Clin Mol Hepatol > Volume 30(3); 2024 > Article
Tsai, Huang, Yeh, Hsieh, Kuo, Hung, Tseng, Lai, Peng, Wang, Chen, Lee, Chien, Yang, Lo, Kao, Liu, Liu, Yan, Lin, Su, Chu, Chen, Tung, Tai, Lin, Lo, Cheng, Chiu, Wang, Cheng, Tsai, Lin, Huang, Chen, Huang, Dai, Chung, Bair, Yu, and T-COACH Study Group: Metformin and statins reduce hepatocellular carcinoma risk in chronic hepatitis C patients with failed antiviral therapy

ABSTRACT

Background/Aims

Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients.

Methods

We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development.

Results

Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients.

Conclusions

Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Graphical Abstract

INTRODUCTION

Hepatitis C virus (HCV) infection is a major public health concern, because it frequently leads to liver cirrhosis (LC) and hepatocellular carcinoma (HCC), which impose significant burdens on many countries [1]. HCV treatment has changed from interferon-based therapies to direct-acting antivirals (DAAs), with significant improvements in sustained virological response (SVR) rates [2]. Achieving SVR through anti-HCV therapy greatly reduces the risk of HCC, liver failure [3], and liver-related mortality [4].
The risk of HCC can be reduced but cannot be eliminated completely, even after successful antiviral therapy [5], particularly among patients with persistent advanced fibrosis, insulin resistance, and diabetes mellitus (DM), as well as among the elderly [6-8]. Moreover, patients in whom antiviral therapy fails are still at a high risk of developing HCC, especially those with advanced fibrosis and DM [9].
Chronic hepatitis C (CHC) has been associated with an increased risk of DM [10], and the comorbidity of DM increases the risk of developing HCC in patients with CHC [11]. Metformin use has been associated with a reduced risk of HCC compared with other oral hypoglycemic agents (OHAs) or insulin among patients with DM [12]. We previously showed that metformin use in DM significantly reduces the risk of HCC in patients with CHC after successful antiviral therapy [13].
Statin use has been associated with reduced development of cirrhosis and incidence of HCC, which is mainly observed in patients receiving lipophilic statins [14]. Although the chemopreventive effects of metformin in patients with DM and statins in patients with hyperlipidemia (HLP) reduce the risk of HCC in patients with CHC, which has been proven after achieving SVR [13], the impact on HCC risk reduction remains unclear in patients with CHC who have failed antiviral therapy.
The current study aimed to assess the impact of metformin for DM and/or statins for HLP on the risk of HCC among CHC patients in who failed antiviral therapy. The findings of this study will improve our understanding of the potential benefits of chemoprevention in reducing the risk of HCC in patients with difficult-to-cure CHC.
The study was approved by the institutional review boards of Kaohsiung Medical University Hospital (KMUHIRB-E(I)-20210378) and was conducted in accordance with the Declaration of Helsinki and the ethical guidelines. All participants provided written informed consent.

MATERIALS AND METHODS

Study population

The study included patients aged ≥20 years who were diagnosed with CHC either through liver histology or by testing positive for anti-HCV or HCV RNA for > six months. These patients were drawn from a large-scale, multicenter cohort in Taiwan (Taiwanese Chronic Hepatitis C Cohort, T-COACH) and had undergone antiviral interferon-based therapy for at least four weeks since 2003.
We excluded patients who lacked virological outcome data, achieved SVR, had coinfection with human immunodeficiency virus or hepatitis B virus (HBV), died within six months of end-of-treatment (EOT), and developed HCC within 1.5 years after EOT. Finally, the analysis focused on 2,779 patients with CHC who experienced antiviral therapy failure (Fig. 1).

Independent variables

Data collected on the independent variables included: 1) demographic characteristics: age, sex, and body mass index (BMI); 2) medical history: DM, HLP, and hypertension (HTN); 3) laboratory data: AST, ALT, platelet count, creatinine, liver fibrosis (FIB-4 score; fibrosis index based on four factors), renal function (estimated glomerular filtration rate, eGFR); and 4) clinical features: renal function impairment (eGFR ≤60), advanced fibrosis (FIB-4 ≥3.25), LC, and sustained virological response (SVR; HCV RNA seronegativity 24 weeks after interferon-based therapy). Related assessments of the liver and renal function were performed accordingly. The FIB-4 score was calculated using age, AST, ALT, and platelet count of the patient: [age (years)×AST(IU/L)]/[platelet (x1,000/μL)×ALT (IU/L)^0.5]. The eGFR was calculated using the patient’s creatinine levels, age, and sex: 186×creatinine (mg/dL)-1.154×age (year)-0.203×0.742 (if female). LC was based on any of the following: liver histology,15 transient elastography (FibroScan®; Echosens, Paris, France) >12 kPa,16 acoustic radiation force impulse >1.98 m/s17, FIB-4 >6.5,18 or the presence of clinical, radiological, endoscopic, or laboratory evidence of cirrhosis and portal hypertension.

Study endpoints and linked databases

The data for the study were obtained from the National Health Insurance Research Database, which covers approximately 26 million Taiwanese people since 1995.
Participants were considered to have DM if they met any of the following criteria: a history of DM on treatment with OHAs with or without insulin, fasting glucose ≥126 mg/dL, or 2-hour plasma glucose ≥200 mg/dL. Patients with a DM diagnosis who had taken metformin for ≥84 days were considered metformin users, whereas those who had taken metformin for <84 days were considered metformin nonusers after six months of EOT. Participants were considered to have HLP if they had a history of HLP and used medication. Diagnosed HLP statin users were defined as patients with an HLP diagnosis who had taken statins for ≥84 days, whereas those who had taken statins for <84 days were considered HLP statin non-users after six months of EOT.
All diseases, including HCC and liver transplant (LT), were identified using specific codes from the International Classification of Diseases, 9th or 10th revision (ICD-9-CM and ICD-10). In this study, the occurrence of HCC was determined based on data from the Cancer Registry, whereas the LT cases were identified from the registry of catastrophic illnesses. Information on patient deaths was obtained from the death registry. The relevant medication codes for the diseases were linked to the corresponding entries in the detailed health insurance inpatient/outpatient records (Supplementary Table 1).
New-onset HCC was defined as HCC occurring in patients 1.5 years after antiviral EOT. The follow-up period began 1.5 years after antiviral EOT and continued until the censored events (HCC and death/LT) or December 31, 2019.

Statistical analysis

Continuous variables are presented as mean ± standard deviation, while categorical variables are expressed as numbers (percentages). Chi-square was used to compare subgroups with categorical parameters, and Student’s t-test was used for continuous parameters, as appropriate.
Person-years were calculated as the number of years that each participant contributed to the study from 1.5 years after EOT to the date of the first diagnosis of HCC, death/LT, or December 31, 2019, whichever occurred first. The annual incidence of HCC was calculated as the number of new-onset HCC cases divided by the sum of person-years and the groups were compared by Poisson method.
The study considered death or LT as competing events, meaning that patients who died or underwent LT before developing HCC were no longer at risk of developing HCC. To account for this, the study modified the Kaplan-Meier method using Gray’s cumulative incidence method [19]. Cox proportional hazard regression was used to calculate sub-distribution hazard ratios (SHRs) [20] for HCC development before and after adjusting for various factors such as age, sex, LC, HCV genotype (GT), HCV RNA and aspirin use. In addition, we compared the cumulative incidence of new-onset HCC between subgroups by stratifying the patients according to their LC status.
Sensitivity analyses were conducted to ensure robustness of the findings. First, advanced fibrosis was substituted with LC to validate the robustness of the results in the multivariate analysis. Second, in this study, participants were defined as metformin users when they used metformin six months after EOT. Patients who used metformin either before or during antiviral therapy were classified as metformin non-users. To strengthen our findings, we reclassified previous metformin users to confirm the effect of metformin on the risk of new-onset HCC in patients with DM. A similar approach was employed for HLP statin users. Third, to avoid potential bias related to specific clinical scenarios including treatment by DAA for IFN-failed patients or patients with diabetes and severe renal impairment (eGFR <30) who are typically not candidates for metformin therapy, we conducted further analysis to validate our findings. All statistical analyses were performed using SAS Enterprise Guide, and P-values less than 0.05 were considered statistically significant.

RESULTS

Patient characteristics

The clinical characteristics of the 2,779 CHC patients who failed antiviral therapy are presented in Table 1. The mean age of the patients was 56.1±10.7 years, mean log-transformed HCV RNA levels were 6.1±0.9, 52.7% were female, 34.7% had advanced fibrosis (FIB-4 ≥3.25), 16.2% had liver cirrhosis, 6.7% had an eGFR <60 mL/min/1.73m2, and 63.1% were infected with HCV GT1. Furthermore, 17.6% of the patients were obese (BMI ≥27), 22.3% had DM, 11.3% had HTN, and 21.8% had HLP. Among the patients with DM, 53.5% were metformin users. Among patients with HLP, 82.5% were statin users. In addition, 10.4% of the patients were aspirin users. Overall, 238 (8.6%) patients died before the development of HCC and 480 (17.3%) developed new-onset HCC during a total of 18,668 person-years of follow-up (median: 6.6 years). The annual incidence of HCC was 257.1 cases per 10,000 person-years (Table 1).

HCC risk between patients with/without DM and on/not on metformin

Of the 2,779 CHC patients in whom antiviral therapy failed, 620 (22.3%) had DM. After a median follow-up of 7.27 years, 65 died before HCC developed, and 125 developed HCC (annual incidence: 277.1 per 10,000 person-years). For the other 2,159 (77.7%) patients without DM, 173 died before HCC developed, and 355 developed HCC (annual incidence: 250.8 per 10,000 person-years) after a median follow-up of 6.56 years. The 5-year cumulative incidence rate of HCC was not significantly different between patients with and without DM (9.3% vs. 11.3%, Gray’s P=0.419) (Fig. 2A). Notably, patients with DM who were not on metformin showed a significant increase in the risk of HCC compared to metformin users (annual incidence: 408.9 per 10,000 person-years in metformin non-users vs. 200.1 per 10,000 person-years in metformin users, P<0.001, Table 1). The 5- and 10-year cumulative incidence rates of HCC were 11.3% and 21.6%, respectively, in non-DM patients; 3.1% and 19.6%, respectively, in DM metformin users; and 16.5% and 28.6%, respectively, in DM metformin non-users. HCC risk was significantly higher in metformin non-users than in metformin users (adjusted sub-distribution hazard ratio (aSHR=1.59, 95% CI=1.07–2.36, P=0.022) and in patients without DM (aSHR=1.51, 95% CI=1.12–2.04, P=0.007). However, there was no difference in HCC risk between metformin users and patients without DM (aSHR=1.05, 95% CI=0.76–1.44, P=0.763) (Fig. 2).

HCC risk between patients with/without HLP and on/not on statins

Of 606 patients with HLP, 31 died before HCC developed, and 61 developed HCC after a median follow-up of 7.64 years (annual incidence: 131.8 per 10,000 person-years). Of the 2,173 patients without HLP, 207 died before HCC developed, and 419 developed HCC (annual incidence: 298.4 per 10,000 person-years) after a median follow-up of 6.46 years. The 5-year cumulative incidence rate of HCC was significantly lower in patients with HLP than in those without HLP (4.8% vs. 12.5%, Gray’s P<0.001). After further stratification by statin use in HLP patients, the annual incidences were 220.8 per 10,000 person-years in statin non-users vs. 117.7 per 10,000 person-years in statin users (P=0.036, Table 1). The 5-year cumulative incidence rates of HCC were 12.5%, 3.8%, and 10.1% in patients without HLP, HLP statin users, and HLP statin non-users, respectively. The HCC risk was significantly lower in HLP statin users than in patients without HLP (3.8% vs. 12.5%; aSHR=0.50, 95% CI=0.36–0.68, P<0.001), but there was no difference between patients with HLP who were statin non-users and those who did not (Fig. 3).

Factors associated with HCC risk

After accounting for death as a competing risk, univariate Cox regression analysis showed that being elderly (≥65 years), female, having DM without metformin use, HCV GT1, high AST, high ALT, advanced fibrosis and LC were independently associated with a higher risk of HCC, while aspirin use, HLP statin use and low HCV viral load were associated with a significantly lower risk of HCC. In multivariate analysis, the significant factors associated with increased HCC risk were LC (aSHR=2.27, 95% CI=1.81–2.85), elderly (≥65 years; aSHR=1.89, 95% CI=1.52–2.36), HCV GT1 (aSHR=1.30, 95% CI=1.04–1.63) and DM without metformin use (vs. no DM; aSHR=1.51, 95% CI=1.12–2.04). Conversely, patients with HLP who were on statins had a significantly lower risk of HCC than those without HLP (aSHR=0.50, 95% CI=0.36–0.68) (Table 2). Aspirin use also exhibited a significantly lower HCC risk than non-aspirin use (aSHR=0.71, 95% CI=0.51–1.00, P=0.049) (Supplementary Fig. 1A).

Subgroup analysis

LC is the most significant risk factor for HCC. Therefore, we stratified the patients according to their cirrhosis status to evaluate the impact of metformin or statin use among different subgroups.
Among patients without LC, the 5-year cumulative incidence rates of HCC were 9.2%, 3.0%, and 13.5% among those without DM, metformin users, and metformin nonusers, respectively. The HCC risk was significantly higher in DM metformin non-users than in patients without DM, with an aSHR of 1.73 (95% CI=1.24–2.40, P=0.001) and in patients with DM on metformin, with an aSHR of 1.71 (95% CI=1.11–2.63, P=0.014) (Fig. 4A). No significant differences were observed between metformin users and patients without DM. Among patients with LC, the 5-year cumulative incidence of HCC was 23.3%, 3.6%, and 25.1% in patients without DM, metformin users, and metformin non-users, respectively. However, the difference in HCC risk between metformin non-users and the other two groups was not significant (Fig. 4B).
Among patients without LC, the 5-year cumulative incidence rates of HCC were 10.4%, 3.1%, and 6.1% in patients without HLP, in HLP statin users, and in HLP statin non-users, respectively. The HCC risk was significantly lower in HLP statin users than in patients without HLP, with an aSHR of 0.43 (95% CI=0.30–0.61, P<0.001), while there was no difference in HCC risk between HLP statin users and HLP statin non-users (Fig. 5A). Among patients with LC, the 5-year cumulative incidence of HCC was 22.8%, 8.4%, and 30.5% in patients without HLP, HLP statin users, and HLP statin non-users, respectively. HCC incidence was significantly lower in HLP statin users than in patients without HLP (aSHR=0.47, 95% CI=0.26–0.85, P=0.012) and HLP statin non-users (aSHR=0.35, 95% CI=0.14–0.91, P=0.032), whereas there was no difference in HCC risk between patients without HLP and HLP statin non-users (Fig. 5B).
The aspirin use was not associated with a lower risk of HCC in the subgroup of non-LC (aSHR=0.76, 95% CI=0.53–1.08, P=0.122, Supplementary Fig. 1B) and LC (aSHR=0.68, 95% CI=0.39–1.18, P=0.167, Supplementary Fig. 1C).

Sensitivity analysis

Four sensitivity analyses were conducted to validate the robustness of the main findings and enhance the results.

Assessment of outcomes with metformin or statin use before or after the end-of-antiviral therapy

To avoid underestimating the duration of metformin or statin use, we redefined metformin or statin use, either before or after EOT. The 5-year cumulative incidence rate of HCC was higher in patients taking metformin before or after EOT, with rates of 11.1%, 8.1%, and 29.7% in patients without DM, metformin users, and metformin non-users, respectively. HCC risk remained significantly higher in DM metformin non-users than in DM metformin users (aSHR=2.28, 95% CI=1.48–3.46, P<0.001) or patients without DM (aSHR=2.45, 95% CI=1.95–4.24, P<0.001) (Supplementary Fig. 2A). The 5-year cumulative incidence of HCC was higher in patients with HLP on statins before or after EOT, with rates of 12.7%, 5.1%, and 12.7% in patients without HLP, HLP statin users, and HLP statin non-users, respectively. HCC risk remained significantly lower in HLP statin users than in patients without HLP (aSHR=0.43, 95% CI=0.34–0.63, P<0.001) (Supplementary Fig. 2B). The results were consistent between groups using different definitions of metformin or statin use.

Outcomes using advanced fibrosis as the critical variable

We used another level of liver fibrosis, advanced fibrosis (FIB-4 score >3.25), to validate our findings. In multivariate analysis, HCC risk was significantly higher in patients with advanced fibrosis than in those without advanced fibrosis (aSHR=3.01, 95% CI=2.45–3.64, P<0.001, see Supplementary Table 2). The predicted model showed that DM metformin non-users continued to have a significantly higher risk of HCC compared to patients without DM (aSHR=1.54, 95% CI=1.16–2.03, P=0.005) and DM metformin users (aSHR=1.60, 95% CI=1.13–2.85, P=0.013). The HCC risk was significantly lower in patients with HLP on statins than in patients without HLP (aSHR=0.47, 95% CI=0.34–0.67, P<0.001). The results of LC and advanced fibrosis models were consistent.

Minimize potential bias related to specific clinical conditions

To avoid potential bias related to specific clinical scenarios including treatment by DAAs for IFN-failed patients or patients with diabetes and severe renal impairment (eGFR <30) who are typically not candidates for metformin therapy, we conducted further analysis to validate our findings.
After excluding 78 IFN-failed patients who experienced retreatment with DAAs, we found that diabetic patients not treated with metformin had a 1.50-fold increased risk of developing HCC compared to non-diabetic individuals (aSHR=1.50, 95% CI=1.13–1.98, P=0.005) (Supplementary Fig. 3A). Conversely, hyperlipidemia patients who were prescribed statins showed a 55% decrease in HCC risk compared to those without hyperlipidemia (aSHR=0.45, 95% CI=0.33–0.60, P<0.001) (Supplementary Fig. 3B).
Similarly, after removing 49 patients with eGFR<30, the risk of HCC in diabetic patients not treated with metformin was found to be 1.56-fold higher than that in non-diabetics (aSHR=1.56, 95% CI=1.18–2.07, P=0.002, Supplementary Fig. 4A). Hyperlipidemia patients on statin therapy had a 55% decreased risk of HCC compared to those without hyperlipidemia (aSHR=0.45, 95% CI=0.33–0.60, P<0.001, Supplementary Fig. 4B).
Taken together, our findings from the current study were consistent across these sensitivity analyses.

Interaction of statin and metformin

In this study, statin non-users had a 2.42-fold higher risk of HCC compared to statin users among metformin non-users, and a 2.23-fold higher risk among metformin users. Whereas, there was no significant difference in HCC risk between metformin non-users and metformin users, both among statin non-users and statin users. Consequently, our analysis did not reveal a significant interaction between statins and metformin in predicting HCC risk (P=0.82, Supplementary Fig. 5).

DISCUSSION

Of the 2,779 CHC patients, 480 (17.3%) developed new-onset HCC and 238 (8.6%) died after antiviral therapy. Patients with DM but no metformin use had a 1.51-fold higher risk of HCC than patients without DM, whereas HCC risk was comparable between patients without DM and those with DM on metformin. The 5-year cumulative HCC incidence (16.5%) was significantly higher in metformin nonusers than in those without DM (11.3%, P=0.007) and metformin users (3.1%, P=0.022). Conversely, patients with HLP who used statins had a 50% lower risk of HCC than those without HLP (5-year cumulative HCC incidence: 3.8% vs. 12.5%, P<0.001). Notably, the unfavorable effect of metformin non-use on increased HCC risk was mainly observed among patients without LC but not among patients with LC. In contrast, a favorable effect of statins on reducing the risk of HCC was observed in patients with and without LC.
HCV infection has been linked to lower lipid profiles, and when a patient with CHC achieves SVR, their lipid profiles may worsen, potentially leading to cardiocerebral events [21-23]. For patients with CHC, DM or HLP, treatment with the antidiabetic agent metformin and cholesterol-lowering statin is commonly used. Several studies have investigated the association between statin use and HCC risk in patients with CHC. Statins are well-known for their preventive role in many cancers, including liver cancer [24,25]. A meta-analysis of 27 studies found strong evidence of statin-related potential in reducing the risk of HCC [24]. Among patients with CHC, statin use has been associated with improved virological response rates to antiviral therapy [26], decreased liver fibrosis progression, and reduced HCC risk in a dose-dependent manner in both Veteran and Taiwanese insurance cohorts [14,27]. These studies suggested that statin use may have a protective effect against liver cancer in patients with hepatitis C infection. In the present study, we found that statin use reduced the risk of HCC in patients with HLP and CHC after the failure of antiviral therapy.
Several studies have explored the association between metformin use and HCC risk in patients with CHC and DM. A systematic review of 12 studies indicated that metformin might have a protective effect against HCC in patients with DM [12]. A large nationwide Taiwanese study showed that metformin use was linked to a lower HCC risk in a dose-dependent manner in patients with type 2 DM and chronic liver disease [28]. These studies suggested that metformin may exert a protective effect against HCC in patients with CHC and diabetes. Furthermore, our previous study documented that after achieving SVR, LC, and metformin non-use in patients with DM and CHC may result in a higher risk of HCC [13]. Similarly, we also observed a chemopreventive effect of metformin on the risk of HCC development in patients who failed antiviral therapy. Another interesting viewpoint is that among these patients, the HCC risk in the DM metformin use group initially appears lower than in the non-DM group but later aligns with it. This trend implies that the timing and effectiveness of metformin usage may vary. Maybe metformin had a real chemopreventive effect at an earlier period, but it was discontinued later due to progression or uncontrolled diabetes, and the effect faded, resulting in a comparable HCC risk as non-DM. Further validation is needed for these findings.
Our clinical findings revealed that unfavorable DM metformin non-use and favorable HLP statin use were critical in reducing the risk of HCC among patients with CHC after antiviral therapy failed. Several studies have investigated the effects of combination therapy with simvastatin (a statin) and metformin on the growth and migration of different cancer cells, including HBV-related HCC [29] and prostate cancer [30,31]. One study found that simvastatin and metformin inhibited the growth of HBV-related HCC cells by upregulating autophagy [29]. Combining simvastatin with metformin induced G1-phase cell cycle arrest and Ripk1- and Ripk3-dependent necrosis in C4-2B osseous metastatic castration-resistant prostate cancer cells. The synergistic effects of simvastatin and metformin on osseous metastatic castration-resistant prostate cancer cells suggest that this combination may be a promising treatment option for this type of cancer [30,31].
After HCV infection, host factors, such as older age and fibrosis progression leading to LC, appear to be significant in the development of HCC [9,32-34]. Coexisting conditions such as DM, obesity, and co-infection with HBV or HIV may accelerate the development of HCC [35,36]. Conversely, successful antiviral therapy has been associated with a reduced risk of HCC [3,37]. In this study, we observed that older age, advanced fibrosis, and LC were the independent risk factors for HCC. Exploring chemopreventive approaches, such as using favorable HLP statins and unfavorable DM metformin nonuse among patients with CHC in whom antiviral therapy has failed, may present another opportunity to decrease the risk of HCC.
Our study had several limitations that merit attention. Firstly, the specific impact of the duration, dosage, continuity, and timing of metformin and statin use on the incidence of HCC remains to be determined. Secondly, our analysis did not differentiate between the effects of lipophilic and hydrophilic statins, nor did it consider the potential influence of other OHAs such as sulfonylureas, thiazolidinediones, and DPP4 inhibitors on HCC incidence. Thirdly, we had no information on interferon preparations, specifically pegylated interferon α-2a versus α-2b, in this study.
Despite these limitations, which make further analysis challenging, our research offers significant insights in the era of DAAs for a small subset of patients who do not achieve SVR with DAAs [38], are non-compliant with treatment [39], or have contraindications to DAAs [40]. Additionally, this study on the chemopreventive effects of metformin and statins on HCC risk could serve as a benchmark for future research on the long-term risk of HCC among HCV patients and other patients with active liver diseases.
In summary, both metformin for DM and statins for HLP had chemopreventive effects on HCC risk in patients with CHC in whom antiviral therapy failed. These findings underscore the importance of implementing personalized preventive strategies to manage patients with these clinical profiles.

ACKNOWLEDGMENTS

This study was supported by Kaohsiung Medical University with plans: KMU-NSTC 112-2635-B-037-001-MY2, KMU-MOST 111-2314-B-037-069-MY2, and MOHW113-TDU-B-221-134007; Kaohsiung Medical University Hospital with plans: KMUH112-2R09, KMUH111-1R04, and KMUHDK(A)113002; and Taitung Mackay Memorial Hospital with plans: MOST 111-2314-B-195-009-MY2 and TTMMH-111-06. The authors would like to thank the TCOACH investigators who provided the patients for the analysis. All linkage databases were supported by the Health and Welfare Data Science Center of Taiwan. We also thank the Center for Medical Informatics and Statistics of Kaohsiung Medical University for providing administrative support and funding.

FOOTNOTES

Authors’ contribution
Guarantor of the article: Ming-Lung Yu. Conception and design: P.C.T., C.F.H., and M.L.Y. Acquisition of data, analysis and interpretation: P.C.T., C.F.H., M.L.Y, M.H.H, H.T.K, C.H.H., K.C.T., H.C.L., C.Y.P, J.H.W., J.J.C., P.L.L., R. N.C., C.C.Y., G.H.L., J.H.K., C.J.L., C.H.L., S.L.Y, C.Y.L, W.W.S, C.H.C., C.J.C., S.Y.T., C.M.T., C.W.L., C.C.L., P.N.C, Y.C.C., C.C.W., J.S.C., W.L.T., H.C.L., Y.H.H., C.Y.C., J.F.H., C.Y.D., W.L.C., M.J.B., and M.L.Y. Manuscript drafting and critical revising: P.C.T., C.F.H., M.L.B., and M.L.Y. All authors contributed to revision of the final manuscript.
Conflicts of Interest
The authors declare no conflicts of interest in this present study.

SUPPLEMENTAL MATERIAL

Supplementary material is available at Clinical and Molecular Hepatology website (http://www.e-cmh.org).
Supplementary Figure 1.
The impact of aspirin on the incidence of HCC among all population (A), the subgroups of non-LC (B) and LC (C). (A) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, DM/ metformin and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype. (B, C) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, HCV GT1, HCV RNA, DM/metformin and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; GT, genotype.
cmh-2024-0038-Supplementary-Fig-1.pdf
Supplementary Figure 2.
The effects of DM with and without metformin (A) and HLP with and without statin (B) on the new-onset HCC among CHC patients who failed antiviral therapy. Metformin or statin use was redefined as ever metformin or statin use before or after endof- treatment. (A) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and p-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype. (B) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and DM/metformin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype.
cmh-2024-0038-Supplementary-Fig-2.pdf
Supplementary Figure 3.
The impact of DM with and without metformin (A) and HLP with and without statin (B) on the new-onset HCC among CHC patients who failed IFN therapy and did not subsequently receive DAAs treatment (n=2,701). (A) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype. (B) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and Pvalues were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and DM/ metformin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype.
cmh-2024-0038-Supplementary-Fig-3.pdf
Supplementary Figure 4.
The impact of DM with and without metformin (A) and HLP with and without statin (B) on the new-onset HCC after excluding 49 patients with eGFR <30 (n=2,730). (A) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype. (B) aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and DM/metformin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype.
cmh-2024-0038-Supplementary-Fig-4.pdf
Supplementary Figure 5.
Interaction of effects of statin and metformin on the incidence of HCC. aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. SHR, sub-distribution hazard ratio.
cmh-2024-0038-Supplementary-Fig-5.pdf
Supplementary Table 1.
Disease codes (ICD-9-CM/ICD-10) and prescription codes
cmh-2024-0038-Supplementary-Table-1.pdf
Supplementary Table 2.
Cox sub-distribution hazards model for risk factors of HCC development among CHC patients in whom antiviral therapy failed, with liver cirrhosis or advanced fibrosis (FIB-4≥3.25) as the confounding factor
cmh-2024-0038-Supplementary-Table-2.pdf

Figure 1.
Patient enrollment of the cohort. aMedian (quartile 1– quartile 3) was shown. bThe annual incidence of HCC was calculated as new-onset HCC divided by the sum of person-years. CHC, chronic hepatitis C; HCC, hepatocellular carcinoma; HIV, human immunodeficiency virus; HBV, hepatitis B virus.

cmh-2024-0038f1.jpg
Figure 2.
The risk of HCC in CHC patients who failed antiviral therapy between with/without DM (A) and on/not on metformin (B) while considering death as a competing risk. aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype.

cmh-2024-0038f2.jpg
Figure 3.
The risk of HCC in CHC patients who failed antiviral therapy between with/without HLP (A) and on/not on statin (B) while considering death as a competing risk. aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, LC, HCV GT1, HCV RNA, aspirin, and DM/metformin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype.

cmh-2024-0038f3.jpg
Figure 4.
The risk of HCC in CHC patients who failed antiviral therapy between with/without DM and on/not on metformin stratified by baseline liver cirrhosis status: non-LC (A) and LC (B). aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, HCV GT1, HCV RNA, aspirin, and HLP/statin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio; LC, liver cirrhosis; GT, genotype.

cmh-2024-0038f4.jpg
Figure 5.
The risk of HCC in CHC patients who failed antiviral therapy between with/without HLP and on/not on statin stratified by baseline liver cirrhosis status: non-LC (A) and LC (B). aAfter considering death as a competing risk, a Kaplan–Meier plot was constructed using Gray’s cumulative incidence method. bAll SHRs (95% CIs) and P-values were calculated using the Cox sub-distribution hazards method. *Adjusted for age, sex, HCV GT1, HCV RNA, aspirin, and DM/metformin. DM, diabetes mellitus; HLP, hyperlipidemia; HCC, hepatocellular carcinoma; SHR, subdistribution hazard ratio; LC, liver cirrhosis; GT, genotype.

cmh-2024-0038f5.jpg

cmh-2024-0038f6.jpg
Table 1.
The characteristics of CHC patients in whom antiviral therapy failed
Variables All (n=2,779) DM patients
HLP patients
Non-metformin
Metformin
P-value Non-statin
Statin
P-value
(n=288) (n=332) (n=106) (n=500)
Age (years) 56.1±10.7 57.9±9.0 56.4±9.5 0.056 57.6±10.1 56.5±9.7 0.275
 >65 553 (19.9) 64 (22.2) 53 (16.0) 0.047 23 (21.7) 97 (19.4) 0.590
Female 1,464 (52.7) 128 (44.4) 159 (47.9) 0.391 52 (49.1) 250 (50.0) 0.860
BMI (kg/m2) 25.0±3.0 25.9±3.8 25.5±2.8 0.088 26.0±3.2 25.3±3.2 0.041
 ≥27 488 (17.6) 91 (31.6) 68 (20.5) 0.002 33 (31.1) 93 (18.6) 0.004
DM 620 (22.3) - - 38 (35.9) 198 (39.6) 0.472
HTN 315 (11.3) 88 (30.6) 46 (13.9) <0.001 44 (41.5) 71 (14.2) <0.001
HLP 606 (21.8) 92 (32.0) 144 (43.4) 0.004 - - -
Metformin use 332 (12.0) 0 (0.0) 332 (100.0) - 12 (11.3) 132 (26.4) <0.001
 Statin use 500 (18.0) 66 (22.9) 132 (39.8) <0.001 0 (0.0) 500 (100.0) -
Aspirin use 289 (10.4) 35 (12.2) 60 (18.1) 0.041 9 (8.5) 110 (22.0) 0.002
AST (IU/L) 87.6±59.2 90.1±61.9 90.8±52.6 0.883 83.6±48.1 80.0±49.7 0.502
 ≥2X (80) 1,193 (42.9) 127 (44.1) 156 (47.0) 0.471 45 (42.5) 180 (36.0) 0.212
ALT (IU/L) 121.0±92.5 120.5±88.6 132.9±87.0 0.080 115.9±72.4 117.2±82.6 0.875
 ≥ 2X (80) 1,722 (62.0) 173 (60.1) 234 (70.5) 0.007 64 (60.4) 298 (59.6) 0.882
Platelet (x1,000/μL) 164.6±55.7 158.6±72.3 160.7±55.1 0.677 171.2±55.5 172.0±59.1 0.895
Creatinine (mg/dL) 1.00±1.23 1.20±1.70 0.92±0.75 0.007 1.05±1.12 1.09±1.61 0.739
FIB-4 3.26±2.77 3.90±3.32 3.40±3.19 0.057 3.11±2.05 2.82±1.93 0.159
 ≥3.25 964 (34.7) 121 (42.0) 115 (34.6) 0.059 37 (34.9) 126 (25.2) 0.041
Liver cirrhosis 451 (16.2) 74 (25.7) 56 (16.9) 0.007 18 (17.0) 64 (12.8) 0.253
eGFR (mL/min/1.73m2) 88.6±25.5 87.4±30.9 87.8±22.6 0.853 83.6±24.8 86.3±25.6 0.308
 <60 185 (6.7) 42 (14.6) 17 (5.1) <0.001 10 (9.4) 44 (8.8) 0.835
HCV RNA (log10 IU/mL) 6.1±0.9 6.0±0.9 6.1±0.8 0.278 6.2±0.9 6.2±0.9 0.688
HCV genotype
 GT 1 1,753 (63.1) 189 (65.6) 192 (57.8) 0.048 69 (65.0) 313 (62.6) 0.659
Follow-up (person-years) 18,668 1,663 2,848 634 3,994
Follow-up duration (years)
 Mean±SD 6.72±3.18 5.78±2.90 8.58±3.01 <0.001 5.98±2.68 7.99±2.91 <0.001
 Median (Q1–Q3) 6.57 (4.41–8.64) 5.76 (3.41–8.05) 8.43 (6.25–10.35) 5.65 (3.92–8.24) 7.82 (5.92–9.55)
New-onset HCC 480 (17.3) 68 (23.6) 57 (17.2) 0.002 14 (13.2) 47 (9.4) <0.001
 Annual incidence of HCC (per 10,000 person-years) 257.1 408.9 200.1 <0.001 220.8 117.7 0.036
Competing death 238 (8.6) 40 (13.9) 25 (7.5) 13 (12.3) 18 (3.6)

Values are presented as mean±standard deviation (SD) or number (%).

CHC, chronic hepatitis C; BMI, body mass index; DM, diabetes mellitus; HTN, hypertension; HLP, hyperlipidemia; AST, aspartate aminotransferase; ALT, alanine aminotransferase; FIB-4, fibrosis index based on four factors; eGFR, estimated glomerular filtration rate; HCC, hepatocellular carcinoma.

Table 2.
Cox sub-distribution hazards model for risk factors of new-onset HCC among CHC patients in whom antiviral therapy failed while considering death as a competing risk
Variables Levels No. New-Onset Competing Crude
Adjusted
Adjusted
SHR (95% CI) P-value SHR (95% CI) P-value SHR (95% CI) P-value
Age (years) <65 2,226 335 (15.1) 156 (7.0) 1 1 1
≥65 553 145 (26.2) 82 (14.8) 1.93 (1.59–2.35) <0.001* 1.89 (1.52–2.36) <0.001* 1.89 (1.52–2.36) <0.001*
Gender Male 1,315 206 (15.7) 139 (10.6) 1 1 1
Female 1,464 274 (18.7) 99 (6.8) 1.23 (1.03–1.47) 0.025* 1.14 (0.92–1.40) 0.225 1.14 (0.92–1.40) 0.225
BMI (kg/m2) <27 2,291 390 (17.0) 186 (8.1) 1 - -
≥27 488 90 (18.4) 52 (10.7) 1.11 (0.88–1.39) 0.378 - -
Aspirin No 2,490 435 (17.5) 213 (8.6) 1 1 1
Yes 289 45 (15.6) 25 (8.7) 0.68 (0.50–0.91) 0.009* 0.71 (0.51–1.00) 0.049* 0.71 (0.51–1.00) 0.049*
DM/Metformin Non-DM 2,159 355 (16.4) 173 (8.0) 1 1 1.05 (0.76–1.44) 0.763
DM/metformin (+) 332 57 (17.2) 25 (7.5) 0.81 (0.62–1.05) 0.116 0.95 (0.69–1.31) 0.763 1
DM/metformin (-) 288 68 (23.6) 40 (13.9) 1.56 (1.20–2.03) <0.001* 1.51 (1.12–2.04) 0.007* 1.59 (1.07–2.36) 0.022*
HLP/Statin Non-HLP 2,173 419 (19.3) 207 (9.5) 1 1 2.02 (1.46–2.78) <0.001*
HLP/statin (+) 500 47 (9.4) 18 (3.6) 0.41 (0.30–0.55) <0.001* 0.50 (0.36–0.68) <0.001* 1
HLP/statin (-) 106 14 (13.2) 13 (12.3) 0.72 (0.43–1.03) 0.230 0.75 (0.44–1.28) 0.289 1.51 (0.83–2.75) 0.180
AST (IU/L) <80 1,586 186 (11.7) 103 (6.5) 1 -§ -§
≥80 1,193 294 (24.6) 135 (11.3) 2.03 (1.69–2.44) <0.001* -§ -§
ALT (IU/L) <80 1,057 119 (11.3) 74 (7.0) 1 -§ -§
≥80 1,722 361 (21.0) 164 (9.5) 1.67 (1.36–2.05) <0.001* -§ -§
FIB-4 <3.25 1,815 185 (10.2) 120 (6.6) 1 -§ -§
≥3.25 964 295 (30.6) 118 (12.2) 3.39 (2.82–4.07) <0.001* -§ -§
Liver cirrhosis No 2,328 339 (14.6) 170 (7.3) 1 1 1
Yes 451 141 (31.3) 68 (15.1) 2.43 (1.99–2.95) <0.001* 2.27 (1.81–2.85) <0.001* 2.27 (1.81–2.85) <0.001*
eGFR (mL/min/1.73m2) ≥60 2,594 446 (17.2) 201 (7.8) 1 - -
<60 185 34 (18.4) 37 (20.0) 1.03 (0.73–1.45) 0.871 - -
HCV RNA (IU/mL) ≤8,000,000 2,078 370 (17.8) 182 (8.8) 1 1 1
>8,000,000 332 38 (11.5) 16 (4.8) 0.66 (0.48–0.93) 0.016* 0.73 (0.51–1.04) 0.079 0.73 (0.51–1.04) 0.079
HCV genotype Non-1 855 126 (14.7) 82 (9.6) 1 1 1
1 1,753 320 (18.3) 133 (7.6) 1.24 (1.01–1.52) 0.039* 1.30 (1.04–1.63) 0.022* 1.30 (1.04–1.63) 0.022*

§ Due to AST, ALT and FIB-4 were associated with composition in the diagnosis of LC, we did not put these variables in the multivariate analysis.

BMI, body mass index; DM, diabetes mellitus; AST, aspartate aminotransferase; ALT, alanine aminotransferase; eGFR, estimated glomerular filtration rate; FIB-4, fibrosis index based on the 4 factors; eGFR, estimated glomerular filtration rate; HCC, hepatocellular carcinoma; SHR, sub-distribution hazard ratio.

* P<0.05.

Abbreviations

CHC
chronic hepatitis C
HCV
hepatitis C virus
HCC
hepatocellular carcinoma
DM
diabetes mellitus
HTN
hypertension
HLP
hyperlipidemia
LC
liver cirrhosis
LT
liver transplant
DAA
Direct-acting antiviral agent
BMI
body mass index
SVR
sustained virological response
ALT
alanine aminotransferase
AST
aspartate aminotransferase
eGFR
estimated glomerular filtration rate
FIB-4
fibrosis index based on the four factors
GT
genotype
SHR
sub-distribution hazard ratio
aSHR
adjusted sub-distribution hazard ratio
CI
confidence interval
ICD-9-CM
International Classification of Diseases
ICD-10
International Classification of Disease

REFERENCES

1. Global Burden of Disease Liver Cancer Collaboration, Akinyemiju T, Abera S, Ahmed M, Alam N, Alemayohu MA, Allen C, et al. The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national level: results from the Global Burden of Disease study 2015. JAMA Oncol 2017;3:1683-1691.
pmid pmc
2. Yu ML, Chuang WL. Path from the discovery to the elimination of hepatitis C virus: honoring the winners of the Nobel Prize in Physiology or Medicine 2020. Kaohsiung J Med Sci 2021;37:7-11.
crossref pmid pdf
3. Hsu WF, Tsai PC, Chen CY, Tseng KC, Lai HC, Kuo HT, et al. Hepatitis C virus eradication decreases the risks of liver cirrhosis and cirrhosis-related complications (Taiwanese chronic hepatitis C cohort). J Gastroenterol Hepatol 2021;36:2884-2892.
crossref pmid pdf
4. Yeh ML, Liang PC, Tsai PC, Wang SC, Leong J, Ogawa E, et al. Characteristics and survival outcomes of hepatocellular carcinoma developed after HCV SVR. Cancers (Basel) 2021;13:3455.
crossref pmid pmc
5. Beste LA, Green P, Berry K, Belperio P, Ioannou GN. Hepatitis C-related hepatocellular carcinoma incidence in the veterans health administration after introduction of direct-acting antivirals. JAMA 2020;324:1003-1005.
crossref pmid pmc
6. Huang CF, Yeh ML, Huang CY, Tsai PC, Ko YM, Chen KY, et al. Pretreatment glucose status determines HCC development in HCV patients with mild liver disease after curative antiviral therapy. Medicine (Baltimore) 2016;95:e4157.
crossref pmid pmc
7. Huang CF, Yeh ML, Huang CI, Liang PC, Lin YH, Lin ZY, et al. Post-treatment fibrotic modifications overwhelm pretreatment liver fibrosis in predicting HCC in CHC patients with curative antivirals. Hepatol Int 2018;12:544-551.
crossref pmid pdf
8. Ciancio A, Ribaldone DG, Dotta A, Giordanino C, Sacco M, Fagoonee S, et al. Long-term follow-up of diabetic and non-diabetic patients with chronic hepatitis C successfully treated with direct-acting antiviral agents. Liver Int 2021;41:276-287.
crossref pmid pdf
9. Wang HW, Tsai PC, Chen CY, Tseng KC, Lai HC, Kuo HT, et al. Risk stratification of hepatocellular carcinoma incidence using a fibrosis-4-based prediction model in patients with chronic hepatitis C receiving antiviral therapy: a nationwide real-world Taiwanese cohort study. Am J Cancer Res 2022;12:3164-3174.
pmid pmc
10. Huang JF, Yu ML, Dai CY, Hsieh MY, Hwang SJ, Hsiao PJ, et al. Reappraisal of the characteristics of glucose abnormalities in patients with chronic hepatitis C infection. Am J Gastroenterol 2008;103:1933-1940.
crossref pmid
11. Davila JA, Morgan RO, Shaib Y, McGlynn KA, El-Serag HB. Diabetes increases the risk of hepatocellular carcinoma in the United States: a population based case control study. Gut 2005;54:533-539.
crossref pmid pmc
12. Cunha V, Cotrim HP, Rocha R, Carvalho K, Lins-Kusterer L. Metformin in the prevention of hepatocellular carcinoma in diabetic patients: a systematic review. Ann Hepatol 2020;19:232-237.
crossref pmid
13. Tsai PC, Kuo HT, Hung CH, Tseng KC, Lai HC, Peng CY, et al. Metformin reduces hepatocellular carcinoma incidence after successful antiviral therapy in patients with diabetes and chronic hepatitis C in Taiwan. J Hepatol 2023;78:281-292.
crossref pmid
14. Simon TG, Bonilla H, Yan P, Chung RT, Butt AA. Atorvastatin and fluvastatin are associated with dose-dependent reductions in cirrhosis and hepatocellular carcinoma, among patients with hepatitis C virus: results from ERCHIVES. Hepatology 2016;64:47-57.
crossref pmid pmc
15. Scheuer PJ. Classification of chronic viral hepatitis: a need for reassessment. J Hepatol 1991;13:372-374.
crossref pmid
16. Castéra L, Vergniol J, Foucher J, Le Bail B, Chanteloup E, Haaser M, et al. Prospective comparison of transient elastography, Fibrotest, APRI, and liver biopsy for the assessment of fibrosis in chronic hepatitis C. Gastroenterology 2005;128:343-350.
crossref pmid
17. Lin YH, Yeh ML, Huang CI, Yang JF, Liang PC, Huang CF, et al. The performance of acoustic radiation force impulse imaging in predicting liver fibrosis in chronic liver diseases. Kaohsiung J Med Sci 2016;32:362-366.
crossref pmid
18. Wang CC, Liu CH, Lin CL, Wang PC, Tseng TC, Lin HH, et al. Fibrosis index based on four factors better predicts advanced fibrosis or cirrhosis than aspartate aminotransferase/platelet ratio index in chronic hepatitis C patients. J Formos Med Assoc 2015;114:923-928.
crossref pmid
19. Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 1988;16:1141-1154.
crossref
20. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 1999;94:496-509.
crossref
21. Dai CY, Chuang WL, Ho CK, Hsieh MY, Huang JF, Lee LP, et al. Associations between hepatitis C viremia and low serum triglyceride and cholesterol levels: a community-based study. J Hepatol 2008;49:9-16.
crossref pmid
22. Dai CY, Yeh ML, Huang CF, Hou CH, Hsieh MY, Huang JF, et al. Chronic hepatitis C infection is associated with insulin resistance and lipid profiles. J Gastroenterol Hepatol 2015;30:879-884.
pmid
23. Huang CF, Dai CY, Yeh ML, Huang CI, Lee HC, Lai WT, et al. Cure or curd: modification of lipid profiles and cardio-cerebrovascular events after hepatitis C virus eradication. Kaohsiung J Med Sci 2020;36:920-928.
crossref pmid pdf
24. Jeong GH, Lee KH, Kim JY, Eisenhut M, Kronbichler A, van der Vliet HJ, et al. Effect of statin on cancer incidence: an umbrella systematic review and meta-analysis. J Clin Med 2019;8:819.
crossref pmid pmc
25. El-Serag HB, Johnson ML, Hachem C, Morgana RO. Statins are associated with a reduced risk of hepatocellular carcinoma in a large cohort of patients with diabetes. Gastroenterology 2009;136:1601-1608.
crossref pmid pmc
26. Butt AA, Yan P, Bonilla H, Abou-Samra AB, Shaikh OS, Simon TG, et al. Effect of addition of statins to antiviral therapy in hepatitis C virus-infected persons: results from ERCHIVES. Hepatology 2015;62:365-374.
crossref pmid
27. Tsan YT, Lee CH, Ho WC, Lin MH, Wang JD, Chen PC. Statins and the risk of hepatocellular carcinoma in patients with hepatitis C virus infection. J Clin Oncol 2013;31:1514-1521.
crossref pmid
28. Chen HP, Shieh JJ, Chang CC, Chen TT, Lin JT, Wu MS, et al. Metformin decreases hepatocellular carcinoma risk in a dosedependent manner: population-based and in vitro studies. Gut 2013;62:606-615.
crossref pmid
29. Jiang Z, Liu H. Metformin inhibits tumorigenesis in HBV-induced hepatocellular carcinoma by suppressing HULC overexpression caused by HBX. J Cell Biochem 2018;119:4482-4495.
crossref pmid pdf
30. Babcook MA, Shukla S, Fu P, Vazquez EJ, Puchowicz MA, Molter JP, et al. Synergistic simvastatin and metformin combination chemotherapy for osseous metastatic castration-resistant prostate cancer. Mol Cancer Ther 2014;13:2288-2302.
crossref pmid pmc pdf
31. Babcook MA, Sramkoski RM, Fujioka H, Daneshgari F, Almasan A, Shukla S, et al. Combination simvastatin and metformin induces G1-phase cell cycle arrest and Ripk1- and Ripk3-dependent necrosis in C4-2B osseous metastatic castrationresistant prostate cancer cells. Cell Death Dis 2014;5:e1536.
crossref pmid pmc pdf
32. Freeman AJ, Dore GJ, Law MG, Thorpe M, Von Overbeck J, Lloyd AR, et al. Estimating progression to cirrhosis in chronic hepatitis C virus infection. Hepatology 2001;34(4 Pt 1):809-816.
crossref pmid
33. El-Serag HB, Rudolph KL. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology 2007;132:2557-2576.
crossref pmid
34. Yu ML, Huang CF, Yeh ML, Tsai PC, Huang CI, Hsieh MH, et al. Time-Degenerative factors and the risk of hepatocellular carcinoma after antiviral therapy among hepatitis C virus patients: a model for prioritization of treatment. Clin Cancer Res 2017;23:1690-1697.
crossref pmid pdf
35. El-Serag HB, Tran T, Everhart JE. Diabetes increases the risk of chronic liver disease and hepatocellular carcinoma. Gastroenterology 2004;126:460-468.
crossref pmid
36. Cramp ME. HBV + HCV = HCC? Gut 1999;45:168-169.
crossref pmid pmc
37. Yu ML, Lin SM, Chuang WL, Dai CY, Wang JH, Lu SN, et al. A sustained virological response to interferon or interferon/ribavirin reduces hepatocellular carcinoma and improves survival in chronic hepatitis C: a nationwide, multicentre study in Taiwan. Antivir Ther 2006;11:985-994.
crossref pmid pdf
38. Lu MY, Huang CF, Hung CH, Tai CM, Mo LR, Kuo HT, et al. Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program. Clin Mol Hepatol 2024;30:64-79.
pmid
39. Yu ML, Tai CM, Mo LR, Kuo HT, Huang CF, Tseng KC, et al. An algorithm for simplified hepatitis C virus treatment with non-specialist care based on nation-wide data from Taiwan. Hepatol Int 2024;18:461-475.
crossref pmid pmc pdf
40. Hsu PY, Wei YJ, Lee JJ, Niu SW, Huang JC, Hsu CT, et al. Comedications and potential drug-drug interactions with directacting antivirals in hepatitis C patients on hemodialysis. Clin Mol Hepatol 2021;27:186-196.
crossref pmid pmc pdf

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