The DLRMM model is essential to identify LTP risk of HCC patients who underwent TA and may potentially benefit personalized decision-making.

Prognosis of Patients with Hepatocellular Carcinoma Treated with Transarterial Chemoembolization(MC-hccAI 001): Development and Validation of the ALFP Score

Background

Transarterial chemoembolization (TACE) is the recommended first-line treatment for intermediate-stage Hepatocellular carcinoma (HCC) patients. However, predicting the survival of HCC patients receiving TACE remains challenging.

Methods

In this retrospective study, we analyzed a total of 1805 HCC patients who received TACE. The patients were randomly divided into a training set (n = 1264) and a validation set (n = 541). We examined various prognostic factors within the training set and developed a simple ALFP (ALBI grade, AFP, and Prothrombin time) score, which was subsequently validated using the independent validation set.

Results

Our multivariate analysis revealed that baseline ALBI grade 2 or 3, AFP ≥ 100 ng/mL, and PT > 13.1 s were independent unfavorable prognostic factors for HCC patients receiving TACE (p < 0.05). Based on these findings, we constructed the ALFP score, which assigns 1 point each for ALBI grade 2 or 3, AFP ≥ 100 ng/mL, and PT > 13.1 s. The score has a range of 0 to 3, and higher scores are associated with poorer outcomes. The median overall survival (OS) varied significantly among different ALFP score groups, both in the training set and the validation set (p < 0.001). We further examined the ALFP score in subgroups based on tumor diameter and the number of intrahepatic lesions. In each subgroup, higher ALFP scores were consistently associated with lower OS (p < 0.05).

Conclusion

Our study confirms the prognostic value of the ALFP score in predicting the survival of HCC patients undergoing TACE. The score incorporates easily obtainable baseline parameters and provides a simple and practical tool for risk stratification and treatment decision-making in HCC patients.

Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation

BACKGROUND AND PURPOSE

Tumor recurrence after liver transplantation (LT) impedes the curative chance for hepatocellular carcinoma (HCC) patients. This study aimed to develop a deep pathomics score (DPS) for predicting tumor recurrence after liver transplantation using deep learning.

PATIENTS AND METHODS

Two datasets of 380 HCC patients who underwent LT were enrolled. Residual convolutional neural networks were used to identify six histological structures of HCC. The individual risk score of each structure and DPS were derived by a modified DeepSurv network. Cox regression analysis and Concordance index were used to evaluate the prognostic significance. The cellular exploration of prognostic immune biomarkers was performed by quantitative and spatial proximity analysis according to three panels of 7-color immunofluorescence.

RESULTS

The overall classification accuracy of HCC tissue was 97%. At the structural level, immune cells were the most significant tissue category for predicting post-LT recurrence (HR 1.907, 95% CI 1.490-2.440). The C-indices of DPS achieved 0.827 and 0.794 in the training and validation cohorts, respectively. Multivariate analysis for recurrence-free survival (RFS) showed that DPS (HR 4.795, 95% CI 3.017-7.619) was an independent risk factor. Patients in the high-risk subgroup had a shorter RFS, larger tumor diameter and a lower proportion of clear tumor borders. At the cellular level, a higher infiltration of intratumoral NK cells was negatively correlated with recurrence risk.

CONCLUSIONS

This study established an effective DPS. Immune cells were the most significant histological structure related to HCC recurrence. DPS performed well in post-LT recurrence prediction and the identification of clinicopathological features.

Radiomics model based on contrast-enhanced computed tomography to predict early recurrence in patients with hepatocellular carcinoma after radical resection

BACKGROUND

Radical resection remains an effective strategy for patients with hepatocellular carcinoma (HCC). Unfortunately, the postoperative early recurrence (recurrence within 2 years) rate is still high.

AIM

To develop a radiomics model based on preoperative contrast-enhanced computed tomography (CECT) to evaluate early recurrence in HCC patients with a single tumour.

METHODS

We enrolled a total of 402 HCC patients from two centres who were diagnosed with a single tumour and underwent radical resection. First, the features from the portal venous and arterial phases of CECT were extracted based on the region of interest, and the early recurrence-related radiomics features were selected via the least absolute shrinkage and selection operator proportional hazards model (LASSO Cox) to determine radiomics scores for each patient. Then, the clinicopathologic data were combined to develop a model to predict early recurrence by Cox regression. Finally, we evaluated the prediction performance of this model by multiple methods.

RESULTS

A total of 1915 radiomics features were extracted from CECT images, and 31 of them were used to determine the radiomics scores, which showed a significant difference between the early recurrence and nonearly recurrence groups. Univariate and multivariate Cox regression analyses showed that radiomics scores and serum alpha-fetoprotein were independent indicators, and they were used to develop a combined model to predict early recurrence. The area under the receiver operating characteristic curve values for the training and validation cohorts were 0.77 and 0.74, respectively, while the C-indices were 0.712 and 0.674, respectively. The calibration curves and decision curve analysis showed satisfactory accuracy and clinical utilities. Kaplan-Meier curves based on recurrence-free survival and overall survival showed significant differences.

CONCLUSION

The preoperative radiomics model was shown to be effective for predicting early recurrence among HCC patients with a single tumour.

The outcomes and prognostic factors of patients with hepatocellular carcinoma and normal serum alpha fetoprotein levels

BACKGROUND

Alpha fetoprotein (AFP) is the most widely used tumor marker for hepatocellular carcinoma (HCC). Nevertheless, few studies have investigated the prognostic factors of HCC patients with normal serum AFP levels.

METHODS

We retrospectively enrolled 2198 patients with HCC and normal serum AFP levels (<20 ng/mL) from 2007 to 2020. Overall survival (OS) rates were calculated by the Kaplan-Meier method, and analyses of the prognostic factors were performed using a Cox proportional hazard model.

RESULTS

Among the enrolled patients, 1385 (63%) patients were in the low-normal AFP group (serum AFP levels ≤7 ng/mL), and 813 (37%) patients were in the high-normal AFP group (serum AFP levels between 7 and 20 ng/mL). The high-normal AFP group had poorer liver functional reserve, more multiple tumors, and smaller tumor size compared to those in the low-normal AFP group. After a median follow-up of 32.4 months, 942 patients died, and the 5-year OS rate was 54.4%. The 5-year OS rates were 57.4% and 49.8% in the low-normal AFP group and high-normal AFP group, respectively (p = 0.001). A multivariate analysis showed the independent prognostic factors of poor OS were no anti-viral therapy, advanced albumin-bilirubin grades, the presence of vascular invasion, tumor size ≥5 cm, and non-curative treatment modalities. Serum AFP levels were not associated with OS according to the multivariate analysis.

CONCLUSION

Liver functional reserve, anti-viral therapy, tumor size, vascular invasion, and treatment modalities, determined the outcomes of HCC patients with normal serum AFP levels, but serum AFP levels did not.

Construction and validation of a survival prognostic model for stage III hepatocellular carcinoma: a real-world, multicenter clinical study

OBJECTIVE

To construct a survival prediction model for patients with TNM stage III hepatocellular carcinoma (HCC) to guide the clinical diagnosis and treatment of HCC patients and improve prognosis.

METHODS

Based on data from patients with stage III (AJCC 7th TNM stage) recorded by the American Institute of Cancer Research from 2010 to 2013, risk factors affecting the prognosis were screened by Cox univariate and multivariate regression, line plots was constructed, and the credibility of the model was verified by Boostrap method. ROC operating curves, calibration curves and DCA clinical decision curves were used to evaluate the model, and Kaplan-Meier was used for survival analysis was used to evaluate the efficacy of the model. External survival data from patients newly diagnosed with stage III hepatocellular carcinoma during 2014-2015 were used to validate and fit the model and to optimize the model.

RESULTS

Age > 75 years vs.18-53 years [HR = 1.502; 95%CI(1.134-1.990)], stage IIIC vs. Stage IIIA [HR = 1.930; 95%CI(1.509-2.470)], lobotomy vs. non-surgery [HR = 0.295; 95%CI(0.228-0.383)], radiotherapy vs. non-radiotherapy [HR = 0.481; 95%CI(0.373-0.619)], chemotherapy vs. Non-chemotherapy [HR = 0.443; 95%CI(0.381-0.515)], positive serum AFP before treatment vs. negative [HR = 1.667; 95%CI(1.356-2.049)], the above indicators are independent prognostic factors for patients with stage III hepatocellular carcinoma, and the P values for the above results were less than 0.05. A joint prediction model was constructed based on age, TNM stage, whether and how to operate, whether to receive radiotherapy, whether to receive chemotherapy, pre-treatment serum AFP status and liver fibrosis score. The consistency index of the improved prognosis model was 0.725.

CONCLUSIONS

The traditional TNM staging has limitations for clinical diagnosis and treatment, while the Nomogram model modified by TNM staging has good predictive efficacy and clinical significance.

Impact of Hypothermic Oxygenated Machine Perfusion on Hepatocellular Carcinoma Recurrence after Liver Transplantation

BACKGROUND

Machine perfusion may be able to mitigate ischemia-reperfusion injury (IRI), which increases hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT). This study aimed to investigate the impact of dual-hypothermic oxygenated machine perfusion (D-HOPE) on HCC recurrence in LT.

METHODS

A single-center retrospective study was conducted from 2016 to 2020. Pre- and postoperative data of HCC patients undergoing LT were analyzed. Recipients of a D-HOPE-treated graft were compared to those of livers preserved using static cold storage (SCS). The primary endpoint was recurrence-free survival (RFS).

RESULTS

Of 326 patients, 246 received an SCS-preserved liver and 80 received a D-HOPE-treated graft (donation after brain death (DBD), n = 66; donation after circulatory death (DCD), n = 14). Donors of D-HOPE-treated grafts were older and had higher BMI. All DCD donors were treated by normothermic regional perfusion and D-HOPE. The groups were comparable in terms of HCC features and estimated 5-year RFS according to the Metroticket 2.0 model. D-HOPE did not reduce HCC recurrence (D-HOPE 10%; SCS 8.9%; p = 0.95), which was confirmed using Bayesian model averaging and inverse probability of treatment weighting-adjusted RFS analysis. Postoperative outcomes were comparable between groups, except for lower AST and ALT peak in the D-HOPE group.

CONCLUSIONS

In this single-center study, D-HOPE did not reduce HCC recurrence but allowed utilizing livers from extended criteria donors with comparable outcomes, improving access to LT for patients suffering from HCC.

The predictive value of the modified AFP model for liver transplantation outcomes in multinodular hepatocellular carcinoma patients

BACKGROUND

There is a lack of studies focusing on the benefit of liver transplantation (LT) in hepatocellular carcinoma (HCC) patients with > 3 tumors. This study aims to establish a model to effectively predict overall survival in Chinese HCC patients with multiple tumors (> 3 tumors) who undergo LT.

METHODS

This retrospective study included 434 HCC liver transplant recipients from the China Liver Transplant Registry. All HCC patients had more than 3 tumor nodules. Three selection criteria systems (i.e., AFP, Metroticket 2.0, and Up-to-7) were compared regarding the prediction of HCC recurrence. The modified AFP model was established by univariate and multivariate competing risk analyses.

RESULTS

The AFP score 2 and the AFP score ≥ 3 groups had 5-year recurrence rates of 19.6% and 40.5% in our cohort. The prediction of HCC recurrence based on the AFP model was associated with a c-statistic of 0.606, which was superior to the Up-to-7 and Metroticket 2.0 models. AFP level > 1000 ng/mL, largest tumor size ≥ 8 cm, vascular invasion, and MELD score ≥ 15 were associated with overall survival. The 5-year survival rate in the modified AFP score 0 group was 71.7%.

CONCLUSIONS

The AFP model is superior in predicting tumor recurrence in HCC patients with > 3 tumors prior to LT. With the modified AFP model, patients likely to derive sufficient benefit from LT can be identified.

2022 KLCA-NCC Korea practice guidelines for the management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

TBS-Based Preoperative Score to Predict Non-transplantable Recurrence and Identify Candidates for Upfront Resection Versus Transplantation for Hepatocellular Carcinoma

BACKGROUND

Recurrence following liver resection (LR) for hepatocellular carcinoma (HCC) can be as high as 50-70%. While salvage liver transplantation may be feasible, patients may develop a non-transplantable recurrence (NTR) (recurrence beyond Milan criteria). We sought to identify preoperative risk factors to predict NTR after resection.

PATIENTS AND METHODS

Patients who underwent curative-intent LR for HCC were identified from a multi-institutional database. Preoperative factors associated with NTR were identified and a risk score model (NTR score) was developed and validated.

RESULTS

Among 1620 patients, 842 (52.0%) developed recurrence; among patients with recurrence, NTR occurred in 341 (40.5%) with a median recurrence-free survival (RFS) of 30 months (24.7-35.3 months). On multivariable analysis, factors associated with NTR included alpha fetoprotein (AFP) > 400 ng/mL [hazard ratio (HR) 1.71, 95% confidence interval (CI) 1.33-2.19], albumin-bilirubin grade (ALBI) (referent low, medium ALBI: HR 1.41, 95% CI 1.10-1.81, high ALBI: HR 2.47, 95% CI 0.91-6.68), and tumor burden score (TBS) (referent low, high TBS: HR 2.55, 95% CI, 1.99-3.28). A simplified TBS-based NTR score was developed using the β-coefficients of each factor (C-index 0.68, 95% CI 0.65-0.71). Higher NTR score was associated with incrementally worse 5-year RFS (low 44.8%, medium 37.5%, high 24.5%) [area under the curve (AUC) 0.59] and increased incidence of NTR (low 13.7%, medium 25.4%, high 38.2%) (AUC 0.65) (both p < 0.001). Moreover, higher NTR score was associated with higher risk of extrahepatic recurrence (low 11.3%, medium 28.8%, high 37.5%) (p < 0.001).

CONCLUSION

NTR following curative-intent resection of HCC occurred in one in five patients. A simple TBS-based NTR score accurately predicted the risk of NTR and may help identify candidates for upfront resection versus transplantation.

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.

Homogeneous Electrochemical Immunoassay Using an Aggregation-Collision Strategy for Alpha-Fetoprotein Detection

Homogeneous immunoassays represent an attractive alternative to traditional heterogeneous assays due to their simplicity and high efficiency. Homogeneous electrochemical assays, however, are not commonly accessed due to the requirement of electrode immobilization of the recognition elements. Herein, we demonstrate a new homogeneous electrochemical immunoassay based on the aggregation-collision strategy for the quantification of tumor protein biomarker alpha-fetoprotein (AFP). The detection principle relies on the aggregation of AgNPs induced by the molecular biorecognition between AFP and AgNPs-anti-AFP probes, which leads to an increased AgNP size and decreased AgNP concentration, allowing an accurate self-validated dual-mode immunoassay by performing nanoimpact electrochemistry (NIE) of the oxidation of AgNPs. The intrinsic one-by-one analytical capability of NIE as well as the participation of all of the atoms of the AgNPs in signal transduction greatly elevates the detection sensitivity. Accordingly, the current sensor enables a limit of detection (LOD) of 5 pg/mL for AFP analysis with high specificity and efficiency. More importantly, reliable detection of AFP in diluted human sera of hepatocellular carcinoma (HCC) patients is successfully achieved, indicating that the NIE-based homogeneous immunoassay shows great potential in HCC liquid biopsy.

Development and validation of a modified albumin-bilirubin grade and α-fetoprotein score (mALF score) for hepatocellular carcinoma patients receiving atezolizumab and bevacizumab

AIM

Predicting the survival of hepatocellular carcinoma (HCC) patients receiving atezolizumab and bevacizumab (Atez/bev) remains a challenge. This study aims to validate the modified albumin-bilirubin grade and α-fetoprotein score (mALF score).

METHODS

This retrospective, multicenter study included 426 HCC patients receiving Atez/Bev. Each patient was randomized 3:2 to a training set (n = 255) and a validation set (n = 171). We investigated prognostic factors in the training set and developed an easily applicable mALF score, which was evaluated in the validation set.

RESULTS

We built the mALF score using baseline mALBI grade 2b or 3 (HR 2.36, 95% CI 1.37-4.05, p = 0.002) and α-fetoprotein ≥ 100 ng/ml (HR 2.61, 95% CI 1.49-4.55, p < 0.001), which were identified as unfavorable prognostic factors in a multivariate analysis. The 1-year OS rates were 82.7% (95% CI 68.9-90.8) in patients who meet neither of the criteria (mALF 0 points, n = 101), 61.7% (95% CI 44.5-74.9) in patients who meet either of the two criteria (mALF 1 point, n = 109), and 24.6% (95% CI 9.0-44.3) in patients who meet both criteria (mALF 2 points, n = 45); the difference was statistically significant (p < 0.001). The median PFS in patients with mALF 0, 1, and 2 points was 9.5 months (95% CI 4.3-NA), 6.6 months (95% CI 6.0-8.0), and 3.8 months (95% CI 3.0-5.2), respectively, which amounted to a significant difference (p < 0.001). These results were confirmed in the validation set (1-year OS rates, 0/1/2 points = 94.2%/62.1%/46.3%, p < 0.001; median PFS, 0/1/2 points = 9.3/6.7/4.7 months, p = 0.018).

CONCLUSION

The mALF score can reliably predict the prognosis of HCC patients receiving Atez/Bev.

Follow-up value of serum AFP and aminotransferases in chronic hepatitis B progression

Introduction

Chronic viral hepatitis (CH) is a stage prior to cirrhosis and primary cancer. Standard protocols for CH assessment during the long follow-up period are of great importance for precise treatment and living quality improvement. In this study, we aimed to analyze multiple serum indexes in chronic hepatitis B (CHB)-infected patients and to discuss their combined values in clinical applications.

Methods

Total 503 lines of laboratory data from 2012 to 2021 were extracted from103 CHB patients who were followed-up in our hospital. They were divided into the remission group and the progression group according to their complete clinical information and laboratory data. A series of models of serum indexes were analyzed to illustrate the fluctuation trend of @ach index in a time-dependent manner.

Results

The models revealed that abundant serum alpha-fetoprotein (AFP) in the remission group was characteristically associated with hepatocyte destruction markers aspartate aminotransferase (AST) and alanine aminotransferase and favored a much longer progression-free period (P 0.0001). A model-derived equation consisting of serum AFP and AST values showed a good performance (83% reliability) to distinguish the two groups.

Discussion

This study clearly demonstrates the intrinsic quantitative relationship between serum AFP and liver aminotransferases involving antivirus treatment response. The model-based equation compensates for serum hepatitis B virus DNA detection during outpatient follow-up and it may serve as a useful laboratory tool for CHB progression assessment.

Development of a Risk Classifier to Predict Tumor Recurrence and Lenvatinib Benefits in Hepatocellular Carcinoma After Liver Transplantation

BACKGROUND

Current selection tools were not precise enough to predict recurrence of hepatocellular carcinoma (HCC) and benefit of adjuvant lenvatinib for patients who received liver transplant (LT) for HCC. Thus, we aim at developing a risk classifier to predict recurrence of HCC and benefit of adjuvant Lenvatinib for those who underwent LT for HCC.

METHODS

Cox regression model was applied to selected predictors and created the final model in a training cohort of 287 patients who underwent LT for HCC, which was tested in an internal validation cohort of 72 patients by using C-statistic and net classification index (NRI) compared with the following HCC selection criteria: the Milan criteria, the Up-to-7 criteria, and the University of California, San Francisco criteria.

RESULTS

We built a Risk Classifier of South China Cohort (RCOSC) based on 4 variables: the maximum diameter plus number of viable tumors, alpha-fetoprotein, microvascular invasion, and highest alanine aminotransferase in 7 days after LT. In validation analyses, our RCOSC showed good predictive performance (C-statistic, 0.866; 95% confidence interval [CI], 0.833-0.899) and had better prognostic value than Milan criteria (NRI, 0.406; P < .001), University of California, San Francisco (NRI, 0.497; P < .001), and Up-to-7 (NRI, 0.527; P < .001). By applying the RCOSC, we were able to accurately categorize patients into high-risk and low-risk groups. Further survival analysis revealed that the patients in the high-risk group might have a better therapeutic response to preventive regimen of lenvatinib after LT for HCC (hazard ratio, 0.38; 95% CI, 0.161-0.871, P = .018).

CONCLUSIONS

Our RCOSC presented favorable predictive performance for HCC recurrence. It might be capable of sifting out patients who benefit from adjuvant therapy after LT for HCC, providing a reliable tool for precise clinical decision-making of patients with HCC with LT.

AFP score and metroticket 2.0 perform similarly and could be used in a "within-ALL" clinical decision tool

Background & Aims

Two recently developed composite models, the alpha-fetoprotein (AFP) score and Metroticket 2.0, could be used to select patients with hepatocellular carcinoma (HCC) who are candidates for liver transplantation (LT). The aim of this study was to compare the predictive performance of both models and to evaluate the net risk reclassification of post-LT recurrence between them using each model's original thresholds.

Methods

This multicenter cohort study included 2,444 adult patients who underwent LT for HCC in 47 centers from Europe and Latin America. A competing risk regression analysis estimating sub-distribution hazard ratios (SHRs) and 95% CIs for recurrence was used (Fine and Gray method). Harrell's adapted c-statistics were estimated. The net reclassification index for recurrence was compared based on each model's original thresholds.

Results

During a median follow-up of 3.8 years, there were 310 recurrences and 496 competing events (20.3%). Both models predicted recurrence, HCC survival and survival better than Milan criteria (p <0.0001). At last tumor reassessment before LT, c-statistics did not significantly differ between the two composite models, either as original or threshold versions, for recurrence (0.72 vs. 0.68; p = 0.06), HCC survival, and overall survival after LT. We observed predictive gaps and overlaps between the model's thresholds, and no significant gain on reclassification. Patients meeting both models ("within-ALL") at last tumor reassessment presented the lowest 5-year cumulative incidence of HCC recurrence (7.7%; 95% CI 5.1-11.5) and higher 5-year post-LT survival (70.0%; 95% CI 64.9-74.6).

Conclusions

In this multicenter cohort, Metroticket 2.0 and the AFP score demonstrated a similar ability to predict HCC recurrence post-LT. The combination of these composite models might be a promising clinical approach.

Impact and implications

Composite models were recently proposed for the selection of liver transplant (LT) candidates among individuals with hepatocellular carcinoma (HCC). We found that both the AFP score and Metroticket 2.0 predicted post-LT HCC recurrence and survival better than Milan criteria; the Metroticket 2.0 did not result in better reclassification for transplant selection compared to the AFP score, with predictive gaps and overlaps between the two models; patients who met low-risk thresholds for both models had the lowest 5-year recurrence rate. We propose prospectively testing the combination of both models, to further optimize the LT selection process for candidates with HCC.

NUSAP1, a novel stemness-related protein, promotes early recurrence of hepatocellular carcinoma

Early recurrence (within 2 years after resection) is the primary cause of poor outcomes among hepatocellular carcinoma (HCC) patients, and liver cancer stem cells are the main contributors to postsurgical HCC recurrence. Nucleolar and spindle-associated protein 1 (NUSAP1) has been reported to be involved in tumor progression. We investigated the function and clinical value of NUSAP1 in early recurrence of HCC. Data from public datasets and our cohort were used to assess the association between NUSAP1 expression and early HCC recurrence. Gain- and loss-of-function experiments were carried out in vivo and in vitro. The predictive effect of NUSAP1 on early HCC recurrence was further evaluated by a validation cohort. We found that elevated NUSAP1 expression in HCC specimens was correlated with poor outcome, especially in cases with postoperative early recurrence. Functional studies indicated that NUSAP1 significantly promotes HCC progression. A postsurgical recurrence murine model further revealed that upregulated NUSAP1 dramatically increased the likelihood of HCC early recurrence. RNA sequencing data revealed that the gene sets of cancer stemness and the signal transducer and activator of transcription 3 (STAT3) pathway were enriched by NUSAP1 overexpression. Mechanistically, NUSAP1 enhanced cancer stemness through stimulating STAT3 nuclear translocation and activation through receptor of activated protein C kinase 1 (RACK1). In a validation cohort with 112 HCC patients, NUSAP1 effectively predicted HCC early recurrence. Our results indicated that NUSAP1 promotes early recurrence of HCC by sustaining cancer stemness and could serve as a valuable predictive indicator for postsurgical intervention in HCC patients.

Prediction of early recurrence of hepatocellular carcinoma after liver transplantation based on computed tomography radiomics nomogram

BACKGROUND

Early recurrence results in poor prognosis of patients with hepatocellular carcinoma (HCC) after liver transplantation (LT). This study aimed to explore the value of computed tomography (CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT.

METHODS

A cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled. A total of 1218 features were extracted from enhanced CT images. The least absolute shrinkage and selection operator algorithm (LASSO) logistic regression was used for dimension reduction and radiomics signature building. The clinical model was constructed after the analysis of clinical factors, and the nomogram was constructed by introducing the radiomics signature into the clinical model. The predictive performance and clinical usefulness of the three models were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA), respectively. Calibration curves were plotted to assess the calibration of the nomogram.

RESULTS

There were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort (P < 0.001) and validation cohort (P < 0.001). The nomogram showed the best predictive performance, with the largest area under the ROC curve in the training (0.882) and validation (0.917) cohorts. Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training (P = 0.138) and validation (P = 0.396) cohorts. DCA showed if the threshold probability is within 0.06-1, the nomogram had better clinical usefulness than the clinical model.

CONCLUSIONS

Our CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.

2022 KLCA-NCC Korea Practice Guidelines for the Management of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

Predictive machine learning model for microvascular invasion identification in hepatocellular carcinoma based on the LI-RADS system

Purposes

This study aimed to establish a predictive model of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) by contrast-enhanced computed tomography (CT), which relied on a combination of machine learning approach and imaging features covering Liver Imaging and Reporting and Data System (LI-RADS) features.

Methods

The retrospective study included 279 patients with surgery who underwent preoperative enhanced CT. They were randomly allocated to training set, validation set, and test set (167 patients vs. 56 patients vs. 56 patients, respectively). Significant imaging findings for predicting MVI were identified through the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression method. Predictive models were performed by machine learning algorithm, support vector machine (SVM), in the training set and validation set, and evaluated in the test set. Further, a combined model adding clinical findings to the radiologic model was developed. Based on the LI-RADS category, subgroup analyses were conducted.

Results

We included 116 patients with MVI which were diagnosed through pathological confirmation. Six imaging features were selected about MVI prediction: four LI-RADS features (corona enhancement, enhancing capsule, non-rim aterial phase hyperehancement, tumor size) and two non-LI-RADS features (internal arteries, non-smooth tumor margin). The radiological feature with the best accuracy was corona enhancement followed by internal arteries and tumor size. The accuracies of the radiological model and combined model were 0.725–0.714 and 0.802–0.732 in the training set, validation set, and test set, respectively. In the LR-4/5 subgroup, a sensitivity of 100% and an NPV of 100% were obtained by the high-sensitivity threshold. A specificity of 100% and a PPV of 100% were acquired through the high specificity threshold in the LR-M subgroup.

Conclusion

A combination of LI-RADS features and non-LI-RADS features and serum alpha-fetoprotein value could be applied as a preoperative biomarker for predicting MVI by the machine learning approach. Furthermore, its good performance in the subgroup by LI-RADS category may help optimize the management of HCC patients.

Clinically Applicable Homogeneous Assay for Serological Diagnosis of Alpha-Fetoprotein by Impact Electrochemistry

Tumor protein quantification with high specificity, sensitivity, and efficiency is of great significance to enable early diagnosis and effective treatment. The existing methods for protein analysis usually suffer from high cost, time-consuming operation, and insufficient sensitivity, making them not clinically friendly. In this work, a label-free homogeneous sensor based on the nano-impact electroanalytic (NIE) technique was proposed for the detection of tumor protein marker alpha-fetoprotein (AFP). The detection principle is based on the recovery of current of single PtNP catalyzed hydrazine oxidation due to the release of the pre-adsorbed passivating aptamers on PtNPs from the competition of the stronger binding between the specific interaction of the AFP aptamer and AFP. The intrinsic one-by-one analytical ability of NIE allows highly sensitive detection, which can be further improved by reducing the reaction/incubation volume. Meanwhile, the current sensor avoids a laborious labeling procedure as well as the separation and washing steps due to the in situ characteristic of NIE. Accordingly, the current sensor enables efficient, highly sensitive, and specific AFP analysis. More importantly, the reliable detection of AFP in diluted real sera from hepatocellular carcinoma (HCC) patients is successfully achieved, indicating that the impact electrochemistry-based sensing platform has great potential to be applied in point-of-care devices for HCC liquid biopsy.

Modified Albumin-Bilirubin Grade and Alpha-Fetoprotein Score (mALF Score) for Predicting the Prognosis of Hepatocellular Carcinoma after Hepatectomy

We developed and evaluated a modified albumin-bilirubin grade and α-fetoprotein (mALF) score, a nutritional and oncological assessment tool for patients with hepatocellular carcinoma (HCC) after surgical resection. Patients (n = 480) who underwent R0 resection between 2010 and 2020 were analyzed retrospectively. The mALF score assigned one point for a modified albumin-bilirubin (mALBI) grade 2b or 3 and one point for an α-fetoprotein (AFP) level ≥ 100 ng/mL. Patients were classified by mALF scores of 0 (mALBI grade 1/2a, AFP < 100 ng/mL), 1 (mALBI grade 2b/3 or AFP ≥ 100 ng/mL), or 2 (mALBI grade 2b/3, AFP ≥ 100 ng/mL) points. Liver reserve deteriorated and cancer progressed with increasing score. Postoperative complications (Clavien−Dindo classification ≥ 3) differed significantly among groups. The 5-year recurrence-free survival (RFS) rates were 34.8%, 11.2%, and 0.0% for 0, 1, and 2 points, respectively (1 or 2 versus 0 points, p < 0.001). The 5-year overall survival (OS) rates were 66.0%, 29.7%, and 17.8% for 0, 1, and 2 points, respectively (1 or 2 versus 0 points, p < 0.001). The mALF score was an independent prognostic predictor of RFS and OS. In HCC, the mALF score was effective for predicting postoperative complications and long-term survival.

Liver transplantation for hepatocellular carcinoma: Historical evolution of transplantation criteria

Liver transplantation (LT) for hepatocellular carcinoma is still a hot topic, and the main factor that is associated with the success of treatment is to determine the patients who will benefit from LT. Milan criteria have been defined 25 years ago and still is being used for patient selection for LT. However, in living donor LT, the Milan criteria is being extended. Current criteria for patient selection do not only consider morphologic characteristics such as tumor size and number of tumor nodules but also biologic markers that show tumor aggressiveness is also being considered. In the present review article, we have summarized all the criteria and scoring systems regarding LT for hepatocellular carcinoma. All criteria have 5-year overall survival rates that were comparable to the Milan Criteria and ranged between 60%-85%. On the other hand, it was seen that the recurrence rates had increased as the Milan criteria were exceeded; the 5-year recurrence rates ranged between 4.9% to 39.9%. Treatment of hepatocellular carcinoma needs a multidisciplinary approach. Ideal selection criteria are yet to be discovered. The same is true for treatment modalities. The goal will be achieved by a harmonic interplay between basic science researchers and clinicians.

2022 KLCA-NCC Korea practice guidelines for the management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

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

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.

Uncovering the Heterogeneity and Clinical Relevance of Circulating Tumor-Initiating Cells in Hepatocellular Carcinoma Using an Integrated Immunomagnetic-Microfluidic Platform

Circulating tumor-initiating cells (CTICs) with stem cell-like properties play pivotal roles in tumor metastasis and recurrence. However, little is known about the biology and clinical relevance of CTICs in hepatocellular carcinoma (HCC). Here, we investigated the molecular heterogeneity and clinical relevance of CTICs in HCC using a novel integrated immunomagnetic-microfluidic platform (iMAC). We constructed the iMAC and evaluated its ability to detect CTICs using a series of spiked cell experiments. A four-channel microfluidic chip was applied to investigate the composition of CTICs in patients with primary and recurrent HCC utilizing microbeads labeled with one of four stem-related markers: epithelial cell adhesion molecule (EpCAM), CD133, CD90, and CD24. The dynamic changes of these four CTIC subsets were serially monitored during treatment courses. Finally, single-cell RNA profiling was used to reveal the molecular characteristics of the four CTIC subsets. The iMAC platform detected significantly more EpCAM⁺ CTICs in the blood samples from 33 HCC patients than the FDA-approved CellSearch system (0.92 ± 0.94 vs 0.23 ± 0.36, P < 0.001). The number of EpCAM⁺ CTICs (≥0.75/mL) detected by iMAC was a predictor of early recurrence (P = 0.007). The distinct stem-related markers' expression of CTICs could distinguish primary HCC, recurrent HCC, and TACE-resistant HCC. Single-cell transcriptional profiling proved the heterogeneity among individual CTICs and separated the four CTIC subsets into distinct phenotypes. Dissecting the heterogeneity of CTICs using the iMAC represents a novel and informative method for accurate CTIC detection and characterization. This innovative technology will enable more indepth cancer biology research and clinical cancer management than is currently available.

The impact of biological features for a better prediction of posttransplant hepatocellular cancer recurrence

PURPOSE OF REVIEW

Morphological criteria (i.e., Milan Criteria) have been considered for a long time to be the best tool for selecting patients with hepatocellular cancer (HCC) waiting for liver transplantation (LT). In the last ten years, a refinement of the selection criteria has been observed, with the introduction of biological tumor characteristics enabling to enlarge the number of potential transplant candidates and to select LT candidates with a lower risk of posttransplant recurrence.

RECENT FINDINGS

Several biological tumor aspects have been explored and validated in international cohorts to expand the ability to predict patients at high risk for recurrence. Alpha-fetoprotein, radiological response to locoregional treatments, and other more recently proposed markers have been principally explored. Moreover, more complex statistical approaches (i.e., deep learning) have been advocated to explore the nonlinear intercorrelations between the investigated features.

SUMMARY

The addition of biological aspects to morphology has improved the ability to discriminate among high- and low-risk patients for recurrence. New prognostic algorithms based on the more sophisticated artificial intelligence approach are further improving the capability to select LT candidates with HCC.

Validation of New York/California Score in the Preoperative Period of Liver Transplant for Hepatocellular Carcinoma at University of Campinas's Hospital

Liver transplant is the main treatment for hepatocellular carcinoma and there is currently an important demand from patients waiting in transplant queues. Thus, it is extremely important to improve the criteria for selecting patients who will undergo transplant to mitigate graft loss and reduce cases of recurrence. Thus, it becomes necessary to use models, such as the New York/California (NYCA), that include alpha fetoprotein as a marker of recurrence and prognosis. The aim of this study was to assess whether the NYCA score correlated with the presence of tumor recurrence after transplant in patients undergoing orthotopic liver transplant at the Clinics Hospital of the University of Campinas. We had 214 patients undergoing liver transplant who met the inclusion Milan criteria. The age of the patients ranged from 34 to 77 years, with a median age of 61 years. The mean waiting time on the transplant list was 6.12 months. After calculating the NYCA score, it was possible to stratify 13 patients (6.1%) as high risk, 64 patients (29.9%) as medium risk, and 137 patients (64%) as low risk. Patients with recurrence had higher scores with a mean of 4 points in relapse and 2 points in the absence of relapse (P = .0011). Patients with recurrence had statistically higher high- and medium-risk scores (P = .0010). Therefore, the NYCA score was higher in patients with recurrence. Therefore, in this study, our findings suggest the possibility of using the NYCA score as an aid to detect patients with a higher risk of tumor recurrence.

[Hepatocellular carcinoma]

The therapeutic spectrum of hepatocellular carcinoma (HCC) in cirrhosis has expanded over the last decade and consists of surgical, interventional and systemic approaches. The tumor stage and liver function are important for the therapeutic strategy. Curation can be achieved by liver resection or transplantation. Access to transplantation is limited by organ shortage and waiting time. Locoregional therapies can be used as a bridge to transplant or for down-sizing in a neoadjuvant setting as well as palliative therapy. Advanced stages might benefit from systemic or immunotherapy. Modern multimodal therapy planning, timing and reevaluation are part of the tasks of tumor boards specialised in the liver, including the option of liver transplantation. Therapies can be used alone or in combination and according to the experience of the center. A curative strategy should always be pursued at initial presentation.

Different Models to Predict the Risk of Recurrent Hepatocellular Carcinoma in the Setting of Liver Transplantation

Simple Summary

Liver transplantation is considered the first-choice curative therapy for hepatocellular carcinoma in the early phase of the disease, when surgical resection is not possible. Even when implementing restrictive criteria to select patients for liver transplantation, there is a risk of recurrence in the transplanted liver, influencing the long-term outcome and prognosis. As it is challenging to predict the individual risk of recurrence, there is a need for validated and predictive scoring systems to use to stratify patients before and/or after liver transplantation. Most of the proposed scorings include biological markers for tumour behavior, in addition to the number and size of tumoral nodules. In this review, we discuss different published models to assess the risk of recurrent hepatocellular carcinoma after transplantation. Our aim is to refine clinical decisions about prioritization and listing for liver transplantation, to better inform patients and provide an appropriate surveillance strategy to influence their prognosis.

Abstract

Liver transplantation is the preferred therapeutic option for non-resectable hepatocellular carcinoma in early-stage disease. Taking into account the limited number of donor organs, liver transplantation is restricted to candidates with long-term outcomes comparable to benign indications on the waiting list. Introducing the morphometric Milan criteria as the gold standard for transplant eligibility reduced the recurrence rate. Even with strict patient selection, there is a risk of recurrence of between 8 and 20% in the transplanted liver, and this is of even greater importance when using more expanded criteria and downstaging protocols. Currently, it remains challenging to predict the risk of recurrence and the related prognosis for individual patients. In this review, the recurrence-risk-assessment scores proposed in the literature are discussed. Currently there is no consensus on the optimal model or the implications of risk stratification in clinical practice. The most recent scorings include additional biological markers for tumour behavior, such as alfa-foetoprotein, and the response to locoregional therapies, in addition to the number and diameter of tumoral nodules. The refinement of the prediction of recurrence is important to better inform patients, guide decisions about prioritization and listing and implement individualized surveillance strategies. In the future, this might also provide indications for tailored immunosuppressive therapy or inclusion in trials for adjuvant treatment.

Using quantitative immunohistochemistry in patients at high risk for hepatocellular cancer

Hepatocellular carcinoma (HCC) is the primary form of liver cancer and a major cause of cancer death worldwide. Early detection is key to effective treatment. Yet, early diagnosis is challenging, especially in patients with cirrhosis, who are at high risk of developing HCC. Dysfunction or loss of function of the transforming growth factor β (TGF-β) pathway is associated with HCC. Here, using quantitative immunohistochemistry analysis of samples from a multi-institutional repository, we evaluated if differences in TGF-β receptor abundance were present in tissue from patients with only cirrhosis compared with those with HCC in the context of cirrhosis. We determined that TGFBR2, not TGFBR1, was significantly reduced in HCC tissue compared with cirrhotic tissue. We developed an artificial intelligence (AI)-based process that correctly identified cirrhotic and HCC tissue and confirmed the significant reduction in TGFBR2 in HCC tissue compared with cirrhotic tissue. Thus, we propose that a reduction in TGFBR2 abundance represents a useful biomarker for detecting HCC in the context of cirrhosis and that incorporating this biomarker into an AI-based automated imaging pipeline could reduce variability in diagnosing HCC from biopsy tissue.

Prognostic impact of surgical margins for hepatocellular carcinoma according to preoperative alpha-fetoprotein level

BACKGROUND

HCC are known to have satellite nodules and microvascular invasions requiring sufficient margins. An alpha-fetoprotein (AFP) level >100 ng/mL is associated with worse pathological features in HCC. In practice, large resection margins, particularly >1 cm, are infrequently retrieved on the specimens.

METHODS

397 patients from 5 centres were included from 2012 to 2017. The primary endpoint was time-to-recurrence in relation to AFP level (> or <100 ng/ml) as well as surgical margins (> or <1 cm). The secondary endpoint was overall survival (OS).

RESULTS

The median follow-up was 25 months. In Low AFP group, median time to recurrence (TTR) for patients with margins <1 cm was 36 months and for patients with margins ≥1 cm was 34 months (p = 0.756), and overall survival (OS) was not significantly different according to margins (p = 0.079). In High-AFP group, patients with margins <1 cm had a higher recurrence rate than patients with margins ≥1 cm (p = 0.016): median TTR for patients with margins <1 cm was 8 months whereas it was not reached for patients with margins ≥1 cm. Patients with margins <1 cm had a significantly worse OS compared to the patients with margins ≥1 cm (p = 0.043).

CONCLUSION

Preoperative AFP level may help determine margins to effectively treat high AFP tumours. For low-AFP tumours, margins didn't have an impact on TTR or OS.

Non-transplantable Recurrence After Resection for Transplantable Hepatocellular Carcinoma: Implication for Upfront Treatment Choice

OBJECTIVES

To identify the preoperative risk factors for prediction of non-transplantable recurrence (NTR) after tumor resection for early-stage hepatocellular carcinoma (HCC) to assist in patient selection relative to upfront liver resection (LR) versus liver transplantation (LT).

METHODS

Patients who underwent curative resection for transplantable HCC and chronic liver disease were identified from an international multi-institutional database. NTR was defined as recurrence beyond the Milan or UCSF criteria, and the preoperative risk factors of NTR were investigated.

RESULTS

Among 293 patients with transplantable HCC within Milan criteria and 320 within UCSF criteria, 113 (38.6%) and 131 (40.9%) patients developed tumor recurrence, respectively. Among patients who recurred, NTR was present in 32 (28.3%) patients within Milan and 35 (26.7%) within UCSF criteria. When either Milan or UCSF criteria was adopted, three preoperative risk factors including liver cirrhosis, tumor size > 3 cm, and multiple lesions were consistently identified as risk factors associated with NTR after curative resection. By summing up the three factors, a scoring model was established and the incidence of NTR among patients with 0, 1 or ≥ 2 risk factors incrementally increased from 4.5%, 13.3% to 20.5% when Milan criteria was used, and from 4.5%, 12.4% to 33.9% when UCSF criteria was adopted. The model demonstrated very good discriminatory power on internal validation (n = 5,000) (c-index 0.689 for Milan criteria, and 0.715 for UCSF criteria).

CONCLUSIONS

Whereas surgical resection may be optimal first-line treatment for patients with no or one risk factor, patients with ≥ 2 risk factors should be considered for upfront liver transplantation.

Progression of AFP SCORE is a Preoperative Predictive Factor of Microvascular Invasion in Selected Patients Meeting Liver Transplantation Criteria for Hepatocellular Carcinoma

Microvascular invasion (MVI) is one of the main prognostic factors of hepatocellular carcinoma (HCC) after liver transplantation (LT), but its occurrence is unpredictable before surgery. The alpha fetoprotein (AFP) model (composite score including size, number, AFP), currently used in France, defines the selection criteria for LT. This study’s aim was to evaluate the preoperative predictive value of AFP SCORE progression on MVI and overall survival during the waiting period for LT. Data regarding LT recipients for HCC from 2007 to 2015 were retrospectively collected from a single institutional database. Among 159 collected cases, 34 patients progressed according to AFP SCORE from diagnosis until LT. MVI was shown to be an independent histopathological prognostic factor according to Cox regression and competing risk analysis in our cohort. AFP SCORE progression was the only preoperative predictive factor of MVI (OR = 10.79 [2.35–49.4]; p 0.002). The 5-year overall survival in the progression and no progression groups was 63.9% vs. 86.3%, respectively (p = 0.001). Cumulative incidence of HCC recurrence was significantly different between the progression and no progression groups (Sub-HR = 4.89 [CI 2–11.98]). In selected patients, the progression of AFP SCORE during the waiting period can be a useful preoperative tool to predict MVI.

The Toronto Postliver Transplantation Hepatocellular Carcinoma Recurrence Calculator: A Machine Learning Approach

Liver transplantation (LT) listing criteria for hepatocellular carcinoma (HCC) remain controversial. To optimize the utility of limited donor organs, this study aims to leverage machine learning to develop an accurate posttransplantation HCC recurrence prediction calculator. Patients with HCC listed for LT from 2000 to 2016 were identified, with 739 patients who underwent LT used for modeling. Data included serial imaging, alpha-fetoprotein (AFP), locoregional therapies, treatment response, and posttransplantation outcomes. We compared the CoxNet (regularized Cox regression), survival random forest, survival support vector machine, and DeepSurv machine learning algorithms via the mean cross-validated concordance index. We validated the selected CoxNet model by comparing it with other currently available recurrence risk algorithms on a held-out test set (AFP, Model of Recurrence After Liver Transplant [MORAL], and Hazard Associated with liver Transplantation for Hepatocellular Carcinoma [HALT-HCC score]). The developed CoxNet-based recurrence prediction model showed a satisfying overall concordance score of 0.75 (95% confidence interval [CI], 0.64-0.84). In comparison, the recalibrated risk algorithms' concordance scores were as follows: AFP score 0.64 (outperformed by the CoxNet model, 1-sided 95% CI, >0.01; P = 0.04) and MORAL score 0.64 (outperformed by the CoxNet model 1-sided 95% CI, >0.02; P = 0.03). The recalibrated HALT-HCC score performed well with a concordance of 0.72 (95% CI, 0.63-0.81) and was not significantly outperformed (1-sided 95% CI, ≥0.05; P = 0.29). Developing a comprehensive posttransplantation HCC recurrence risk calculator using machine learning is feasible and can yield higher accuracy than other available risk scores. Further research is needed to confirm the utility of machine learning in this setting.

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients

Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance of HCC. This study aimed to propose a novel CSCs-related cluster of HCC to predict patients' response to immunotherapy. Based on RNA-seq datasets from The Cancer Genome Atlas (TCGA) and Progenitor Cell Biology Consortium (PCBC), one-class logistic regression (OCLR) algorithm was applied to compute the stemness index (mRNAsi) of HCC patients. Unsupervised consensus clustering was performed to categorize HCC patients into two stemness subtypes which further proved to be a predictor of tumor immune microenvironment (TIME) status, immunogenomic expressions and sensitivity to neoadjuvant therapies. Finally, four machine learning algorithms (LASSO, RF, SVM-RFE and XGboost) were applied to distinguish different stemness subtypes. Thus, a five-hub-gene based classifier was constructed in TCGA and ICGC HCC datasets to predict patients' stemness subtype in a more convenient and applicable way, and this novel stemness-based classification system could facilitate the prognostic prediction and guide clinical strategies of immunotherapy and targeted therapy in HCC.

Laparoscopic liver resection for hepatocellular carcinoma complicated with significant portal hypertension: A propensity score-matched survival analysis

BACKGROUND

Significant portal hypertension (SPH) is a relative contraindication for patients with resectable hepatocellular carcinoma (HCC). However, increasing evidence indicates that liver resection is feasible for HCC patients with SPH.

METHODS

HCC patients with cirrhosis who underwent laparoscopic liver resection (LLR) in two centers from January 2013 to April 2018 were included. Surgical and survival outcomes were analyzed to explore potential prognostic factors. Propensity score matching (PSM) analysis was performed to minimize bias.

RESULTS

A total of 165 patients were divided into two groups based on the presence (SPH, n = 76) or absence (non-SPH, n = 89) of SPH. Patients in the SPH group had longer operative time, more blood loss, and more advanced TNM stage than patients in the non-SPH group (P < 0.05). However, there were no significant differences in the postoperative 90-day mortality rate (n = 0), overall postoperative complications (47.4% vs. 41.6%, P = 0.455), Clavien-Dindo classification (P = 0.347), conversion to open surgery (9.2% vs. 6.7%, P = 0.557), or length of hospitalization (16 vs. 15 days, P = 0.203) between SPH and non-SPH groups before PSM. Similar results were obtained after PSM. The 1-, 3-, and 5-year overall survival (OS) and recurrence-free survival rates in the SPH group were not significantly different from those in the non-SPH group both before and after PSM (log-rank P > 0.05).After PSM, alpha-fetoprotein (AFP) ≥ 400 μg/L [hazard ratio (HR) = 4.71, 95% confidence interval (CI): 2.69-8.25], ascites (HR = 2.18, 95% CI: 1.30-3.66), American Society of Anesthesiologists (ASA) classification (III vs. II) (HR = 2.13, 95% CI: 1.11-4.07) and tumor diameter > 5 cm (HR = 3.91, 95% CI: 2.02-7.56) independently predicted worse OS.

CONCLUSIONS

LLR for patients with HCC complicated with SPH appears feasible at the price of increasing operative time and blood loss. AFP, ascites, ASA classification and tumor diameter may predict the prognosis of HCC complicated with SPH after LLR.