BPG is committed to discovery and dissemination of knowledge
Retrospective Study Open Access
Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastrointest Oncol. May 15, 2026; 18(5): 116764
Published online May 15, 2026. doi: 10.4251/wjgo.v18.i5.116764
Severe hepatic steatosis as a protective prognostic factor in combined hepatocellular-cholangiocarcinoma: A multicenter pathological study
Han Wang, Zhen-Ying Cao, Wen-Ming Cong, Hui Dong, Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
Han Wang, Miao-Xia He, Department of Pathology, Changhai Hospital, Naval Medical University, Shanghai 200433, China
Chun-Yan Xia, Department of Pathology, Changzheng Hospital, Naval Medical University, Shanghai 200003, China
Xia Sheng, Department of Pathology, Minhang Hospital, Fudan University, Shanghai 201199, China
Yun Zhao, Department of Pathology, Huadong Hospital, Fudan University, Shanghai 200040, China
Hong-Zhen Chen, Department of Pathology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 310015, Zhejiang Province, China
ORCID number: Hui Dong (0009-0003-0428-9593).
Co-first authors: Han Wang and Zhen-Ying Cao.
Co-corresponding authors: Miao-Xia He and Hui Dong.
Author contributions: Wang H and Cao ZY wrote the manuscript, were involved in the acquisition, analysis, and interpretation of data, and substantially participated in the writing of this paper, they contributed equally to this article, they are the co-first authors of this manuscript; Wang H, Cao ZY, Xia CY, Sheng X, Zhao Y, Chen HZ, Cong WM, He MX, and Dong H accessed and verified the study data; Cong WM, He MX, and Dong H participated in the conception and design of the study; He MX and Dong H jointly supervised the research project, provided critical guidance throughout study design and data interpretation, they contributed equally to this article, they are the co-corresponding authors of this manuscript; and all authors thoroughly reviewed and endorsed the final manuscript.
Supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project, No. 2023ZD0500100; Shanghai Leading Talent Program of Eastern Talent Plan, No. BJWS2024084; Municipal Hospital Clinical Technology Promotion and Management Optimization Project by Shanghai Shenkang Hospital Development Center, No. SHDC22023208; Shanghai Science and Technology Innovation Action Plan-Medical Innovation Research Project, No. 22Y11909100; Naval Medical University Basic Medical Research Project, No. 2023NQ095; and Take-off Project Talent Program of EHBH, No. TF2024XSJJ02.
Institutional review board statement: This study was approved by the Medical Ethics Committee of Eastern Hepatobiliary Surgery Hospital, approval No. EHBHKY2022-H010-P001.
Informed consent statement: The need for patient consent was waived due to the retrospective nature of the study.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Dataset available from the corresponding authors at huidongwh@126.com or hmm26@163.com. Consent was not obtained but the presented data are anonymized and risk of identification is low.
Corresponding author: Hui Dong, PhD, Associate Faculty, Associate Professor, Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, No. 225 Changhai Road, Yangpu District, Shanghai 200438, China. huidongwh@126.com
Received: November 20, 2025
Revised: December 18, 2025
Accepted: February 5, 2026
Published online: May 15, 2026
Processing time: 175 Days and 10.7 Hours

Abstract
BACKGROUND

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare and aggressive primary liver cancer characterized by the presence of both hepatocellular and cholangiocellular differentiation within the same tumor. Its diagnostic complexity and low incidence have resulted in a scarcity of well-established prognostic pathological parameters to guide clinical management. Given the rising global prevalence of metabolic dysfunction-associated steatotic liver disease and alcohol-related liver disease, and their close association with the occurrence of primary liver cancer, it is plausible that hepatic steatosis influences the prognosis of cHCC-CCA.

AIM

To investigate the specific clinicopathological role of background hepatic steatosis in patients with cHCC-CCA who underwent curative-intent liver resection.

METHODS

This multicenter study analyzed 310 patients with cHCC-CCA who underwent curative-intent hepatectomy between 2013 and 2017. Hepatic steatosis in liver tissue was graded pathologically: Grade 0-1 (< 33% hepatocytes) was defined as negligible hepatic steatosis (n = 283, 91.3%), and grade 2-3 (≥ 33% hepatocytes) as severe hepatic steatosis (n = 27, 8.7%). Primary endpoints were recurrence-free survival (RFS), overall survival, early (≤ 2 years) and late (> 2 years) RFS.

RESULTS

Patients with severe hepatic steatosis had a significantly prolonged RFS compared to those with negligible steatosis (P = 0.035), with 5-year RFS rates of 28.8% vs 15.7%. This benefit was primarily observed in early RFS (P = 0.024) and was more pronounced in non-cirrhotic patients. In contrast, no statistically significant difference was found in overall survival (P = 0.586) or late RFS (P = 0.931) between the two groups. Multivariate logistic regression analysis showed higher body mass index and lymphocyte count, and lower lactate dehydrogenase were independent predictors for the presence of severe steatosis. Furthermore, multivariate Cox regression analysis confirmed severe hepatic steatosis as an independent protective factor for RFS (hazard ratio = 0.614) and early RFS (hazard ratio = 0.577).

CONCLUSION

Severe hepatic steatosis is a protective factor associated with RFS and early RFS in patients with cHCC-CCA who underwent hepatectomy, which is especially significant in the absence of liver cirrhosis.

Key Words: Combined hepatocellular-cholangiocarcinoma; Mixed hepatocellular-cholangiocarcinoma; Hepatic steatosis; Hepatocellular steatosis; Liver steatosis; Fatty liver disease; Pathological assessment; Alcohol-related liver disease; Metabolic dysfunction-associated steatotic liver disease

Core Tip: This retrospective multicenter study investigated the prognostic influence of hepatic steatosis in patients with combined hepatocellular-cholangiocarcinoma (cHCC-CCA). Severe hepatic steatosis was associated with a favorable prognosis in cHCC-CCA patients. This protective effect was particularly significant in preventing early recurrence and was more pronounced among non-cirrhotic patients. We propose that the evaluation of hepatic steatosis be incorporated into the routine pathological diagnosis of cHCC-CCA to optimize postoperative management for this tumor entity.



INTRODUCTION

Primary liver cancer stands as one of the most prevalent cancers worldwide and a leading cause of cancer-related mortality[1]. Among all pathological subtypes of primary liver cancer, combined hepatocellular-cholangiocarcinoma (cHCC-CCA) remains poorly characterized in terms of standardized diagnostic and therapeutic paradigms due to its unique histological composition and relatively rare incidence[2]. According to the Surveillance, Epidemiology, and End Results database, its 5-year survival rate is only 17.1%[3], suggesting the critical need for pathologists to identify histopathological parameters with prognostic value to refine the management of cHCC-CCA.

In China, hepatitis B virus (HBV) infection has long been the predominant etiological factor driving primary liver carcinogenesis[4]. However, with societal advancements, alcohol abuse and metabolic syndrome-related fatty liver diseases are increasingly recognized as significant contributors to hepatocellular carcinoma (HCC)[5]. Recent projections indicate that the proportion of alcohol-associated HCC patients is expected to rise from 18.8% in 2022 to 21.1% by 2050, while metabolic dysfunction-associated steatohepatitis-related HCC cases are projected to increase from 8.0% to 10.8% during the same period[6]. Consequently, rigorous pathological evaluation of hepatic steatosis may provide more granular insights for postoperative management in cHCC-CCA patients[7].

Although hepatic steatosis has been implicated in hepatocarcinogenesis, its prognostic significance in cHCC-CCA patients after curative resection remains unclear. Given the potential reversibility of hepatic steatosis, elucidating its impact on survival outcomes is clinically actionable. To address this gap, we conducted a multicenter pathological study to comprehensively compare the clinical manifestations and prognosis of cHCC-CCA patients undergoing curative-intent hepatectomy, stratified by the severity of hepatic steatosis.

MATERIALS AND METHODS
Patients

This study retrospectively collected and analyzed the clinicopathological data of consecutive patients with primary cHCC-CCA who underwent liver resection with curative intent at six medical centers (Eastern Hepatobiliary Surgery Hospital, Changhai Hospital, Changzheng Hospital, Minhang Hospital, Huadong Hospital, and Affiliated Hospital of Hangzhou Normal University) between January 2013 and December 2017. cHCC-CCA is defined as a primary liver cancer requiring simultaneous histopathological demonstration of both hepatocellular and cholangiocellular differentiation within the same tumor nodule, as defined in the 5th edition of the World Health Organization Classification of Digestive System Tumours. The patients with neoadjuvant therapies before surgery, patients with recurrent cHCC-CCA, patients with heterologous differentiation components in tumor (e.g., chondroid differentiation), and patients with incomplete crucial clinical information were excluded from this study (Supplementary Figure 1). The study protocol complied with the Declaration of Helsinki and was approved by the Institutional Review Board of Eastern Hepatobiliary Surgery Hospital, approval No. EHBHKY2022-H010-P001 and confirmed by other centers. Owing to the retrospective nature of the study, written informed consent was waived by the ethics committee, provided that patient information was anonymized and no extra risk was imposed on patients.

Data collection

Clinical data were systematically extracted from institutional electronic records, including demographic profiles, preoperative laboratory findings, operative information, and histopathological assessments. Demographic profiles were sourced from the first hospitalization documentation. Serum biomarker measurements were based on the latest available preoperative laboratory evaluations. Liver resection strategies were defined in compliance with the Tokyo 2020 terminology of liver anatomy and resections[8]. The gross specimen parameters (tumor diameter, tumor number, distance of surgical margin, macrovascular invasion, etc.) were obtained from pathological reports. Considering the potential association between nutritional status and hepatic steatosis, we also incorporated the prognostic nutritional index as one of the evaluation parameters[9]. A single-blind histopathological review was independently conducted by three fellowship-trained pathologists to evaluate tumor differentiation, microvascular invasion (MVI)[10], perineural invasion (PNI)[11], tumor component proportion, intratumoral mature tertiary lymphoid structure and background liver pathology. Comprehensive slide examination incorporated 4-6 tumor and peritumoral regions and 1-2 non-neoplastic liver tissue sections per patient. For the patients with multifocal tumors, analytical emphasis was placed on the index of the largest cHCC-CCA lesion. Tumor-node-metastasis classification followed the current cancer staging guideline of the American Joint Committee on Cancer (8th edition)[12].

Pathological evaluation of hepatic steatosis

Three-micrometer-thick sections were cut from each formalin-fixed paraffin-embedded block using a microtome and stained with hematoxylin and eosin. All stained slides were independently evaluated through microscopic examination. Hepatic steatosis is a pathological manifestation, defined as the presence of large and small vesicles of fat within hepatocytes, predominantly triglycerides. In hematoxylin and eosin-stained sections, hepatic steatosis is characterized by the presence of numerous clear, well-circumscribed vacuoles within the cytoplasm of hepatocytes, resulting from the dissolution of intracellular lipid droplets during tissue processing. These vacuoles manifest in two primary patterns. Macrovesicular steatosis features a single large vacuole or a few large vacuoles that fill most of the cytoplasm, displacing the nucleus to the cell periphery and flattening it against the cell membrane (Supplementary Figure 2A). Microvesicular steatosis is defined by the accumulation of innumerable, small, uniform vacuoles that impart a foamy, spongiform appearance to the cytoplasm and the hepatocyte nucleus remains centrally located (Supplementary Figure 2B). These two patterns frequently coexist. The affected hepatocytes in both forms appear enlarged and distended but significantly reduced eosinophilic cytoplasmic staining due to the physical replacement of organelles by lipid. Hepatocytes surrounding the central vein are most susceptible to steatosis. Immunohistochemistry was performed using an automated stainer. However, Immunohistochemical staining was not routinely required and was only conducted on selected cases where cytokeratin 8/18 (clone: B22.1; Beijing Zhongshan Golden Bridge Biotechnology Co. Ltd.) was necessary to distinguish hepatic steatosis from hepatic edema. Cytokeratin 8/18 positivity was considered indicative of hepatic edema. As described previously, for each patient, the hematoxylin and eosin-stained sections included 4 to 6 tumor and peritumoral regions and 1 section to 2 sections of non-neoplastic liver tissue. All available non-tumorous hepatic regions from hematoxylin and eosin-stained slides of each patient were systematically evaluated. The severity of hepatic steatosis was graded based on the proportion of hepatocytes exhibiting intracellular lipid accumulation as observed by microscopy [(number of steatotic hepatocytes/total number of hepatocytes) × 100%]. Evaluation was performed at low to medium power magnification. Based on the criteria of Nonalcoholic Fatty Liver Disease Activity Score and Brunt’s pathologic criteria, the steatosis severity grading initially employed a semi-quantitative four-level ordinal scale. This scale was defined by the percentage of lipid-containing hepatocytes observed (grade 0, < 5%; grade 1, 5%-33%; grade 2, 33%-66%; grade 3, > 66%)[13,14]. Furthermore, hepatic steatosis with grade 0 or 1 was defined as negligible hepatic steatosis. Hepatic steatosis with grade 2 or 3 was defined as severe hepatic steatosis (Figure 1).

Figure 1
Figure 1 Histopathological images of different degree of hepatic steatosis of the normal liver tissue in combined hepatocellular-cholangiocarcinoma patients (40 × magnification). A: Grade 0, negligible; B: Grade 1, negligible; C: Grade 2, severe; D: Grade 3, severe.
Follow up and study endpoints

Postoperative monitoring followed an adaptive schedule with every 2-3 months evaluations during the first two years, transitioning to every 3-6 months intervals thereafter. Standard protocols incorporated tumor biomarker profiling (α-fetoprotein and carbohydrate antigen 19-9), HBV DNA load for hepatitis B surface antigen (HBsAg) positive individuals, and cross-sectional abdominal imaging (ultrasonography, computed tomography, or magnetic resonance imaging). Suspected recurrence, identified through imaging anomalies or serum tumor biomarker elevation, prompted multidisciplinary evaluation to formulate treatment strategies based on systemic status, hepatic functional reserve, and tumor burden characteristics. Clinical endpoints included recurrence-free survival (RFS: Surgery-to-relapse or censoring), overall survival (OS: Surgery-to-death or censoring), early (≤ 2 years) and late (> 2 years) RFS, with recurrence patterns categorized as intrahepatic (liver parenchymal, vascular, or biliary), extrahepatic (metastatic or lymphatic), or combined manifestations. Follow-up concluded in February 2025.

Statistical analysis

Quantitative data were presented as mean ± SD or median (interquartile range), while categorical variables were expressed as frequency distributions with percentages. Intergroup comparisons of continuous measurements utilized parametric tests (Student’s t-test or one-way analysis of variance) or their nonparametric counterparts (Mann-Whitney U or Kruskal-Wallis tests), whereas categorical comparisons employed χ2 tests or Fisher’s exact tests. Survival outcomes were analyzed through Kaplan-Meier curves with log-rank testing. Cox regression models were applied in univariate and multivariate frameworks to identify risk factors for survival, with model performance assessed via Harrell’s C-index. Logistic regression analyses identified predictors associated with hepatic steatosis, subsequently validated using area under the curve metrics. Variables exhibiting marginal significance (P < 0.2) in univariate screening underwent multivariate adjustment. Statistical significance was defined as a two-tailed P < 0.05. All statistical analyses were performed in R version 4.4.2 (R Foundation, Vienna).

RESULTS
Patient’s characteristics at baseline

This retrospective study enrolled 310 cHCC-CCA patients, predominantly male (n = 271, 87.4%) with an average age of 52.7 years (standard deviation: 10.3 years). Tumor characteristics revealed the median tumor diameter was 4.4 cm (interquartile range: 2.8-6.9 cm), with solitary lesions in 208 patients (67.1%) and multifocal lesions in 102 patients (32.9%). Tumor-node-metastasis staging categorized 236 patients (76.1%) as stages I-II and 74 (23.9%) as stages III-IV. Based on the degree of hepatic steatosis, the crude cohort was further stratified into grade 0 (n = 156, 50.3%), grade 1 (n = 127, 41.0%), grade 2 (n = 25, 8.1%), and grade 3 (n = 2, 0.6%), with negligible and severe hepatic steatosis prevalence rates of 91.3% (n = 283) and 8.7% (n = 27), respectively.

Comparative analysis demonstrated that patients with severe hepatic steatosis exhibited the following clinicopathological features when compared with patients with negligible hepatic steatosis: Higher body mass index (BMI), lymphocyte (LY), and prognostic nutritional index, lower alkaline phosphatase and lactate dehydrogenase (LDH), as well as smaller tumor diameter (all P < 0.05). These differences still exist even when the groups are formed using the four-level classification (Table 1).

Table 1 Baseline characteristics of all patients, n (%).
Characteristics
All patients (n = 310)
Grade 0 (n = 156)
Grade 1 (n = 127)
Grade 2 (n = 25)
Grade 3 (n = 2)
P value
Negligible (n = 283)
Severe (n = 27)
P value
Age (year), mean ± SD52.7 ± 10.353.4 ± 10.352.3 ± 10.651.2 ± 8.754.5 ± 4.90.69552.9 ± 10.451.5 ± 8.40.431
Sex0.900-0.551
Female39 (12.6)21 (13.5)16 (12.6)2 (8.0)0 (0.0)37 (13.1)2 (7.4)
Male271 (87.4)135 (86.5)111 (87.4)23 (92.0)2 (100.0)246 (86.9)25 (92.6)
BMI, kg/m224.2 (22.3; 26.2)22.9 (21.0; 24.8)25.4 (23.5; 26.6)26.6 (24.9; 28.0)26.6 (25.8; 27.4)< 0.00123.9 (22.1; 26.0)26.6 (24.9; 28.0)< 0.001
Hypertension0.199-0.288
No238 (76.8)126 (80.8)94 (74.0)17 (68.0)1 (50.0)220 (77.7)18 (66.7)
Yes72 (23.2)30 (19.2)33 (26.0)8 (32.0)1 (50.0)63 (22.3)9 (33.3)
Diabetes0.592-0.757
No272 (87.7)140 (89.7)109 (85.8)21 (84.0)2 (100.0)249 (88.0)23 (85.2)
Yes38 (12.3)16 (10.3)18 (14.2)4 (16.0)0 (0.0)34 (12.0)4 (14.8)
TBIL, μmol/L13.6 (10.7; 17.5)13.4 (10.9; 17.2)13.6 (10.6; 17.6)15.5 (11.8; 17.9)12.2 (10.5; 13.9)0.67513.6 (10.6; 17.4)15.5 (11.7; 17.7)0.403
DBIL, μmol/L5.2 (4.0; 6.9)5.0 (4.1; 6.8)5.4 (4.0; 7.0)5.2 (4.1; 7.8)4.0 (3.6; 4.4)0.6745.2 (4.0; 6.8)5.0 (4.0; 7.7)0.833
IBIL, μmol/L8.1 (6.5; 10.7)7.9 (6.6; 10.6)8.0 (6.2; 10.6)9.3 (8.0; 11.1)8.2 (6.9; 9.5)0.3978.0 (6.5; 10.6)9.3 (7.8; 10.9)0.112
TBA, μmol/L6.6 (4.4; 11.4)7.1 (4.5; 11.9)6.0 (4.0; 11.7)6.2 (5.3; 8.1)7.8 (7.2; 8.4)0.6436.6 (4.3; 11.7)6.2 (5.5; 8.1)0.816
TP, g/L68.9 (65.7; 73.2)68.3 (65.7; 73.2)69.5 (66.2; 73.2)69.1 (64.9; 72.2)68.9 (67.5; 70.4)0.85468.9 (65.8; 73.2)69.1 (65.1; 72.0)0.692
ALB, g/L42.0 (39.7; 44.3)41.7 (39.0; 44.2)42.1 (40.0; 44.2)42.5 (41.3; 44.6)43.8 (43.1; 44.4)0.47741.9 (39.5; 44.2)42.5 (41.3; 44.6)0.187
GLB, g/L26.8 (24.4; 30.3)26.9 (24.6; 30.4)27.4 (24.4; 30.7)26.0 (23.8; 28.1)25.2 (24.4; 26.0)0.52427.0 (24.4; 30.5)26.0 (23.7; 27.6)0.156
PA, mg/L212.9 ± 65.2206.5 ± 66.2215.4 ± 62.1238.6 ± 71.4214.5 ± 20.50.140210.5 ± 64.4236.8 ± 69.10.067
ALT, U/L32.0 (21.0; 48.0)27.5 (18.8; 41.2)34.0 (23.0; 50.0)37.0 (24.0; 57.0)45.5 (40.8; 50.2)0.00832.0 (20.0; 47.0)37.0 (25.0; 56.0)0.118
AST, U/L30.0 (22.0; 40.0)29.5 (22.8; 42.0)30.5 (22.0; 39.8)28.0 (22.0; 35.0)30.5 (30.2; 30.8)0.94930.0 (22.0; 41.0)28.0 (22.5; 34.5)0.892
ASTm, U/L5.0 (4.0; 8.0)5.0 (4.0; 8.0)6.0 (4.0; 8.0)5.0 (4.0; 8.0)4.0 (3.5; 4.5)0.6526.0 (4.0; 8.0)5.0 (4.0; 8.0)0.460
GGT, U/L60.5 (35.0; 111.0)56.0 (31.0; 107.0)63.0 (34.2; 114.2)73.0 (44.0; 132.0)48.5 (40.2; 56.8)0.57758.0 (32.5; 111.0)65.0 (43.5; 109.5)0.429
ALP, U/L85.0 (68.8; 109.0)86.0 (71.0; 117.5)83.0 (67.2; 103.8)71.0 (61.0; 92.0)67.0 (67.0; 67.0)0.02785.0 (70.0; 110.0)69.0 (61.5; 91.0)0.022
LDH, U/L162.0 (142.0; 187.0)162.0 (142.0; 189.0)166.0 (146.0; 187.0)149.0 (136.0; 173.5)116.0 (108.5; 123.5)0.044162.0 (144.0; 189.0)143.0 (131.0; 173.0)0.016
SCR, μmol/L70.0 (62.0; 79.0)70.0 (60.8; 82.0)70.0 (63.0; 79.0)71.0 (66.0; 79.0)71.5 (70.2; 72.8)0.95670.0 (62.0; 79.5)71.0 (66.0; 79.0)0.576
WBC, 109/L5.5 (4.4; 6.6)5.3 (4.3; 6.4)5.6 (4.3; 6.6)6.2 (5.2; 7.0)6.0 (5.8; 6.2)0.2615.4 (4.3; 6.6)6.2 (5.2; 7.0)0.078
NE, 109/L3.4 (2.5; 4.2)3.3 (2.4; 4.1)3.4 (2.5; 4.3)3.4 (2.8; 4.3)3.7 (3.6; 3.9)0.7193.3 (2.4; 4.2)3.5 (2.8; 4.2)0.458
LY, 109/L1.6 (1.3; 1.9)1.5 (1.2; 1.8)1.6 (1.3; 1.9)1.9 (1.7; 2.1)1.7 (1.6; 1.8)0.0131.5 (1.2; 1.9)1.9 (1.6; 2.1)0.003
MO, 109/L0.4 (0.3; 0.5)0.4 (0.3; 0.5)0.4 (0.3; 0.5)0.4 (0.3; 0.5)0.4 (0.4; 0.5)0.8980.4 (0.3; 0.5)0.4 (0.3; 0.5)0.799
EO, 109/L0.1 (0.1; 0.2)0.1 (0.1; 0.2)0.1 (0.1; 0.2)0.2 (0.1; 0.3)0.1 (0.1; 0.2)0.2830.1 (0.1; 0.2)0.2 (0.1; 0.3)0.144
BA, 109/L< 0.1 (< 0.1; < 0.1)< 0.1 (< 0.1; < 0.1)< 0.1 (< 0.1; < 0.1)< 0.1 (< 0.1; < 0.1)< 0.1 (< 0.1; < 0.1)0.938< 0.1 (< 0.1; < 0.1)< 0.1 (< 0.1; < 0.1)0.562
RBC, 1012/L4.6 ± 0.54.5 ± 0.64.7 ± 0.54.6 ± 0.54.4 ± 0.30.1004.6 ± 0.54.6 ± 0.50.863
PLT, 109/L150.5 (108.2; 195.8)145.5 (105.5; 195.5)152.0 (106.0; 191.5)162.0 (130.0; 196.0)197.0 (181.5; 212.5)0.510149.0 (105.5; 193.5)163.0 (130.5; 197.5)0.237
INR1.0 (0.9; 1.1)1.0 (1.0; 1.1)1.0 (0.9; 1.0)1.0 (0.9; 1.0)0.9 (0.9; 0.9)0.2361.0 (0.9; 1.1)1.0 (0.9; 1.0)0.122
PT, second11.9 (11.4; 12.7)12.0 (11.5; 12.8)12.0 (11.4; 12.6)11.7 (11.3; 12.6)11.2 (11.1; 11.4)0.31012.0 (11.4; 12.7)11.6 (11.3; 12.4)0.215
AFP, μg/L57.2 (8.3; 399.6)67.4 (8.8; 558.1)37.1 (6.7; 244.4)122.7 (9.2; 615.4)234.4 (132.7; 336.1)0.55151.4 (8.1; 395.8)122.7 (9.9; 526.6)0.494
CEA, μg/L2.7 (1.7; 4.1)2.7 (1.6; 3.8)2.8 (1.9; 4.4)2.6 (1.6; 3.9)1.2 (1.2; 1.3)0.1622.7 (1.7; 4.2)2.4 (1.6; 3.8)0.529
CA199, U/mL22.2 (11.5; 49.4)22.5 (12.6; 48.9)20.9 (9.5; 48.7)32.1 (18.5; 57.1)25.6 (17.2; 33.9)0.39521.5 (11.0; 49.1)32.1 (18.1; 54.8)0.189
HBsAg0.515-1.000
Negative53 (17.1)28 (17.9)21 (16.5)3 (12.0)1 (50.0)49 (17.3)4 (14.8)
Positive257 (82.9)128 (82.1)106 (83.5)22 (88.0)1 (50.0)234 (82.7)23 (85.2)
HBsAb0.178-0.509
Negative277 (89.4)143 (91.7)111 (87.4)22 (88.0)1 (50.0)254 (89.8)23 (85.2)
Positive33 (10.6)13 (8.3)16 (12.6)3 (12.0)1 (50.0)29 (10.2)4 (14.8)
HBeAg0.418-1.000
Negative240 (77.4)126 (80.8)93 (73.2)19 (76.0)2 (100.0)219 (77.4)21 (77.8)
Positive70 (22.6)30 (19.2)34 (26.8)6 (24.0)0 (0.0)64 (22.6)6 (22.2)
HBeAb0.930-1.000
Negative99 (31.9)50 (32.1)40 (31.5)9 (36.0)0 (0.0)90 (31.8)9 (33.3)
Positive211 (68.1)106 (67.9)87 (68.5)16 (64.0)2 (100.0)193 (68.2)18 (66.7)
HBcAb0.331-0.522
Negative8 (2.6)2 (1.3)5 (3.9)1 (4.0)0 (0.0)7 (2.5)1 (3.7)
Positive302 (97.4)154 (98.7)122 (96.1)24 (96.0)2 (100.0)276 (97.5)26 (96.3)
HBV DNA load0.190-0.585
NA10 (3.2)5 (3.2)5 (3.9)0 (0.0)0 (0.0)10 (3.5)0 (0.0)
≤ 1 × 103 IU/mL177 (57.1)100 (64.1)63 (49.6)13 (52.0)1 (50.0)163 (57.6)14 (51.9)
> 1 × 103 IU/mL123 (39.7)51 (32.7)59 (46.5)12 (48.0)1 (50.0)110 (38.9)13 (48.1)
HCV0.785-1.000
Negative305 (98.4)154 (98.7)124 (97.6)25 (100.0)2 (100.0)278 (98.2)27 (100.0)
Positive5 (1.6)2 (1.3)3 (2.4)0 (0.0)0 (0.0)5 (1.8)0 (0.0)
Ascites0.815-1.000
Negative284 (91.6)141 (90.4)118 (92.9)23 (92.0)2 (100.0)259 (91.5)25 (92.6)
Positive26 (8.4)15 (9.6)9 (7.1)2 (8.0)0 (0.0)24 (8.5)2 (7.4)
Macrovascular invasion0.902-0.774
Negative240 (77.4)118 (75.6)100 (78.7)20 (80.0)2 (100.0)218 (77.0)22 (81.5)
Positive70 (22.6)38 (24.4)27 (21.3)5 (20.0)0 (0.0)65 (23.0)5 (18.5)
Large bile duct invasion1.000-1.000
Negative296 (95.5)149 (95.5)121 (95.3)24 (96.0)2 (100.0)270 (95.4)26 (96.3)
Positive14 (4.5)7 (4.5)6 (4.7)1 (4.0)0 (0.0)13 (4.6)1 (3.7)
Pringle maneuver0.911-0.789
No52 (16.8)26 (16.7)21 (16.5)5 (20.0)0 (0.0)47 (16.6)5 (18.5)
Yes258 (83.2)130 (83.3)106 (83.5)20 (80.0)2 (100.0)236 (83.4)22 (81.5)
Transfusion0.447-0.150
No264 (85.2)131 (84.0)107 (84.3)24 (96.0)2 (100.0)238 (84.1)26 (96.3)
Yes46 (14.8)25 (16.0)20 (15.7)1 (4.0)0 (0.0)45 (15.9)1 (3.7)
Surgery0.662-1.000
Anatomic73 (23.5)41 (26.3)26 (20.5)6 (24.0)0 (0.0)67 (23.7)6 (22.2)
Non-anatomic237 (76.5)115 (73.7)101 (79.5)19 (76.0)2 (100.0)216 (76.3)21 (77.8)
Surgical margin0.023-0.158
> 0.1 cm138 (44.5)58 (37.2)64 (50.4)14 (56.0)2 (100.0)122 (43.1)16 (59.3)
≤ 0.1 cm172 (55.5)98 (62.8)63 (49.6)11 (44.0)0 (0.0)161 (56.9)11 (40.7)
Tumor diameter, cm4.4 (2.8; 6.9)5.0 (3.0; 8.5)4.1 (2.8; 6.0)3.5 (2.1; 5.3)3.3 (3.2; 3.4)0.0444.5 (2.8; 7.0)3.5 (2.2; 5.2)0.040
Tumor number0.631-1.000
Single208 (67.1)101 (64.7)89 (70.1)16 (64.0)2 (100.0)190 (67.1)18 (66.7)
Multiple102 (32.9)55 (35.3)38 (29.9)9 (36.0)0 (0.0)93 (32.9)9 (33.3)
Lymph node metastasis0.241-1.000
Negative278 (89.7)138 (88.5)115 (90.6)24 (96.0)1 (50.0)253 (89.4)25 (92.6)
Positive32 (10.3)18 (11.5)12 (9.4)1 (4.0)1 (50.0)30 (10.6)2 (7.4)
Distant metastasis0.785-1.000
Negative305 (98.4)154 (98.7)124 (97.6)25 (100.0)2 (100.0)278 (98.2)27 (100.0)
Positive5 (1.6)2 (1.3)3 (2.4)0 (0.0)0 (0.0)5 (1.8)0 (0.0)
Tumor component proportion0.337-0.231
HCC-dominant93 (30.0)42 (26.9)42 (33.1)9 (36.0)0 (0.0)84 (29.7)9 (33.3)
Balanced103 (33.2)54 (34.6)37 (29.1)10 (40.0)2 (100.0)91 (32.2)12 (44.4)
CCA-dominant114 (36.8)60 (38.5)48 (37.8)6 (24.0)0 (0.0)108 (38.2)6 (22.2)
Tumor differentiation0.326-0.136
Well-moderate114 (36.8)57 (36.5)43 (33.9)13 (52.0)1 (50.0)100 (35.3)14 (51.9)
Poor196 (63.2)99 (63.5)84 (66.1)12 (48.0)1 (50.0)183 (64.7)13 (48.1)
MVI0.734-1.000
Negative138 (44.5)68 (43.6)58 (45.7)12 (48.0)0 (0.0)126 (44.5)12 (44.4)
Positive172 (55.5)88 (56.4)69 (54.3)13 (52.0)2 (100.0)157 (55.5)15 (55.6)
PNI0.739-0.591
Negative260 (83.9)133 (85.3)103 (81.1)22 (88.0)2 (100.0)236 (83.4)24 (88.9)
Positive50 (16.1)23 (14.7)24 (18.9)3 (12.0)0 (0.0)47 (16.6)3 (11.1)
Capsule0.016-1.000
Negative61 (19.7)41 (26.3)15 (11.8)5 (20.0)0 (0.0)56 (19.8)5 (18.5)
Positive249 (80.3)115 (73.7)112 (88.2)20 (80.0)2 (100.0)227 (80.2)22 (81.5)
Intratumoral mTLS0.222-0.743
Negative251 (81.0)130 (83.3)98 (77.2)22 (88.0)1 (50.0)228 (80.6)23 (85.2)
Positive59 (19.0)26 (16.7)29 (22.8)3 (12.0)1 (50.0)55 (19.4)4 (14.8)
Cirrhosis0.585-0.726
Negative168 (54.2)89 (57.1)63 (49.6)15 (60.0)1 (50.0)152 (53.7)16 (59.3)
Positive142 (45.8)67 (42.9)64 (50.4)10 (40.0)1 (50.0)131 (46.3)11 (40.7)
Prognostic nutritional index50.2 (46.5; 53.3)49.2 (46.0; 52.6)50.5 (47.3; 53.5)52.5 (49.1; 54.2)52.4 (51.3; 53.5)0.03350.0 (46.2; 53.0)52.5 (49.3; 54.4)0.014
TNM0.143-0.164
I-II236 (76.1)115 (73.7)97 (76.4)23 (92.0)1 (50.0)212 (74.9)24 (88.9)
III-IV74 (23.9)41 (26.3)30 (23.6)2 (8.0)1 (50.0)71 (25.1)3 (11.1)
Impact of hepatic steatosis on the prognosis

The cohort of 310 patients demonstrated median follow-up, RFS, and OS periods of 8.52 years (7.61-9.81 years), 0.43 years (0.14-2.02 years), and 2.20 years (0.78-10.04 years), respectively. Additionally, seven patients (2.26%) died within 30 days postoperatively.

For the patients with grade 0-3 hepatic steatosis, the median (interquartile range) RFS of four groups were 0.36 years (0.12-1.93 years), 0.46 years (0.20-1.70 years), 1.09 years (0.24-6.05 years), and 1.03 years (1.03 years, not reached). The corresponding 1 year-, 2 year-, 5 year-, 10 year-RFS rates were 31.8%, 24.9%, 15.4%, and 12.7% vs 35.3%, 21.3%, 16.0%, and 8.9% vs 52.0%, 44.0%, 27.0%, and 21.6% vs 100.0%, 50.0%, 50.0%, and 50.0% (P = 0.181, Supplementary Figure 3A). The median (interquartile range) OS of four groups were 2.23 years (0.66 years, not reached), 1.92 years (0.78-9.72 years), 2.52 years (1.47-9.85 years), 1.60 years (1.60 years, not reached). The corresponding 1 year-, 2 year-, 5 year-, 10 year-OS rates were 67.9%, 53.6%, 35.2%, and 30.0% vs 70.0%, 47.3%, 30.1%, and 22.9% vs 84.0%, 60.0%, 35.6%, and 0.0%; 100.0%, 50.0%, 50.0%, 0.0% (P = 0.804, Supplementary Figure 3B). There was no significant difference in early RFS (P = 0.152, Supplementary Figure 3C) and late RFS (P = 0.838, Supplementary Figure 3D) among four groups.

Considering the similar prognosis of grade 0 and 1 groups as well as grade 2 and 3 groups as well as the extremely small number of patients in grade 3 group, further analyses were performed between the negligible hepatic steatosis group and severe hepatic steatosis group. For the patients with negligible and severe hepatic steatosis, the median (interquartile range) RFS were 0.36 years (0.14-1.82 years) and 1.09 years (0.24-6.05 years). The corresponding 1 year-, 2 year-, 5 year-, 10 year-RFS rates were 33.4%, 23.3%, 15.7%, and 10.6% vs 55.6%, 44.4%, 28.8%, and 24.0% (P = 0.035, Figure 2A). The median (interquartile range) OS of two groups were 2.17 years (0.71-10.16 years) and 2.52 years (1.47-9.85 years). The corresponding 1 year-, 2 year-, 5 year-, 10 year-OS rates were 68.9%, 50.8%, 32.9%, and 26.6% vs. 85.2%, 59.3%, 36.7%, and 0.0% (P = 0.586, Supplementary Figure 4A). A significant difference in early RFS (P = 0.024, Figure 2B) was observed between the two groups, whereas no significant difference was found in late RFS (P = 0.931, Supplementary Figure 4B).

Figure 2
Figure 2 Impact of the two-level degree of hepatic steatosis on the prognosis of combined hepatocellular-cholangiocarcinoma. aP < 0.05: Data with statistical significance. A: Recurrence-free survival; B: Early recurrence-free survival.

Two hundred and fifty-six patients were recorded with recurrence patterns. The recurrence patterns showed no significant difference between the patients with negligible or severe hepatic steatosis (P = 0.970, Supplementary Figure 5).

Subgroup analyses for the patients without and with liver cirrhosis

Given the close relationship between hepatic steatosis and liver fibrosis, subgroup analyses were conducted for patients without and with liver cirrhosis. For the patients without liver cirrhosis (n = 168), there were still significant differences in RFS (P = 0.038, Figure 3A) and early RFS (P = 0.022, Figure 3B) between those with negligible and severe hepatic steatosis. The median (interquartile range) RFS of two groups were 0.47 years (0.14-1.95 years) and 2.02 years (0.26 years, not reached). The corresponding 1 year-, 2 year-, 5 year-, 10 year-RFS rates were 34.7%, 24.8%, 15.6%, and 12.3% vs 56.3%, 56.3%, 35.7%, and 26.8%. No significant differences were observed in OS (P = 0.696, Supplementary Figure 6A) or late RFS (P = 0.950, Supplementary Figure 6B) between the two groups.

Figure 3
Figure 3 Impact of the degree of hepatic steatosis on the prognosis of combined hepatocellular-cholangiocarcinoma patients without liver cirrhosis. aP < 0.05: Data with statistical significance. A: Recurrence-free survival; B: Early recurrence-free survival.

For the patients with liver cirrhosis (n = 142), there were not significant different in RFS (P = 0.477, Supplementary Figure 7A) and early RFS (P = 0.497, Supplementary Figure 7B) between those with negligible and severe hepatic steatosis. The median (interquartile range) RFS of two groups were 0.29 years (0.14-1.52 years) and 1.03 years (0.13-2.04 years). The corresponding 1 year-, 2 year-, 5 year-, 10 year-RFS rates were 31.9%, 21.6%, 16.1%, and 8.0% vs 54.5%, 27.3%, 18.2%, and 0.0%. No significant differences were also observed in OS (P = 0.817, Supplementary Figure 7C) or late RFS (P = 0.833, Supplementary Figure 7D) between the two groups.

Predictors of severe hepatic steatosis

The univariate logistic analyses of the predictive factors of severe hepatic steatosis were shown in Supplementary Table 1. Multivariate logistic analysis showed that higher BMI, higher LY, and lower LDH were the independent predictors of severe hepatic steatosis (area under the curve value: 0.816, Table 2).

Table 2 Multivariate logistic analysis of the predictive factors of hepatic steatosis.
Characteristics
OR (95%CI)
P value
BMI, kg/m21.300 (1.127-1.494)< 0.001
LDH, U/L0.980 (0.960-0.994)0.008
LY, 109/L2.730 (1.252-5.958)0.012
Survival analyses of cHCC-CCA patients

The univariate Cox regression analyses of RFS, OS, early RFS, and late RFS were shown in Supplementary Tables 2-5. Multivariate Cox regression analyses showed that age, macrovascular invasion, tumor diameter, tumor number, tumor component proportion, MVI, PNI, and hepatic steatosis were the independent factors of RFS (C-index: 0.710, Table 3); LY, macrovascular invasion, tumor diameter, tumor number, MVI, PNI, and intratumoral mature tertiary lymphoid structure were the independent factors of OS (C-index: 0.716, Table 4); Age, macrovascular invasion, tumor diameter, tumor number, MVI, PNI, and hepatic steatosis were the independent factors of early RFS (C-index: 0.706, Table 5); Albumin, basophil, and tumor number were the independent factors of late RFS (C-index: 0.683, Table 6).

Table 3 Multivariate Cox regression analysis of recurrence-free survival.
Characteristics
HR (95%CI)
P value
Age, years0.982 (0.969-0.995)0.007
Macrovascular invasion, positive1.621 (1.156-2.271)0.005
Tumor diameter, cm1.048 (1.011-1.087)0.011
Tumor number, multiple1.937 (1.466-2.560)< 0.001
Tumor component proportion, balanced1.706 (1.216-2.393)0.002
Tumor component proportion, CCA-dominant1.524 (1.101-2.109)0.011
MVI, positive1.685 (1.292-2.197)< 0.001
PNI, positive1.445 (1.027-2.035)0.035
Hepatic steatosis, severe0.614 (0.383-0.984)0.043
Table 4 Multivariate Cox regression analysis of overall survival.
Characteristics
HR (95%CI)
P value
LY, 109/L0.725 (0.559-0.940)0.015
Macrovascular invasion, positive1.980 (1.417-2.766)< 0.001
Tumor diameter, cm1.058 (1.016-1.102)0.006
Tumor number, multiple1.752 (1.313-2.339)< 0.001
MVI, positive2.115 (1.578-2.835)< 0.001
PNI, positive1.732 (1.215-2.467)0.002
Intratumoral mTLS, positive0.676 (0.460-0.993)0.046
Table 5 Multivariate Cox regression analysis of early recurrence-free survival.
Characteristics
HR (95%CI)
P value
Age, years0.984 (0.971-0.997)0.016
Macrovascular invasion, positive1.597 (1.129-2.261)0.008
Tumor diameter, cm1.051 (1.011-1.092)0.011
Tumor number, multiple1.925 (1.438-2.577)< 0.001
MVI, positive1.783 (1.332-2.386)< 0.001
PNI, positive1.512 (1.068-2.142)0.020
Hepatic steatosis, severe0.577 (0.339-0.983)0.043
Table 6 Multivariate Cox regression analysis of late recurrence-free survival.
Characteristics
HR (95%CI)
P value
ALB, g/L0.875 (0.792-0.967)0.009
BA, 109/L0.000 (0.000-0.014)0.024
Tumor number, multiple3.485 (1.002-12.110)0.050
DISCUSSION

For a long period of time, cHCC-CCA has lacked an independent paradigm for pathological diagnosis, with both the International Collaboration on Cancer Reporting and the College of American Pathologists incorporating its pathological diagnosis into the framework of intrahepatic cholangiocarcinoma (iCCA). This reflects not only its diagnostic criteria have been constantly evolving over the past two decades[15] but also the scarcity of large-scale cohort studies because of its low incidence. Consequently, it is difficult for clinicians to obtain valuable information from a non-tailored pathological report to conduct appropriate therapeutic interventions for cHCC-CCA patients.

Previous studies have shown that the prognostic significance of hepatic steatosis across different histological subtypes of primary liver cancer remains unclear. From the perspective of postoperative complications and surgery-related mortality, a meta-analysis indicated that patients with hepatic steatosis after liver resection had a twofold increased risk of postoperative complications, and those with severe steatosis had an almost threefold risk of mortality[16]. Regarding long-term clinical outcomes, Su et al[17] suggested that among patients with early-stage HCC meeting the Milan criteria, approximately 40% exhibited hepatic steatosis, which was associated with poorer OS (5-year rate: 57.8% vs 75.6%), particularly in non-cirrhotic patients. Conversely, a Japanese study reported that in HCC patients without HBV or hepatitis C virus infection, the absence of hepatic steatosis was associated with worse disease-free survival [hazard ratio (HR) = 2.13, 95% confidence interval (CI): 1.21-3.93, P = 0.0077][18]. Another study found that in non-alcoholic and non-viral hepatitis-related HCC, the absence of hepatic steatosis was significantly correlated with shorter disease-free survival (HR = 2.14, 95%CI: 1.21-3.80; P = 0.009)[19]. A subsequent study by a Chinese team further reported that in patients with HBV-related HCC, those with concomitant steatotic liver disease demonstrated significantly better OS (P = 0.047). Additionally, these patients exhibited lower levels of α-fetoprotein (Z = 7.82, P = 0.007), lower tumor grades (χ2 = 6.567, P = 0.035), and reduced incidence of MVI (χ2 = 6.252, P = 0.044)[20]. Even in HCC patients treated with radiofrequency ablation, a study showed that the presence of steatotic liver disease is also associated with lower all-cause mortality (adjusted HR = 0.67; 95%CI: 0.45-0.996; P = 0.048)[21]. In contrast, emerging evidence suggests that HCC arising from steatotic liver disease exhibits significantly better clinical outcomes compared to other etiologies-associated HCC[22]. For iCCA, no study has independently investigated the impact of hepatic steatosis on prognosis. However, a study suggested that nonalcoholic fatty liver disease-related iCCA had a poorer prognosis compared to HBV-related iCCA in terms of OS (HR = 2.26, 95%CI: 1.63-3.13, P < 0.001), RFS (HR = 2.24, 95%CI: 1.61-3.10, P < 0.001), and early RFS (HR = 2.23, 95%CI: 1.60-3.09, P < 0.001)[23]. Additionally, iCCA patients with a higher BMI exhibited worse outcomes (odds ratio = 1.16, 95%CI: 1.02-1.32, for every 5-unit increase)[24]. From the perspective of explaining adverse outcomes in liver cancer patients, steatosis may induce inflammation and fibrosis of the liver; meanwhile, it directly contributes to hepatocyte necrosis. These pathological injuries may collectively exacerbate tumor progression. From the perspective of explaining favorable outcomes in liver cancer patients, hepatic steatosis may represent a better nutritional status. These seemingly conflicting and ambiguous conclusions underscore the necessity to elucidate the significance of background hepatic steatosis in cHCC-CCA.

Based on our results, patients with severe hepatic steatosis exhibited higher LY, prealbumin, and prognostic nutritional index, lower alkaline phosphatase and LDH, smaller tumor diameter, and better tumor differentiation (all demonstrating significant or borderline statistical significance). These findings indicate that cHCC-CCA patients with severe hepatic steatosis possess enhanced immune defensive status, improved nutritional status, milder hepatic injury, and less aggressive tumor biological behavior. Severe hepatic steatosis emerged as a favorable factor of RFS, particularly in preventing early recurrence. Notably, this anti-recurrence effect was more pronounced in cHCC-CCA patients without liver cirrhosis. These results indicate that hepatic steatosis may serve as a compensatory protective mechanism for cHCC-CCA patients especially for those with relatively preserved hepatic backgrounds. The multivariate prognostic models further confirmed severe hepatic steatosis as an independent protective factor for both RFS and early RFS.

The close association between hepatic steatosis and the nutritional status of patients is of significant interest. Parameters such as serum LY count, prealbumin levels, and the prognostic nutritional index all reflect nutritional status[25-27] and are closely correlated with hepatic steatosis. Moreover, these parameters served as protective prognostic factors for clinical outcomes in patients with cHCC-CCA. This suggests that a certain degree of hepatic fat accumulation may provide adequate energy reserves to support better postoperative recovery. However, hepatic steatosis and these parameters exhibited divergent effects on clinical outcomes. For instance, while hepatic steatosis showed no statistically significant association with OS in cHCC-CCA patients, LY, prealbumin, and the prognostic nutritional index were indicative of improved OS. Therefore, severe hepatic steatosis should not be equated with favorable nutritional status, nor should a high BMI be considered a reliable indicator of good nutrition[28]. Based on epidemiological evidence, maintaining a healthy body weight remains essential[29]. However, further research is warranted to explore strategies for preserving a certain degree of hepatic fat reserves in populations at high-risk for cHCC-CCA, when their livers are exposed to stressors such as the hepatitis viruses.

Given that most patients in our cohort had viral hepatitis, the interplay between hepatic steatosis and viral pathogenesis warrants particular attention. Recent studies demonstrate that metabolic dysfunction-associated steatotic liver disease in patients with HBV infection can suppress viral replication and promote HBsAg seroclearance[30], potentially through increased apoptosis of HBV-infected hepatocytes[31]. For patients with hepatitis C virus infection, those with concomitant metabolic dysfunction-associated steatotic liver disease exhibited enhanced anti-fibrotic benefits from direct-acting antiviral therapy[32]. This may be attributed to lipid droplet accumulation buffering toxic lipid metabolites. By sequestering lipotoxic substances within these lipid droplets, hepatocytes can protect vital organelles from hepatitis C virus-induced damage, thereby delaying fibrosis progression[33]. These findings collectively suggest that hepatic steatosis might mitigate viral pathogenicity and attenuate virus-induced fibrotic progression in cHCC-CCA patients. Regarding the intrinsic characteristics of tumors, previous studies and our experience indicate that steatotic liver disease-associated HCCs sometimes show well-differentiated histology and steatohepatitis-like morphology, requiring differential diagnosis from hepatocellular adenoma[34]. Such characteristics suggest potentially better prognosis.

To our knowledge, this represents the first multicenter pathological study investigating the significance of hepatic steatosis in cHCC-CCA, providing detailed stratification of steatosis severity on clinical outcomes in this rare tumor entity. However, our study has several limitations. First, subgroup analysis based on different etiologies of cHCC-CCA was not conducted, primarily due to the predominant inclusion of viral hepatitis patients in the cohort, along with comparable HBsAg positivity rates, HBV DNA load positivity rates, and hepatitis C virus infection rates between the patients with negligible and severe hepatic steatosis. Therefore, etiological factors might not constitute potential bias in this study. Second, as the patient population included in this study was exclusively of Asian ethnicity, the generalizability of the findings across other racial and ethnic groups, including White and Black populations, requires confirmation through multinational studies in the future. Additionally, constrained by challenges in data collection, we did not analyze postoperative weight changes, limiting us to elucidate why hepatic steatosis specifically impacts RFS without affecting OS. Lastly, while pathological evaluation of hepatic steatosis offers higher precision, it remains susceptible to sampling randomness. Nevertheless, the strong correlation between BMI and hepatic steatosis in this study suggests that our findings are reasonable.

CONCLUSION

Through this large-scale multicenter study, we found that severe hepatic steatosis is associated with prolonged RFS and early RFS in patients with cHCC-CCA, particularly in those without cirrhosis. However, it does not have an impact on late RFS and OS. Beyond obesity, severe hepatic steatosis correlates closely with the elevated serum LY level and reduced LDH level, suggesting enhanced immune defense and attenuated hepatic injury. We recommend incorporating the pathological evaluation of hepatic steatosis into the routine diagnostic protocol for cHCC-CCA to improve the precision of clinical management for those patients.

References
1.  Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229-263.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 16785]  [Cited by in RCA: 14476]  [Article Influence: 7238.0]  [Reference Citation Analysis (17)]
2.  Terashima T, Harada K, Yamashita T. Diagnosis, clinical characteristics, and treatment of combined hepatocellular-cholangiocarcinoma. Jpn J Clin Oncol. 2025;55:327-333.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 4]  [Reference Citation Analysis (0)]
3.  Wang J, Li E, Yang H, Wu J, Lu HC, Yi C, Lei J, Liao W, Wu L. Combined hepatocellular-cholangiocarcinoma: a population level analysis of incidence and mortality trends. World J Surg Oncol. 2019;17:43.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 20]  [Cited by in RCA: 31]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
4.  Yan R, Sun M, Yang H, Du S, Sun L, Mao Y. 2024 latest report on hepatitis B virus epidemiology in China: current status, changing trajectory, and challenges. Hepatobiliary Surg Nutr. 2025;14:66-77.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 32]  [Cited by in RCA: 32]  [Article Influence: 32.0]  [Reference Citation Analysis (0)]
5.  European Association for the Study of the Liver (EASL); European Association for the Study of Diabetes (EASD);  European Association for the Study of Obesity (EASO). EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). J Hepatol. 2024;81:492-542.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1322]  [Cited by in RCA: 1194]  [Article Influence: 597.0]  [Reference Citation Analysis (2)]
6.  Chan SL, Sun HC, Xu Y, Zeng H, El-Serag HB, Lee JM, Schwartz ME, Finn RS, Seong J, Wang XW, Paradis V, Abou-Alfa GK, Rimassa L, Kao JH, Zhang BH, Llovet JM, Bruix J, Yip TC, Wong VW, Wong GL, Chan LL, Liu MQ, Gao Q, Shen F, Kelley RK, Cheng AL, Kurosaki M, Toyoda H, Chen WX, Murakami T, Liang P, Zucman-Rossi J, Minami Y, Miyayama S, Wang K, Man K, Hasegawa K, Li Q, Tsuchiya K, Xu L, Chew V, Chow P, Hoshida Y, Lujambio A, Ng IO, Sakamoto M, Park YN, Yau T, Kudo M, Fan J, Zhou J. The Lancet Commission on addressing the global hepatocellular carcinoma burden: comprehensive strategies from prevention to treatment. Lancet. 2025;406:731-778.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 69]  [Cited by in RCA: 73]  [Article Influence: 73.0]  [Reference Citation Analysis (1)]
7.  Zhou J, Sun H, Wang Z, Cong W, Zeng M, Zhou W, Liu L, Wen T, Kuang M, Zhang B, Tao K, Han G, Yan Z, Wang M, Liu R, Guo J, Zeng Z, Liang P, Ren Z, Hou J, Zhang Y, Liu X, Pan H, Bi F, Liang C, Chen M, Yan F, Xu H, Xie X, Ju S, Ji Y, Yun J, Li Z, Bai X, Cai D, Chen W, Chen Y, Chen Y, Cheng W, Cheng S, Dai Z, Dai C, Gao Q, Guo R, Guo W, Guo Y, Hua B, Huang X, Jiang H, Jia W, Li Q, Li T, Li X, Li X, Li Y, Li Y, Liang J, Liang X, Ling C, Liu H, Liu T, Lu S, Lv G, Mao Y, Meng Z, Peng T, Ren W, Shi G, Shi H, Shi M, Song T, Tan G, Wang J, Wang K, Wang L, Wang W, Wang X, Wang Z, Xiang B, Xia J, Xing B, Xu J, Xu J, Yang J, Yang X, Yang Y, Yang Y, Yao X, Yin Z, Yuan Z, Zeng Y, Zeng Y, Zhang B, Zhang L, Zhang S, Zhang T, Zhang Z, Zhao M, Zhao Y, Zheng H, Zhou L, Zhu J, Zhu K, Shi Y, Liu R, Zhang L, Xiao Y, Yang C, Wu Z, Ding Z, Zhu X, Tang Z, Huang X, Han H, Wu H, Chen M, Wang W, Li Q, Cai J, Shen F, Cai X, Qin S, Teng G, Fan J. China Liver Cancer Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2024 Edition). Liver Cancer. 2025;14:779-835.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 4]  [Cited by in RCA: 17]  [Article Influence: 17.0]  [Reference Citation Analysis (4)]
8.  Wakabayashi G, Cherqui D, Geller DA, Abu Hilal M, Berardi G, Ciria R, Abe Y, Aoki T, Asbun HJ, Chan ACY, Chanwat R, Chen KH, Chen Y, Cheung TT, Fuks D, Gotohda N, Han HS, Hasegawa K, Hatano E, Honda G, Itano O, Iwashita Y, Kaneko H, Kato Y, Kim JH, Liu R, López-Ben S, Morimoto M, Monden K, Rotellar F, Sakamoto Y, Sugioka A, Yoshiizumi T, Akahoshi K, Alconchel F, Ariizumi S, Benedetti Cacciaguerra A, Durán M, Garcia Vazquez A, Golse N, Miyasaka Y, Mori Y, Ogiso S, Shirata C, Tomassini F, Urade T, Wakabayashi T, Nishino H, Hibi T, Kokudo N, Ohtsuka M, Ban D, Nagakawa Y, Ohtsuka T, Tanabe M, Nakamura M, Tsuchida A, Yamamoto M. The Tokyo 2020 terminology of liver anatomy and resections: Updates of the Brisbane 2000 system. J Hepatobiliary Pancreat Sci. 2022;29:6-15.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 105]  [Cited by in RCA: 131]  [Article Influence: 32.8]  [Reference Citation Analysis (0)]
9.  Onodera T, Goseki N, Kosaki G. [Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients]. Nihon Geka Gakkai Zasshi. 1984;85:1001-1005.  [PubMed]  [DOI]
10.  Wang H, Chen JJ, Yin SY, Sheng X, Wang HX, Lau WY, Dong H, Cong WM. A Grading System of Microvascular Invasion for Patients with Hepatocellular Carcinoma Undergoing Liver Resection with Curative Intent: A Multicenter Study. J Hepatocell Carcinoma. 2024;11:191-206.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 1]  [Cited by in RCA: 17]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
11.  Wang H, Zhou YY, Chen HZ, Sheng X, Xia CY, Qian YW, Yu H, Cao ZY, Cong WM, He MX, Dong H. Perineural invasion as a prognostic determinant in combined hepatocellular-cholangiocarcinoma: a multicenter pathological study. J Gastrointest Surg. 2025;29:102155.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 2]  [Cited by in RCA: 2]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
12.  Chun YS, Pawlik TM, Vauthey JN. 8th Edition of the AJCC Cancer Staging Manual: Pancreas and Hepatobiliary Cancers. Ann Surg Oncol. 2018;25:845-847.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 637]  [Cited by in RCA: 598]  [Article Influence: 74.8]  [Reference Citation Analysis (1)]
13.  Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, Ferrell LD, Liu YC, Torbenson MS, Unalp-Arida A, Yeh M, McCullough AJ, Sanyal AJ; Nonalcoholic Steatohepatitis Clinical Research Network. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41:1313-1321.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 9231]  [Cited by in RCA: 8576]  [Article Influence: 408.4]  [Reference Citation Analysis (4)]
14.  Brunt EM, Kleiner DE, Wilson LA, Belt P, Neuschwander-Tetri BA; NASH Clinical Research Network (CRN). Nonalcoholic fatty liver disease (NAFLD) activity score and the histopathologic diagnosis in NAFLD: distinct clinicopathologic meanings. Hepatology. 2011;53:810-820.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 1072]  [Cited by in RCA: 994]  [Article Influence: 66.3]  [Reference Citation Analysis (1)]
15.  Xu S, Calderaro J. Combined Hepatocellular-Cholangiocarcinoma: A Clinical and Molecular Review. Semin Liver Dis. 2025;45:476-486.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 1]  [Reference Citation Analysis (0)]
16.  de Meijer VE, Kalish BT, Puder M, Ijzermans JN. Systematic review and meta-analysis of steatosis as a risk factor in major hepatic resection. Br J Surg. 2010;97:1331-1339.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 225]  [Cited by in RCA: 199]  [Article Influence: 12.4]  [Reference Citation Analysis (0)]
17.  Su CW, Chau GY, Hung HH, Yeh YC, Lei HJ, Hsia CY, Lai CR, Lin HC, Wu JC. Impact of Steatosis on Prognosis of Patients with Early-Stage Hepatocellular Carcinoma After Hepatic Resection. Ann Surg Oncol. 2015;22:2253-2261.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 27]  [Cited by in RCA: 37]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
18.  Nishio T, Hatano E, Sakurai T, Taura K, Okuno M, Kasai Y, Seo S, Yasuchika K, Mori A, Kaido T, Uemoto S. Impact of Hepatic Steatosis on Disease-Free Survival in Patients with Non-B Non-C Hepatocellular Carcinoma Undergoing Hepatic Resection. Ann Surg Oncol. 2015;22:2226-2234.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 15]  [Cited by in RCA: 17]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
19.  Shigematsu Y, Kanda H, Amori G, Takahashi Y, Takazawa Y, Inamura K. Nonalcoholic non-virus-related hepatocellular carcinoma arising from nonsteatotic liver: Clinical and pathological features. Medicine (Baltimore). 2022;101:e28746.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 1]  [Cited by in RCA: 1]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
20.  Zheng B, Xiao Y, Wu F, Yang C, Sheng R, Zeng M. Impact of steatotic liver disease on hepatitis B-related hepatocellular carcinoma: MRI manifestation and prognostic potential. Br J Radiol. 2025;98:1313-1320.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Reference Citation Analysis (15)]
21.  Tsai FP, Su TH, Huang SC, Tseng TC, Hsu SJ, Liao SH, Hong CM, Liu CH, Yang HC, Liu CJ, Chen PJ, Kao JH. Outcomes of radiofrequency ablation for hepatocellular carcinoma with concurrent steatotic liver disease. Cancer. 2025;131:e35541.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1]  [Cited by in RCA: 2]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
22.  Su JY, Deng ZJ, Teng YX, Koh YX, Zhang WG, Zheng MH, Xie S, Huo RR, Chen CJ, Ma L, Zhong JH. Prognosis after hepatic resection of patients with hepatocellular carcinoma related to non-alcoholic fatty liver disease: meta-analysis. BJS Open. 2023;7:zrac167.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 12]  [Cited by in RCA: 19]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
23.  Yu Q, Lei Z, Ma W, Yang F, Tang H, Xiao Q, Tang X, Si A, Yang P, Zhou N, Cheng Z. Postoperative Prognosis of Non-alcoholic Fatty Liver Disease-Associated Intrahepatic Cholangiocarcinoma: a Multi-center Propensity Score Matching Analysis. J Gastrointest Surg. 2023;27:2403-2413.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1]  [Cited by in RCA: 5]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
24.  Merath K, Mehta R, Hyer JM, Bagante F, Sahara K, Alexandrescu S, Marques HP, Aldrighetti L, Maithel SK, Pulitano C, Weiss MJ, Bauer TW, Shen F, Poultsides GA, Soubrane O, Martel G, Koerkamp BG, Guglielmi A, Itaru E, Ejaz A, Pawlik TM. Impact of body mass index on tumor recurrence among patients undergoing curative-intent resection of intrahepatic cholangiocarcinoma- a multi-institutional international analysis. Eur J Surg Oncol. 2019;45:1084-1091.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 5]  [Cited by in RCA: 17]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
25.  Liang Y, Guo H, Man Q, Chang S, Wang E, Gao S. Prognostic nutritional score based on pretreatment lymphocyte, platelet, and prealbumin predicts prognosis in patients with pancreatic cancer. J Surg Oncol. 2023;128:831-843.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 5]  [Cited by in RCA: 6]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
26.  Zhang Y, Yu D, Xu X, Guo Y, Zhao Z, Ji S. Prealbumin Adjusted Prognostic Nutritional Index May Predict the Postoperative Survival and Free Walking Abilities of Patients with Hip Fractures: A Multi-Center Follow-Up Study. Clin Interv Aging. 2025;20:1571-1582.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in RCA: 2]  [Reference Citation Analysis (0)]
27.  Shen Q, Liu W, Quan H, Pan S, Li S, Zhou T, Ouyang Y, Xiao H. Prealbumin and lymphocyte-based prognostic score, a new tool for predicting long-term survival after curative resection of stage II/III gastric cancer. Br J Nutr. 2018;120:1359-1369.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 24]  [Cited by in RCA: 42]  [Article Influence: 5.3]  [Reference Citation Analysis (0)]
28.  Gastelurrutia P, Lupón J, de Antonio M, Zamora E, Domingo M, Urrutia A, Altimir S, Coll R, Díez C, Bayes-Genis A. Body mass index, body fat, and nutritional status of patients with heart failure: The PLICA study. Clin Nutr. 2015;34:1233-1238.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 34]  [Cited by in RCA: 42]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
29.  Yuan Y, Liu K, Zheng M, Chen S, Wang H, Jiang Q, Xiao Y, Zhou L, Liu X, Yu Y, Wu J, Ding X, Yang H, Li X, Min X, Zhang C, Zhang X, He M, Zheng Y, Sun D, Qi L, Hemler EC, Wu S, Wu T, Pan A. Analysis of Changes in Weight, Waist Circumference, or Both, and All-Cause Mortality in Chinese Adults. JAMA Netw Open. 2022;5:e2225876.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 2]  [Cited by in RCA: 61]  [Article Influence: 15.3]  [Reference Citation Analysis (0)]
30.  Mao X, Cheung KS, Peng C, Mak LY, Cheng HM, Fung J, Peleg N, Leung HH, Kumar R, Lee JH, Shlomai A, Yuen MF, Seto WK. Steatosis, HBV-related HCC, cirrhosis, and HBsAg seroclearance: A systematic review and meta-analysis. Hepatology. 2023;77:1735-1745.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 64]  [Cited by in RCA: 74]  [Article Influence: 24.7]  [Reference Citation Analysis (2)]
31.  Li MP, Luo KZ. The outcomes and mechanisms of chronic hepatitis B complicated by metabolic dysfunction-associated steatotic liver disease. Hepatobiliary Pancreat Dis Int. 2025;24:476-483.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 2]  [Reference Citation Analysis (0)]
32.  McCary A, Sheu YS, Chesbrough K, Jonas MC. Improved Liver Fibrosis Regression After Direct-Acting Antiviral Therapy in Hepatitis C Patients: A Comparison of Patients With and Without MASLD. Clin Ther. 2025;47:504-510.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 1]  [Reference Citation Analysis (0)]
33.  Jarc E, Petan T. Lipid Droplets and the Management of Cellular Stress. Yale J Biol Med. 2019;92:435-452.  [PubMed]  [DOI]
34.  Takahashi Y, Dungubat E, Kusano H, Fukusato T. Pathology and Pathogenesis of Metabolic Dysfunction-Associated Steatotic Liver Disease-Associated Hepatic Tumors. Biomedicines. 2023;11:2761.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 18]  [Cited by in RCA: 38]  [Article Influence: 12.7]  [Reference Citation Analysis (0)]
Footnotes

Peer review: Externally peer reviewed.

Peer-review model: Single blind

Corresponding Author's Membership in Professional Societies: Digestive Pathology Group, Society of Pathology, Chinese Medical Association; Pathology Group, Liver Cancer Professional Committee, Chinese Anti-Cancer Association.

Specialty type: Pathology

Country of origin: China

Peer-review report’s classification

Scientific quality: Grade B, Grade B

Novelty: Grade B, Grade B

Creativity or innovation: Grade A, Grade C

Scientific significance: Grade B, Grade C

P-Reviewer: Morozov S, MD, PhD, Professor, Senior Researcher, Russia S-Editor: Bai Y L-Editor: A P-Editor: Zhao YQ

Write to the Help Desk