Evolutionary changes in metabolic dysfunction-associated steatotic liver disease and risk of hepatocellular carcinoma: A nationwide cohort study
Article information
Abstract
Background/Aims
To determine the association between evolutionary changes in metabolic dysfunction-associated steatotic liver disease (MASLD) status and the risk of hepatocellular carcinoma (HCC) in a nationwide population-based cohort.
Methods
Information on study participants was derived from the Korea National Health Insurance Service database. The study population consisted of 5,080,410 participants who underwent two consecutive biennial health screenings between 2009 and 2012. All participants were followed up until HCC, death, or 31 December 2020. The association of evolutionary changes in MASLD status, as assessed by the fatty liver index and cardiometabolic risk factors, including persistent non-MASLD, resolved MASLD, incident MASLD, and persistent MASLD, with HCC risk was evaluated using multivariable-adjusted Cox proportional hazards regression.
Results
Among the 5,080,410 participants with 39,910,331 person-years of follow-up, 4,801 participants developed HCC. The incidence of HCC in participants with resolved, incident, and persistent MASLD was approximately 2.2-, 2.3-, and 4.7-fold higher, respectively, than that in those with persistent non-MASLD among the Korean adult population. When stratifying the participants according to the evolutionary change in MASLD status, persistent (adjusted hazard ratio [aHR], 2.94; 95% confidence interval [CI], 2.68–3.21; P<0.001), incident (aHR, 1.85; 95% CI, 1.63–2.10; P<0.001), and resolved MASLD (aHR, 1.33; 95% CI, 1.18–1.50; P<0.001) had an increased risk of HCC compared to persistent non-MASLD.
Conclusions
The evolutionary changes in MASLD were associated with the differential risk of HCC independent of metabolic risk factors and concomitant medications, providing additional information on the risk of HCC stratification in patients with MASLD.
Graphical Abstract
INTRODUCTION
Primary liver cancer is the sixth most common cancer worldwide and the third most common cause of cancer-related mortalities [1]. Hepatocellular carcinoma (HCC) accounts for up to 75% of all liver cancers, with global incidence and mortality rates of 9.3 and 8.5 per 100,000 person-years (PY) in 2018, respectively [2,3]. The incidence of HCC varies across different regions with regard to the proportion of etiologic factors, such as nonalcoholic fatty liver disease (NAFLD), hepatitis B virus (HBV), and hepatitis C virus (HCV) [4]. To date, rational and practical approaches to surveillance, diagnosis, early detection, prevention, and treatment have been developed, showing their efficacy in reducing the incidence of HCC and cancer-related mortality [5]. However, the incidence of HCC and cancer-related mortality continues to rise, and most patients remain undiagnosed until the advanced stages of the disease [6].
Chronic HBV and HCV infections, diabetes mellitus, alcohol intake, aflatoxins, and aristolochic acid are well-established risk factors for HCC [7-10]. However, NAFLD and nonalcoholic steatohepatitis (NASH) have become the most common liver diseases globally and have emerged as a major factor contributing to the development of HCC [11-13]. Indeed, the global proportion of NAFLD-related HCC accounts for up to 38% [14]. Although high-quality, large-scale, population-based studies exploring the association between NAFLD and the risk of HCC are lacking, several studies have confirmed its significant association with an increased risk of HCC [14,15]. In addition, NAFLD-related HCC often occurs even in patients without liver cirrhosis; a substantial number of HCC cases were found in patients with NAFLD without cirrhosis in large population-based studies [16,17]. However, current evidence is not sufficient to provide a confident rationale for the appropriate management of NAFLD to prevent the development of HCC in diverse populations with varying severity of NAFLD. Furthermore, approximately one-quarter of HCC cases have been reported to develop without any known risk factors [18]. More recently, Kim et al. [19] found that newly suggested metabolic dysfunction-associated steatotic liver disease (MASLD), defined as steatotic liver disease (fatty liver index ≥60) and at least one of the cardiometabolic risk factors, is associated with a higher risk of HCC [20]. However, the effects of evolutionary changes in MASLD status on the risk of HCC remain unclear.
In the present study, we sought to determine the association of evolutionary changes in MASLD status with the risk of HCC in a prospectively collected Korean nationwide cohort, which may support the establishment of better management strategies for patients with MASLD to prevent HCC.
MATERIALS AND METHODS
Study population
This South Korea nationwide retrospective cohort study derived information on the study population from the National Health Insurance Service (NHIS) of the Republic of Korea. Detailed elucidations of the NHIS cohort design, methods, and validity of the data are presented in previous studies [21]. Briefly, the NHIS is a quasi-government entity that provides mandatory healthcare insurance with a coverage rate of up to 97% of all Korean citizens and is established under the Ministry of Health and Welfare. The NHIS database routinely and prospectively collects individual-level demographic characteristics, results of health screenings, medical treatment records, medication prescription records, and lifestyle behaviors, and undergoes quality control before being released for research purposes.
We enrolled 7,629,948 participants without alcohol consumption (<1 time/week) who underwent two consecutive biennial health screening examinations of the NHIS between 2009–2010 and 2011–2012. We excluded participants with death before January 1, 2013, diagnosis of HCC before January 1, 2013, prior history of other competing liver diseases (alcohol-related liver disease, toxic liver disease, hepatic failure, chronic hepatitis B or C virus infection, chronic hepatitis not elsewhere classified, liver cirrhosis, other inflammatory liver diseases, and other diseases of the liver; Supplementary Table 1), aged under 20 years, missing information for the covariates, and missing information for the evaluation of steatotic liver disease status (Fig. 1). Finally, 5,080,410 non-drinking adult men and women comprised the analytic cohort for the follow-up investigation against HCC. This study was conducted in accordance with both the Declarations of Helsinki and Istanbul. The institutional review board of Seoul National University Hospital approved this study (No. E-2108-136-1246). Informed consents were exempted because the NHIS database is strictly anonymized according to the Personal Data Protection Act. This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (https://www.equator-network.org/reporting-guidelines/strobe/).
Flow diagram of study participants selected from the Korea National Health Insurance Service database.
Classification of change in MASLD status
At each health screening period, the fatty liver index (FLI) was calculated for each participant using the following formula:
x=0.953×loge(serum triglycerides)+0.139×(BMI)+0.718 ×loge(serum GGT)+0.053×(waist circumference)-15.745
The FLI efficiently identifies NAFLD in European and Asian populations, and previous studies have also adopted FLI in the operational definition of steatotic liver disease status [22-25]. MASLD was defined as steatotic liver disease (FLI ≥60) [26] and the presence of at least one of the following cardiometabolic risk factors: body mass index (BMI) ≥23 kg/m2 or waist circumference ≥90 cm (for men) and ≥85 cm (for women) [27], fasting serum glucose ≥100 mg/dL or a history of antidiabetic drug prescription or type 2 diabetes, blood pressure ≥130/85 mm Hg or a history of antihypertensive drug prescription, triglycerides ≥150 mg/dL or a history of lipid-lowering drug prescription, and high-density lipoprotein cholesterol ≤40 mg/dL (for men) and ≤50 mg/dL (for women) [20].
We created categories as follows: (1) No MASLD at both health screening periods (persistent non-MASLD; no MASLD to no MASLD), (2) MASLD at the first health screening and no MASLD at the second health screening (resolved MASLD; MASLD to no MASLD), (3) no MASLD at first health screening to MASLD at second health screening (incident MASLD; no MASLD to MASLD), and (4) MASLD at both health screening periods (persistent MASLD; MASLD to MASLD). The first and second health screenings were carried out between 2009–2010 and 2011–2012, respectively.
Follow-up for HCC
The baseline period for data collection was 2011–2012, and the past MASLD status was backtracked by collecting data from 2009 to 2010. We collected medical treatment claims data from the NHIS to identify HCC events during the follow-up investigation from January 1, 2013, to December 31, 2020. We used the International Classification of Diseases, 10th Revision (ICD-10) code C22.0 and the critical condition code for cancer, as defined previously [28].
Key variables for adjustment and subgroup analyses
Socioeconomic factors, including age (continuous; years), sex (categorical; men and women), and household income (categorical; 1st, 2nd, 3rd, and 4th quartiles), health examination results, including body mass index (continuous; kg/m2), systolic blood pressure (continuous; mmHg), and fasting serum glucose (continuous; mg/dL), lifestyle behaviors, including cigarette smoking (categorical; never, past, and current) and moderate-to-vigorous physical activity (MVPA; categorical; none, 1–2 times/week, 3–4 times/ week, and ≥5 times/week), drug prescriptions (defined as history of specified drug prescriptions within 3 years before the date of follow-up investigation began; Supplementary Table 2), including antihypertensive medication (categorical; yes and no), antidiabetic medication (categorical; yes and no), antidyslipidemic medication (categorical; yes and no), aspirin (categorical; yes and no), acetaminophen (categorical; yes and no), and non-steroidal anti-inflammatory drugs (NSAIDs) (categorical; yes and no), and advanced fibrosis (categorical; yes and no) were included for the adjustments. Advanced fibrosis was defined as the BMI, aspartate aminotransferase/alanine aminotransferase ratio, and diabetes mellitus (BARD) score ≥2. The BARD score is calculated as follows: BMI ≥28 kg/m2=1 point, aspartate aminotransferase/alanine aminotransferase ratio ≥0.8=2 points, and diabetes mellitus=1 point [29].
Statistical analysis
Beginning from January 1, 2013, all participants were followed until the date of HCC or death, or December 31, 2020, whichever came earliest. Characteristics of participants were calculated by n (%) and mean (standard deviation, SD) for categorical and continuous variables, respectively. The crude rate (i.e., incidence) was computed based on the number of total HCC events per 100,000 person-years in each group according to evolutionary changes in MASLD status. Adjusted hazard ratio (aHR) and 95% confidence interval (CI) were calculated using the Cox proportional hazards model through cause-specific analyses. The first model was adjusted for age and sex. We then developed a second adjustment model using age, sex, household income, BMI, systolic blood pressure, fasting serum glucose, cigarette smoking, exercise frequency, and the Charlson comorbidity index (CCI). In addition, the final full adjustment model was further adjusted for antihypertensive medication, antidiabetic medication, antidyslipidemic medication, aspirin, acetaminophen, NSAIDs, and advanced fibrosis.
Sensitivity analyses were performed after excluding events that occurred within 1, 3, and 5 years since the date of the follow-up investigation. We also conducted competing risk analysis using the Fine-Gray model to support primary findings by treating death (n=252,061) or liver transplantation (n=241) as competing risks. The proportional hazards assumption was not violated for the evolutionary changes in MASLD status based on the Kolmogorov-type supremum test (P=0.346). Graphical visualization was carried out using the cumulative incidence function for the incidence of HCC according to the evolutionary change in MASLD status. Subgroup analyses were carried out after stratifying participants according to the known risk factors for HCC. All data mining, collection, and statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, USA). P-values of less than 0.05 were considered statistically significant for all analyses.
RESULTS
Descriptive characteristics
Among 5,080,410 participants, the mean age was 51.7 years (SD, 14.2; Table 1). The mean BMI and waist circumferences were 26.4 kg/m2 (SD, 2.8) and 87.1 cm (SD, 7.3), respectively, in participants with persistent MASLD. Approximately half of the participants with persistent MASLD were physically inactive (n=837,300; 51.4%; no MVPA) and 675,090 participants (41.5%) had no comorbidities (CCI=0). Of the 4 different groups stratified by the evolutionary changes in MASLD status, BMI and waist circumference showed an increasing tendency from persistent nonMASLD to resolved, incident, and persistent MASLD (P<0.001). The proportions of men and former or current smokers were higher in participants with persistent MASLD than in those with persistent non-MASLD (P<0.001). In addition, those with persistent MASLD also had higher blood pressure, triglycerides, alanine aminotransferase, and γ-glutamyl transpeptidase but lower high-density lipoprotein cholesterol levels in a group-dependent manner (P<0.001).
Descriptive characteristics of the participants according to evolutionary changes in MASLD status
Changes in MASLD status and the risk of HCC
Overall, 4,801 new HCC cases were identified during 39,910,331 person-years of follow-up. The crude rate was approximately 2.2-, 2.3-, and 4.7-fold higher in participants with resolved, incident, and persistent MASLD than those with persistent non-MASLD. In addition, persistent MASLD had the highest risk of HCC, followed by incident MASLD and resolved MASLD, compared to persistent non-MASLD (Table 2). After adjustments were made for confounding factors, persistent MASLD (aHR, 2.94; 95% CI, 2.68–3.21; P<0.001), incident MASLD (aHR, 1.85; 95% CI, 1.63–2.10; P<0.001), and resolved MASLD (aHR, 1.33; 95% CI, 1.17–1.50; P<0.001) revealed higher risks of HCC compared to persistent non-MASLD. When setting each of resolved, incident, and persistent MASLD as a reference in the intergroup analyses with full adjustments, the risk of HCC was significantly increased in the order of resolved (lowest), incident (middle), and persistent (highest) MASLD (Supplementary Table 3).
Association of evolutionary changes in MASLD status with the risk of hepatocellular carcinoma
Figure 2 shows biennial numbers of HCC events for the evolutionary changes in MASLD. The curves are located at the top and the bottom for persistent MASLD and persistent non-MASLD, respectively, while the curves of resolved and incident MASLD groups are located in the middle (Fine and Gray’s P<0.001).
Cumulative incidence function according to the evolutionary changes in MASLD status. MASLD, metabolic dysfunctionassociated steatotic liver disease.
Sensitivity analyses
In the sensitivity analyses, the results were similar to the primary findings (Supplementary Table 4). However, in the analysis that was carried out after excluding events that occurred within 5 years, resolved MASLD (aHR, 1.20; 95% CI, 0.99–1.46) did not have an increased risk of HCC compared to persistent non-MASLD. In the competing risk analysis, resolved, incident, and persistent MASLD were associated with higher risks of HCC compared to persistent non-MASLD (Supplementary Table 5).
Stratified analyses
The study participants were stratified by age, obesity, smoking, and CCI (Fig. 3). Consistently, the risk of HCC was highest in persistent MASLD followed by incident MASLD and resolved MASLD as compared to persistent non-MASLD regardless of stratification subgroups. While both incident and resolved MASLD generally revealed a higher risk of HCC, obese participants with resolved MASLD and incident MASLD did not significantly increase the risk of HCC compared to persistent non-MASLD.
A forest plot on the impact of evolutionary changes in MASLD status on the risk of HCC stratified by risk factors for HCC. Data are adjusted hazard ratio (95% confidence interval) calculated using the Cox proportional hazards model after adjustments for baseline fatty liver index, age, sex, household income, body mass index, systolic blood pressure, fasting serum glucose, cigarette smoking, exercise frequency, CCI, antihypertensive medication, antidiabetic medication, antidyslipidemic medication, aspirin, acetaminophen, NSAIDs, and advanced fibrosis. MASLD, metabolic dysfunction-associated steatotic liver disease; CCI, Charlson comorbidity index; NSAIDs, non-steroidal anti-inflammatory drugs.
When stratified by drug prescription, no significant interaction was found for antihypertensive medication, antidyslipidemic medication, aspirin, acetaminophen, and NSAIDs (Supplementary Table 6). On the contrary, a significant interaction effect was found for antidiabetic medication (P for interaction<0.001); in the incident MASLD and persistent MASLD groups, participants with a prescription history of antidiabetic medication had even higher risks of HCC than those without. When stratifying the participants with resolved MASLD, incident MASLD, and persistent MASLD according to the presence of advanced fibrosis (BARD≥2), those with advanced fibrosis were associated with a higher risk of HCC in the incident and persistent MASLD groups (Supplementary Table 7).
DISCUSSION
In this Korean nationwide population-based cohort study, we provided robust real-world evidence that evolutionary changes in MASLD status are significantly associated with the risk of HCC. Both persistent and incident MASLD were associated with a higher risk of developing HCC than those with persistent non-MASLD. Even patients with a history of MASLD, who no longer had MASLD at the second health screening, had an increased risk of HCC. In this context, we need to develop a refined screening and surveillance program for HCC in participants with resolved or incident MASLD.
NAFLD has now emerged as the leading cause of liver-related morbidity worldwide [30]. NAFLD-related cirrhosis is deemed an evident risk factor for HCC. However, even NAFLD patients without evidence of cirrhosis may occasionally develop HCC, and the TERT promoter mutation is most commonly observed in NAFLD-related HCC, implicating that such a population at risk of HCC may be distinct from other high-risk groups for HCC such as viral hepatitis or liver cirrhosis [31]. Furthermore, genetic mutations are increasingly accumulated in both cancerous and noncancerous tissues of the liver obtained from patients with NAFLD regardless of fibrosis progression [32]. In the current study, participants with resolved MASLD retained a higher risk of HCC compared to those with persistent non-MASLD, suggesting that those with resolved MASLD may be at the residual risk of HCC despite lifestyle modifications or therapeutic interventions.
Current guidelines suffer from limited data regarding the selection of the target population with NAFLD to undergo HCC surveillance and the optimal frequency of monitoring HCC among NAFLD patients without NASH or cirrhosis [33]. Therefore, the current MASLD definition, accompanied by steatotic liver disease and cardiometabolic risk factors, may provide additional information [20]. In the current study, participants with resolved MASLD had a lower risk of HCC compared to those with persistent MASLD, and individuals with persistent non-MASLD had a lower risk of HCC compared to those with incident MASLD. In this context, we should provide more intensive care for patients with MASLD in order to reduce the risk of HCC as secondary prevention. Importantly, it is more cost-effective and easily attainable to prevent incident MASLD through preemptive measures, such as physical activity and dietary intervention, ultimately lowering the risk of HCC as primary prevention.
The underlying mechanisms of HCC arising in liver cirrhosis are characterized by repeated hepatocellular death and subsequent regeneration, accompanied by continual cell growth and proliferation that favor the ultimate development of HCC [34]. However, the mechanism of NAFLD-related hepatocarcinogenesis is more likely associated with the pathogenesis of hepatic steatosis per se than that of advanced fibrosis or cirrhosis alone, which requires further elucidation [35]. To date, NAFLD-related hepatocarcinogenesis may be driven by adipose tissue-derived inflammation, changes in hormones, lipotoxicity, oxidative stress, gut dysbiosis, and genetic factors, which are of increasing importance [36-42]. As an advanced status of NAFLD, NASH-related HCC currently lacks a cost-effective surveillance program for HCC, leading to the diagnosis of HCC at an advanced stage, and is considered less responsive to immunotherapy targeted at programmed death-1 [43]. In addition, the defenses against ferroptosis were found to be ultimately surpassed by lipid peroxidation in MASLD and metabolic dysfunction-associated steatohepatitis, as indicated by the existence of ferroptosis executors in hepatocytes and sinusoidal cells, the decrease in polyunsaturated fatty acids in membrane phospholipids, the increase in lysophosphatidylcholine, and the elevation in breakdown products of ferroptosis, thus generating a proferroptotic environment that contributes to the development of HCC [44]. Therefore, preventive strategies stratified according to the changes in MASLD status may be a novel approach to lower the disease burden of MASLD-related HCC.
The strength of the current study is to reveal the association of the evolutionary change in MASLD with HCC risk in adults using a nationwide population-based database with repeated measurements for the evaluation of the change in MASLD status. Ascertainment of an HCC event was made by the medical claims record, which was collected at a nationwide level, and its accuracy is deemed high along with the critical condition code for cancer. However, the current study has several limitations. First, the evolutionary change in MASLD status was defined using the FLI. There is a chance of misclassification when diagnosing MASLD using noninvasive surrogate markers. The NHIS database lacks information on the results of liver biopsy and imaging tests, such as ultrasound and computed tomography. Therefore, further studies with histological examination or imaging modalities are warranted to evaluate the evolutionary change in MASLD status in relation to the risk of HCC. Second, additional information on potential confounders, such as dietary habits and genetic variants, was not available in the NHIS database. Third, the health screening data had neither information on the presence of liver fibrosis nor platelet counts that are required for the calculation of the fibrosis-4 index, which led us to adopt the BARD score for the operational definition of advanced fibrosis. The occurrence of HCC was followed up through the ICD-10 code for HCC in the NHIS database, thus there might be interval censoring. Lastly, the generalizability of our results is limited to Korean adults who received health screening from the NHIS. More evidence from other ethnic or multi-ethnic population-based cohorts is needed.
Given the apparent association of the evolutionary change in MASLD with the risk of HCC, a refined HCC surveillance program incorporating the evolutionary changes in MASLD may aid in reducing the future risk of HCC. Especially, patients with resolved MASLD still have a residual risk of HCC, thus requiring optimal screening and preventive strategies against HCC.
Notes
Authors’ contribution
Seogsong Jeong (Conceptualization: Equal; Data curation: Lead; Formal analysis: Lead; Methodology: Equal; Visualization: Lead; Writing – original draft: Lead; Writing – review & editing: Lead). Yun Hwan Oh (Investigation: Supporting; Methodology: Equal; Writing – review & editing: Supporting). Joseph C Ahn (Investigation: Supporting; Methodology: Equal; Writing – review & editing: Supporting). Seulggie Choi (Data curation: Supporting; Formal analysis: Supporting; Investigation: Supporting; Writing – review & editing: Supporting). Sun Jae Park (Data curation: Supporting; Formal analysis: Supporting; Investigation: Supporting; Writing – review & editing: Supporting). Hye Jun Kim (Data curation: Supporting; Investigation: Supporting; Writing – review & editing: Supporting). Gyeongsil Lee (Investigation: Supporting; Methodology: Equal; Writing – review & editing: Supporting). Joung Sik Son (Investigation: Supporting; Methodology: Equal; Writing – review & editing: Supporting). Heejoon Jang (Investigation: Supporting; Methodology: Equal; Funding acquisition: Supporting; Writing – review & editing: Supporting). Dong Hyeon Lee (Investigation: Supporting; Methodology: Equal; Funding acquisition: Suppor ting; Writing – review & editing: Supporting). Meng Sha (Investigation: Supporting; Methodology: Supporting; Writing – review & editing: Equal). Lei Chen (Investigation: Supporting; Methodology: Supporting; Writing – review & editing: Equal). Won Kim (Conceptualization: Equal; Investigation: Equal; Methodology: Equal; Supervision: Lead; Funding acquisition: Lead; Writing – review & editing: Lead). Sang Min Park (Conceptualization: Equal; Investigation: Equal; Methodology: Equal; Supervision: Lead; Funding acquisition: Lead; Writing – review & editing: Lead).
Conflicts of Interest
The authors have no conflicts to disclose.
Acknowledgements
This work was supported by the MSIT (Ministry of Science and ICT), Korea, under the ICAN (ICT Challenge and Advanced Network of HRD) support program (IITP-2024- RS-00156439) supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2021R1F1A 1063346, 2021R1A2C2005820, 2021M3A9E4021818, and RS-2023-00237783), the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (HI21C0538), the Korea National Institute of Health (KNIH) research project (2022ER090202), and the SNUH Research Fund (04-2021-0370).
Abbreviations
HCC
Hepatocellular carcinoma
NAFLD
Nonalcoholic fatty liver disease
HBV
Hepatitis B virus
HCV
hepatitis C virus
MASLD
Metabolic dysfunction-associated steatotic liver disease
NHIS
National Health Insurance Service
FLI
Fatty liver index
MVPA
moderate-to-vigorous physical activity
NSAIDs
non-steroidal anti-inflammatory drugs
BMI
body mass index
BARD
body mass index
IQR
interquartile range
aHR
adjusted hazard ratio
CI
confidence interval
CCI
Charlson comorbidity index
SUPPLEMENTAL MATERIAL
Supplementary material is available at Clinical and Molecular Hepatology website (http://www.e-cmh.org).
Definition of exclusion criteria in the Korea National Health Insurance Service database
Definition of drug prescriptions based on Korea drug codes in the Korea National Health Insurance Service database
Between-group differences of evolutionary changes in MASLD status for the risk of hepatocellular carcinoma
Sensitivity analysis on the impact of evolutionary changes in MASLD status on the risk of hepatocellular carcinoma after excluding events that occurred within specified latent periods
Competing risk analysis on the impact of evolutionary changes in MASLD status on the risk of hepatocellular carcinoma
Stratified analyses on the association of evolutionary changes in MASLD status with the risk of hepatocellular carcinoma according to the use of medications
Association of the advanced fibrosis (BARD≥2) with the risk of hepatocellular carcinoma
References
Article information Continued
Notes
Study Highlights
• Evolutionary alterations, including persistent non-metabolic dysfunction-associated steatotic liver disease (MASLD), resolved MASLD, incident MASLD, and persistent MASLD, were linked to varying hepatocellular carcinoma risks independent of metabolic risk factors and concomitant medications, offering enhanced insight into hepatocellular carcinoma risk stratification among MASLD patients.