Prediction of postoperative early recurrence and response to adjuvant transcatheter arterial chemoembolization in hepatocellular carcinoma with microvascular invasion after hepatectomy: a multicenter study

Introduction

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Although hepatectomy is currently recognized as the most effective treatment for HCC, the 5-year postoperative recurrence occurs in up to 80% of patients resulting in an unsatisfactory outcome (1,2). Exploring liver cancer recurrence has long been a focus of medical research. Previous studies have shown that microvascular invasion (MVI) is an independent risk factor for both recurrence and poor prognosis in HCC (3-5). MVI is a key histopathological feature of the invasive behavior of patients with HCC, accounting for approximately 50% of cases (6,7). Recent studies have found that MVI is a major factor in the early recurrence (ER) of HCC after surgery (7-9). Patients with HCC and ER always have worse surgical outcomes. Thus, identifying risk factors of ER among patients with HCC and MVI is of great importance.

Although numerous previous studies have unveiled the association of recurrence in patients with HCC and MVI with aggressive pathological features of tumors and underlying diseases, such as large tumor size, diabetes mellitus, and preoperative hypercoagulability status (10-12), few studies have addressed the risk factors of ER in patients with HCC and MVI after hepatectomy. Current prediction models separately discuss HCC recurrence and MVI occurrence (13,14), with less attention paid to the prediction of postoperative ER in patients with HCC and MVI.

Since patients with HCC and MVI are susceptible to ER, adjuvant therapy after surgery is pivotal. Our previous study indicated that transcatheter arterial chemoembolization (TACE) can be beneficial for such patients (15). However, this concept remains controversial, as some studies have shown that not all patients with HCC and MVI can benefit from TACE (9,16,17). Therefore, patients suitable for postoperative adjuvant TACE therapy need to be screened to improve treatment efficacy.

In this study, we developed and validated the DCDAM score for predicting ER in patients with HCC and MVI. This model allows the precise stratification of recurrence risk among patients and helps identify subgroups that benefit from TACE. A more accurate basis for clinical decision-making can reduce ER rates and improve the long-term prognosis of patients with HCC and MVI after surgery. We present this article in accordance with the TRIPOD reporting checklist (available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-557/rc).

Methods

Study population

This is a retrospective study conducted on consecutive patients with HCC and MVI who underwent hepatectomy in the Chinese People’s Liberation Army General Hospital (PLAGH) and 15 hospitals of the Chinese National Research Cooperative Group for Diagnosis and Treatment of Hepatocellular Carcinoma with Tumor Thrombus between March 2010 and May 2022. In the PLAGH, patients were randomized 2:1 to the training cohort and the internal validation cohort. The remaining patients were assigned to the external validation cohort. This study was conducted following the Declaration of Helsinki and its subsequent amendments. This study was approved by the institutional ethics committees of PLAGH and the Chinese National Research Cooperative Group (S2023-528-01). As patient identities were anonymized, the requirement for informed consent was waived by the Ethics Committee.

Inclusion and exclusion criteria

Inclusion criteria were as follows: (I) histopathological diagnosis of HCC and MVI; (II) curative R0 liver resection; (III) no preoperative neoadjuvant therapy; and (IV) Child-Pugh class A or selected B liver function (score ≤7). Exclusion criteria were as follows: (I) incomplete clinical and pathological information; (II) death due to complications or causes other than HCC; (III) combination of macrovascular invasion, other malignant tumors, or distant metastases; and (IV) loss to follow-up without an outcome event of recurrence or death within 1 year. Additionally, the classification of MVI follows the pathological diagnosis based on the seven-point sampling protocol as previously reported (18). MVI was categorized into two grades: M1 and M2. M1 is defined as amount of MVI ≤5 and distance ≤1 cm away from the adjacent cancer tissues, while M2 is characterized by amount >5 or distance >1 cm away from the adjacent cancer tissues. If the pathological diagnosis was indefinite, the decision was discussed by two or more senior pathologists.

Follow-up

After surgery, patients were followed once every 3 months in the first 2 years and every 6 months thereafter until death or loss of follow-up. Postoperative surveillance included history taking, physical examination, serum α-fetoprotein (AFP) levels, contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI) of the abdomen, and chest radiography. Additionally, we recorded whether the patients underwent postoperative adjuvant TACE therapy. TACE was performed 1–2 months after curative resection of HCC by using lipiodol-based regimens, including the administration of an anticancer-in-oil emulsion followed by embolic agents. Tumor relapse was diagnosed based on CT/MRI and elevated serum levels of AFP, or it was confirmed by biopsy according to the available practice guidelines for HCC management at that time. Recurrence within 1 year after surgery was defined as ER (7,9). The primary endpoint was defined as recurrence-free survival (RFS), and the secondary endpoint was defined as overall survival (OS).

Data on demographics, clinical details, biological markers, radiological findings, and treatment outcomes, were collected prospectively and analyzed retrospectively. HCC and liver function were staged according to the albumin-bilirubin (ALBI) grade (19), the Cancer of the Liver Italian Program (CLIP) (20), the Chinese University Prognostic Index (CUPI) (21), the TOKYO score (22), and the Model for End-Stage Liver Disease (MELD) (23).

Statistical analysis

Clinical and pathological characteristics were summarized using frequencies and percentages for categorical variables and medians and ranges for continuous variables. The Chi-squared test or Fisher’s exact test was used to compare categorical variables, while continuous variables or variables with an abnormal distribution were compared using the unpaired t-test, Mann-Whitney U test, or Kruskal-Wallis test. Survival curves were drawn and compared using the Kaplan-Meier method and log-rank test. Univariate and multivariate logistic regression analyses were used to determine independent risk factors associated with ER among patients in the training cohort. A nomogram was developed based on the proportional conversion of each regression coefficient from multivariate logistic regression to a 0-to-100-point scale. Decision curve analysis (DCA), calibration curves, and time-dependent receiver operating characteristic (time-ROC) curves were used to measure the performances of different models across the three cohorts. The optimal cut-off value of the nomogram score was calculated using the maximum Youden index method. A two-tailed P value <0.05 was considered statistically significant. Data were analyzed using SPSS (version 26) and R program (version 3.6.3). The following packages of R software were used for analysis: ‘survival’, ‘survminer’, ‘CsChange’, ‘stdca’, ‘nomogramFormula’, ‘Time-ROC’, ‘rms’, and ‘DynNom’.

Results

Participants

In total, 1,397 patients with HCC and MVI underwent radical hepatectomy, and 1,191 patients met the inclusion criteria (Figure S1). A total of 1,000 patients (84.0%) were hepatitis B virus (HBV)-related HCC, but only 323 patients (27.1%) were on preoperative anti-viral therapy. In the training cohort of 503 patients, the ER rate was 43.1%, while in the internal and external validation cohorts of 252 and 436 patients, the ER rates were 45.6% and 43.4%, respectively. During follow-up, the median RFS of patients was 18.4, 15.0, and 18.3 months in the training, internal validation, and external validation cohorts, respectively (P=0.53). The median OS in the three cohorts were 32.0, 33.5, and 36.2 months, respectively (P=0.03). In the training, internal validation, and external validation cohorts, 186 (37.0%), 92 (36.5%), and 165 (37.8%) patients received adjuvant TACE after surgery, respectively (P=0.93). The clinicopathological characteristics and surgical outcomes of patients with HCC and MVI in the training, internal validation, and external validation cohorts are shown in Table 1. The details between the ER and non-ER groups in the training cohort are shown in Table S1.

Identification of independent prognostic factors in the training cohort

In the training cohort, 25 clinical basic indicators were included in univariate regression analysis for ER, which showed that ER was associated with HBV, AFP, prothrombin time, diameter, cirrhosis, capsule, differentiation, intraoperative blood loss, and MVI grade. Multivariate logistic regression analysis showed that AFP, diameter, cirrhosis, differentiation, and MVI grade were independent risk factors for ER (Table 2).

Development of a nomogram predicting postoperative ER

A nomogram, referred to as the DCDAM score, was developed to predict ER for patients with HCC and MVI after hepatectomy based on five significant factors identified by the logistic regression model (Figure 1A). The DCDAM score assesses the probability of ER by summing the scores of the point scales for variables. The highest score (100 points) was assigned to tumor diameter. The scores for other variables were as follows: cirrhosis (69 points), differentiation (62 points), AFP level (47 points), and MVI grade (61 points). An online version of DCDAM score can be accessed at https://wiley.shinyapps.io/ER-predict/ to facilitate clinical application.

Figure 1 Nomogram for predicting ER of patients with HCC and MVI after hepatectomy and decision curve analyses in the three cohorts. (A) DCDAM score, the optimal cutoff value of nomogram score was 169. Low-risk group (nomogram score ≤169) and high-risk group (nomogram score >169). (B-D) Decision curve analyses showed the net benefits of DCDAM score and other models in the training, internal validation and external validation cohorts, respectively. AFP, α-fetoprotein; ALBI, albumin-bilirubin; CLIP, Cancer of the Liver Italian Program; CUPI, Chinese University Prognostic Index; ER, early recurrence; HCC, hepatocellular carcinoma; MELD, Model for End-Stage Liver Disease; MVI, microvascular invasion.

Evaluation and validation of the DCDAM score

DCA was used to assess the DCDAM score against other staging systems (ALBI grade, CLIP, CUPI, TOKYO, and MELD) in the training, internal validation, and external validation cohorts (Figure 1B-1D). DCA demonstrated the superior net benefit of the DCDAM score for risk stratification compared to other international staging systems. Calibration curves confirmed that the DCDAM score accurately predicted ER probability in three cohorts (P=0.06, P=0.19, P=0.31, respectively; Figure S2A-S2C). The area under the ROC curve (AUC) values for ER prediction using the DCDAM score were 0.770 [95% confidence interval (CI): 0.728–0.812], 0.763 (95% CI: 0.704–0.822) and 0.762 (95% CI: 0.717–0.806), respectively, significantly outperforming other systems (Figure S2D-S2F). Additionally, the area under the time-ROC curves (time-AUCs) of the DCDAM score for predicting OS within 5 years in the three cohorts were 0.701–0.758, 0.776–0.801, and 0.726–0.750, respectively, which were significantly higher than those of other systems (all P<0.001; Figure S2G-S2I).

Comparison of the long-term survival of patients in different risk groups

The discriminatory ability was further evaluated by dividing the predicted probabilities of ER into two risk groups based on DCDAM scores (a low-risk group with DCDAM score ≤169 and a high-risk group with DCDAM score >169). We found that the high-risk group had a higher ER incidence than the low-risk group in the three cohorts (all P<0.001; Table S2).

The Kaplan-Meier survival curves showed that the DACAM risk subgroups demonstrated outstanding discrimination ability for cumulative recurrence rates and OS in the training, internal validation, and external validation cohorts. The cumulative recurrence rates of patients in the high-risk group were significantly higher than those in the low-risk group (all P<0.001; Figure 2A-2C). The median OS of patients in the high-risk group was significantly shorter than that in the low-risk group (22.0 vs. 38.3, 17.5 vs. 41.7, and 23.6 vs. 45.2 months in the three cohorts, respectively, all P<0.001, Figure 2D-2F).

Figure 2 Kaplan-Meier plots of cumulative recurrence rate (A-C) and OS (D-F) for groups stratified by DCDAM score in the training, internal validation and external validation cohorts. OS, overall survival.

Survival analyses stratified by adjuvant TACE in different risk groups

Subgroup analyses revealed no significant difference between the high- and low-risk groups in terms of the proportion of patients receiving postoperative adjuvant TACE therapy (38.5% vs. 36.4%, P=0.47). Among the training, internal validation, and external validation cohorts, OS was not all significant in the TACE group compared to the non-TACE (P=0.004, 0.25, and 0.04, respectively; Figure S3). In all of the three cohorts, in the high-risk subgroup, patients receiving postoperative adjuvant TACE therapy had significantly longer OS compared to those not receiving TACE (37.8 vs. 14.8, 20.6 vs. 10.9, and 39.5 vs. 18.1 months, respectively, all P<0.001; Figure 3A-3C). Conversely, in the low-risk subgroup, there was no significant difference in OS between patients with and without TACE (37.0 vs. 38.7 months, P=0.39; 39.6 vs. 41.7 months, P=0.62; and 41.5 vs. 45.3 months, P=0.55, respectively, Figure 3D-3F).

Figure 3 Kaplan-Meier plots of OS for high-risk subgroup stratified by TACE in the training, internal validation and external validation cohorts (A-C) and low-risk subgroup in these cohorts (D-F). OS, overall survival; TACE, transcatheter arterial chemoembolization.

Discussion

The presence of MVI is associated with worse surgical outcomes and tumor recurrence among patients with HCC (3,4,24). Patients with HCC and MVI more easily develop ER after hepatectomy, which always worsens prognosis (7,8). However, few studies have focused on the prediction of ER after hepatectomy for patients with HCC and MVI. In the present study, the DCDAM score was developed and validated as a nomogram using data from multiple liver centers to predict ER in patients with HCC and MVI after hepatectomy. Based on DCDAM scores, patients were categorized into a low-risk group (DCDAM score ≤169) and a high-risk group (DCDAM score >169). Subgroup analyses revealed that the high-risk group had a higher proportion of ER and a worse prognosis compared to the low-risk group. Importantly, postoperative TACE showed a survival benefit only in the high-risk group.

ER has long been a research focus. It is usually defined as recurrence within less than 2 years after surgery for HCC (3,25,26). In this study, the cut-off for ER was set at 1 year, which was consistent with previous studies because patients with HCC and MVI are more likely to recurrence within 1 year and patients with relapse have a worse prognosis (7-9). MVI plays a critical role in the ER of patients with HCC, but the risk factors of ER in patients with HCC and MVI remain unclear. Our study indicated that some malignant features of the primary tumor, such as tumor diameter, AFP level, tumor differentiation, and MVI grade, were independent risk factors for ER in patients with HCC and MVI. These findings are consistent with those reported by some of the previous studies (6,27,28). The degree of MVI indicates the aggressiveness of the tumor, and the type of invaded vessels determines the nature of tumor cell spread (29,30). However, cirrhosis was also an independent risk factor for ER in our study, it was often considered to be associated with late recurrence in HCC (25). This may be related to antiviral therapy or not in cirrhosis since Li et al. found that preoperative anti-HBV therapy can reduce the risk of MVI and early tumor recurrence (31). Although most patients with cirrhosis in China has a background of HBV infection, preoperative antiviral therapy is usually lacking and irregular, which may necessitate more studies.

Among various available prediction tools, the nomogram has a high degree of accuracy, possesses excellent discrimination ability, and is easy to use. Some nomograms predicting ER have primarily focused on HCC and HCC with macrovascular invasion (32,33), with little attention to ER in patients with HCC and MVI (7). In our study, the DCDAM score not only predicts ER among patients with HCC and MVI but also plays a crucial role in determining prognosis and adjuvant treatment. All results were validated internally and externally, which increases the credibility of this model. In addition, compared to the traditional model, the DCDAM score showed superior net benefit and more accurate prediction of ER and prognosis in patients with HCC and MVI after surgery. These findings can help modern medicine in improving individualized treatment and clinical decision-making.

In addition, the accuracy of the DCDAM score in predicting ER was further validated by the fact that the ER rate was significantly higher in the high-risk group than in the low-risk group. Higher cumulative recurrence rates and worse OS were also found in the high-risk group compared to the low-risk group. This is consistent with the findings of many previous studies reporting that different types of tumors with ER have a worse prognosis (27,34,35). Moreover, the median OS for the low-risk group in our study was 38.3 to 45.2 months, which was similar to the previously reported prognosis among patients with HCC after surgery (12,36). Patients in the high-risk group should be followed more closely to monitor for ER. Several studies have reported a long-term prognosis associated with regular postoperative surveillance, as this allows for timely intervention for recurrence (25,31).

The DCDAM score can also provide a useful reference for the postoperative treatment of resectable HCC with MVI. The optimal treatment strategy for patients with HCC and MVI after radical resection remains controversial (37,38). Postoperative adjuvant TACE has been reported to play a significant role in preventing recurrence and improving prognosis in HCC, even in cases with MVI (15,39,40). However, its effectiveness remains a subject of debate. A randomized clinical trial demonstrated that the survival of patients with postoperative recurrence of HCC with MVI was worse with TACE alone compared to the combination regimen (17). In addition, Liu et al. found that postoperative adjuvant TACE can be beneficial for treating the recurrence of patients with HCC and MVI within 13 months (9). Our study also found that only the high-risk group with HCC and MVI benefited from adjuvant TACE. The new prediction model appears to be useful in decision-making and tailored TACE interventions for patients with HCC and MVI. This approach benefits both individuals and society. On one hand, it improves treatment outcomes and extends patients’ prognosis. On the other hand, it optimizes the allocation of healthcare resources, reduces ineffective treatments, and lowers healthcare costs.

There are several limitations to this study. First, this is a retrospective study, with inherent biases. Second, the use of gelatin sponge and related materials may vary among patients, although TACE was performed 1–2 months post-curative resection of HCC using lipiodol-based regimens. Another key limitation is the absence of a standardized technique for intra-arterial therapy. Additionally, the impact of different postoperative adjuvant treatment methods like pharmacotherapy on the prognosis of these patients requires further investigation. Furthermore, this study was from China. Most patients with HCC had a background of HBV infection, unlike patients from the United States and Europe, where HCV infection, alcoholic liver disease, and non-alcoholic fatty liver disease are the main etiological factors. Our findings need to be validated in other regions. Moreover, the MVI grade in the DCDAM score was extremely affected by subjective sampling and observation; thus, combined imaging and omics studies are needed to screen patients with ER.

Conclusions

In conclusion, this multicenter study developed and validated a nomogram that can predict ER after hepatectomy in patients with HCC and MVI. The nomogram model had high degrees of stability and accuracy, which may provide references for individualized treatment strategies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-557/rc

Data Sharing Statement: Available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-557/dss

Peer Review File: Available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-557/prf

Funding: This study was supported by the Capital Health Development Research Special Project (CFH 2024-4-5026, 2022-2-5021), the Beijing Natural Science Foundation (L242144), the National Natural Science Foundation of China (32201232), the Beijing Nova Program (20230484372), the Young Elite Scientists Sponsorship Program by CAST (2023QNRC001), the Young Elite Scientists Sponsorship Program by BAST (BYESS2024001), and the National Key Research and Development Program of China (2022YFC2407402).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-557/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted following the Declaration of Helsinki and its subsequent amendments. This study was approved by the institutional ethics committees of PLAGH and the Chinese National Research Cooperative Group (S2023-528-01). As patient identities were anonymized, the requirement for informed consent was waived by the Ethics Committee.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Vogel A, Meyer T, Sapisochin G, et al. Hepatocellular carcinoma. Lancet 2022;400:1345-62. [Crossref] [PubMed]
2. Brown ZJ, Tsilimigras DI, Ruff SM, et al. Management of Hepatocellular Carcinoma: A Review. JAMA Surg 2023;158:410-20. [Crossref] [PubMed]
3. Imamura H, Matsuyama Y, Tanaka E, et al. Risk factors contributing to early and late phase intrahepatic recurrence of hepatocellular carcinoma after hepatectomy. J Hepatol 2003;38:200-7. [Crossref] [PubMed]
4. Zhang X, Li J, Shen F, et al. Significance of presence of microvascular invasion in specimens obtained after surgical treatment of hepatocellular carcinoma. J Gastroenterol Hepatol 2018;33:347-54. [Crossref] [PubMed]
5. Xing H, Zhang WG, Cescon M, et al. Defining and predicting early recurrence after liver resection of hepatocellular carcinoma: a multi-institutional study. HPB (Oxford) 2020;22:677-89. [Crossref] [PubMed]
6. Fuster-Anglada C, Mauro E, Ferrer-Fàbrega J, et al. Histological predictors of aggressive recurrence of hepatocellular carcinoma after liver resection. J Hepatol 2024;81:995-1004. [Crossref] [PubMed]
7. Zhang K, Tao C, Siqin T, et al. Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion. J Transl Med 2021;19:293. [Crossref] [PubMed]
8. Chen ZH, Zhang XP, Feng JK, et al. Patterns, treatments, and prognosis of tumor recurrence after resection for hepatocellular carcinoma with microvascular invasion: a multicenter study from China. HPB (Oxford) 2022;24:1063-73. [Crossref] [PubMed]
9. Liu ZH, Chai ZT, Feng JK, et al. A reasonable identification of the early recurrence time based on microvascular invasion for hepatocellular carcinoma after R0 resection: A multicenter retrospective study. Cancer Med 2023;12:10294-302. [Crossref] [PubMed]
10. Yu Y, Wang XH, Hu WJ, et al. Patterns, Risk Factors, and Outcomes of Recurrence After Hepatectomy for Hepatocellular Carcinoma with and without Microvascular Invasion. J Hepatocell Carcinoma 2024;11:801-12. [Crossref] [PubMed]
11. Zhang XP, Chai ZT, Feng JK, et al. Association of type 2 diabetes mellitus with incidences of microvascular invasion and survival outcomes in hepatitis B virus-related hepatocellular carcinoma after liver resection: A multicenter study. Eur J Surg Oncol 2022;48:142-9. [Crossref] [PubMed]
12. Zhang XP, Zhou TF, Wang ZH, et al. Association of Preoperative Hypercoagulability with Poor Prognosis in Hepatocellular Carcinoma Patients with Microvascular Invasion After Liver Resection: A Multicenter Study. Ann Surg Oncol 2019;26:4117-25. [Crossref] [PubMed]
13. Lei Z, Li J, Wu D, et al. Nomogram for Preoperative Estimation of Microvascular Invasion Risk in Hepatitis B Virus-Related Hepatocellular Carcinoma Within the Milan Criteria. JAMA Surg 2016;151:356-63. [Crossref] [PubMed]
14. Wehrle CJ, Hong H, Kamath S, et al. Tumor Mutational Burden From Circulating Tumor DNA Predicts Recurrence of Hepatocellular Carcinoma After Resection: An Emerging Biomarker for Surveillance. Ann Surg 2024;280:504-13. [Crossref] [PubMed]
15. Chen ZH, Zhang XP, Zhou TF, et al. Adjuvant transarterial chemoembolization improves survival outcomes in hepatocellular carcinoma with microvascular invasion: A systematic review and meta-analysis. Eur J Surg Oncol 2019;45:2188-96. [Crossref] [PubMed]
16. Liu S, Li H, Guo L, et al. Tumor Size Affects Efficacy of Adjuvant Transarterial Chemoembolization in Patients with Hepatocellular Carcinoma and Microvascular Invasion. Oncologist 2019;24:513-20. [Crossref] [PubMed]
17. Fan W, Zhu B, Chen S, et al. Survival in Patients With Recurrent Intermediate-Stage Hepatocellular Carcinoma: Sorafenib Plus TACE vs TACE Alone Randomized Clinical Trial. JAMA Oncol 2024;10:1047-54. [Crossref] [PubMed]
18. Sheng X, Ji Y, Ren GP, et al. A standardized pathological proposal for evaluating microvascular invasion of hepatocellular carcinoma: a multicenter study by LCPGC. Hepatol Int 2020;14:1034-47. [Crossref] [PubMed]
19. Johnson PJ, Berhane S, Kagebayashi C, et al. Assessment of liver function in patients with hepatocellular carcinoma: a new evidence-based approach-the ALBI grade. J Clin Oncol 2015;33:550-8. [Crossref] [PubMed]
20. Kudo M, Chung H, Osaki Y. Prognostic staging system for hepatocellular carcinoma (CLIP score): its value and limitations, and a proposal for a new staging system, the Japan Integrated Staging Score (JIS score). J Gastroenterol 2003;38:207-15. [Crossref] [PubMed]
21. Leung TW, Tang AM, Zee B, et al. Construction of the Chinese University Prognostic Index for hepatocellular carcinoma and comparison with the TNM staging system, the Okuda staging system, and the Cancer of the Liver Italian Program staging system: a study based on 926 patients. Cancer 2002;94:1760-9. [Crossref] [PubMed]
22. Tateishi R, Yoshida H, Shiina S, et al. Proposal of a new prognostic model for hepatocellular carcinoma: an analysis of 403 patients. Gut 2005;54:419-25. [Crossref] [PubMed]
23. Botta F, Giannini E, Romagnoli P, et al. MELD scoring system is useful for predicting prognosis in patients with liver cirrhosis and is correlated with residual liver function: a European study. Gut 2003;52:134-9. [Crossref] [PubMed]
24. Zhang XP, Wang K, Wei XB, et al. An Eastern Hepatobiliary Surgery Hospital Microvascular Invasion Scoring System in Predicting Prognosis of Patients with Hepatocellular Carcinoma and Microvascular Invasion After R0 Liver Resection: A Large-Scale, Multicenter Study. Oncologist 2019;24:e1476-88. [Crossref] [PubMed]
25. Xu XF, Xing H, Han J, et al. Risk Factors, Patterns, and Outcomes of Late Recurrence After Liver Resection for Hepatocellular Carcinoma: A Multicenter Study From China. JAMA Surg 2019;154:209-17. [Crossref] [PubMed]
26. Tabrizian P, Jibara G, Shrager B, et al. Recurrence of hepatocellular cancer after resection: patterns, treatments, and prognosis. Ann Surg 2015;261:947-55. [Crossref] [PubMed]
27. Portolani N, Coniglio A, Ghidoni S, et al. Early and late recurrence after liver resection for hepatocellular carcinoma: prognostic and therapeutic implications. Ann Surg 2006;243:229-35. [Crossref] [PubMed]
28. Cheng Z, Yang P, Qu S, et al. Risk factors and management for early and late intrahepatic recurrence of solitary hepatocellular carcinoma after curative resection. HPB (Oxford) 2015;17:422-7. [Crossref] [PubMed]
29. Yao LQ, Li C, Diao YK, et al. Grading severity of microscopic vascular invasion was independently associated with recurrence and survival following hepatectomy for solitary hepatocellular carcinoma. Hepatobiliary Surg Nutr 2024;13:16-28. [Crossref] [PubMed]
30. Xu XF, Diao YK, Zeng YY, et al. Association of severity in the grading of microvascular invasion with long-term oncological prognosis after liver resection for early-stage hepatocellular carcinoma: a multicenter retrospective cohort study from a hepatitis B virus-endemic area. Int J Surg 2023;109:841-9. [Crossref] [PubMed]
31. Li Z, Lei Z, Xia Y, et al. Association of Preoperative Antiviral Treatment With Incidences of Microvascular Invasion and Early Tumor Recurrence in Hepatitis B Virus-Related Hepatocellular Carcinoma. JAMA Surg 2018;153:e182721. [Crossref] [PubMed]
32. Liu X, Qiu Z, Ndhlovu E, et al. Establishing and Externally Validating a Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score-Based Nomogram for Predicting Early Recurrence in BCLC Stage 0/A Hepatocellular Carcinoma Patients After Radical Liver Resection: A Multi-Center Study. J Hepatocell Carcinoma 2024;11:1127-41. [Crossref] [PubMed]
33. Zhang XP, Chen ZH, Zhou TF, et al. A nomogram to predict early postoperative recurrence of hepatocellular carcinoma with portal vein tumour thrombus after R0 liver resection: A large-scale, multicenter study. Eur J Surg Oncol 2019;45:1644-51. [Crossref] [PubMed]
34. Zhang XP, Xu S, Gao YX, et al. Early and late recurrence patterns of pancreatic ductal adenocarcinoma after pancreaticoduodenectomy: a multicenter study. Int J Surg 2023;109:785-93. [Crossref] [PubMed]
35. Cho JY, Han HS, Choi Y, et al. Association of Remnant Liver Ischemia With Early Recurrence and Poor Survival After Liver Resection in Patients With Hepatocellular Carcinoma. JAMA Surg 2017;152:386-92. [Crossref] [PubMed]
36. Bednarsch J, Czigany Z, Heise D, et al. Prognostic evaluation of HCC patients undergoing surgical resection: an analysis of 8 different staging systems. Langenbecks Arch Surg 2021;406:75-86. [Crossref] [PubMed]
37. Li SH, Mei J, Cheng Y, et al. Postoperative Adjuvant Hepatic Arterial Infusion Chemotherapy With FOLFOX in Hepatocellular Carcinoma With Microvascular Invasion: A Multicenter, Phase III, Randomized Study. J Clin Oncol 2023;41:1898-908. [Crossref] [PubMed]
38. Wang K, Xiang YJ, Yu HM, et al. Adjuvant sintilimab in resected high-risk hepatocellular carcinoma: a randomized, controlled, phase 2 trial. Nat Med 2024;30:708-15. [Crossref] [PubMed]
39. Zhang XP, Liu YC, Chen ZH, et al. Postoperative Adjuvant Transarterial Chemoembolization Improves Outcomes of Hepatocellular Carcinoma Associated with Hepatic Vein Invasion: A Propensity Score Matching Analysis. Ann Surg Oncol 2019;26:1465-73. [Crossref] [PubMed]
40. Sun JJ, Wang K, Zhang CZ, et al. Postoperative Adjuvant Transcatheter Arterial Chemoembolization After R0 Hepatectomy Improves Outcomes of Patients Who have Hepatocellular Carcinoma with Microvascular Invasion. Ann Surg Oncol 2016;23:1344-51. [Crossref] [PubMed]