Factors associated with pre-treatment hyperferritinemia in patients with chronic hepatitis C virus infection

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We delineated pre-treatment factors associated with hyperferritinemia in these patients. 1682 eligible patients underwent pre-treatment assessment for serum ferritin and various host/viral factors. Univariate and multivariate logistic regression analyses were conducted to evaluate factors associated with hyperferritinemia. Multivariate logistic regression analyses revealed that age > 50 years (adjusted odds ratio [OR]: 1.38 (95% confidence interval [CI]: 1.09–1.74), p = 0.008), fibrosis stage ≥ F3 (adjusted OR: 1.36 (95% CI: 1.04–1.77), p = 0.02), fibrosis index based on four parameters (FIB-4) > 3.25 (adjusted OR: 1.46 (95% CI: 1.11–1.92), p = 0.01), presence of metabolic dysfunction-associated steatotic liver disease (MASLD) (adjusted OR: 1.43 (95% CI: 1.21–1.76), p = 0.001), and alanine transaminase (ALT) > 2 folds upper limit of normal (ULN) (adjusted OR: 2.87 (95% CI: 2.20–3.75), p < 0.001) were associated hyperferritinemia. The log 10 value of HBV or HCV viral load was not associated with the log 10 value of ferritin level (Spearman’s rank correlation coefficient: -0.025, p = 0.81 and 0.002, p = 0.92). In conclusion, host factors, rather than viral factors, are associated with hyperferritinemia in patients with HCV. Biological sciences/Microbiology Health sciences/Gastroenterology hepatitis C virus hepatitis B virus hyperferritinemia metabolic dysfunction-associated steatotic liver disease Introduction Globally, an estimated 58 million people have chronic hepatitis C virus (HCV) infection, with about 1.5 million new infections occurring annually. 1 The complications of HCV, including cirrhosis, hepatic decompensation and hepatocellular carcinoma (HCC), significantly contribute to the global health and economic burdens. In 2019, an estimated 290,000 deaths were attributed to HCV, primarily as a result of these complications. 1 Ferritin is essential for iron storage and homeostasis, protecting cells from iron toxicity through ferroxidase activity on its heavy chain. 2 Serum ferritin has been extensively studied for decades as a noninvasive and affordable laboratory test. 3 , 4 Elevated serum ferritin levels, which are observed with a prevalence of 5.9–19.0% in healthy individuals, vary among different ethnic groups. 5 , 6 This condition is often overlooked by general practitioners despite its wide range of etiologies, including inflammatory and infectious diseases, chronic liver disorders like cirrhosis, non-alcoholic fatty liver disease (NAFLD), and viral hepatitis, metabolic syndrome (MS), malignancies and immune-mediated syndromes such as adult-onset Still's disease, hemophagocytic lymphohistiocytosis, hemochromatosis. 7 Hyperferritinemia, once considered an indirect sign of increased iron stores, is now understood to result from complex mechanisms, including hepatocyte damage leading to ferritin release and acute phase reactions that stimulate ferritin synthesis and secretion. 4 While the physiological significance of ferritin is not yet fully understood, research regarding ferritin as a biomarker in relation to inflammatory diseases, cancer, neurodegeneration, and infections is currently emerging. 8 Serum levels of ferritin were first described to be linked to chronic HCV infection in 1990s. 9 Approximately 30–40% of individuals with HCV exhibit increased levels of serum iron, transferrin saturation, and ferritin. 10 However, it is not fully understood whether the hyperferritinemia is caused by the virus itself, other host factors, or the interaction between the virus and the host. Serum ferritin has been suggested as a potential predictor of treatment response and disease progression in HCV infections. Elevated ferritin levels in patients with chronic HCV infection are highly correlated with advanced hepatic fibrosis, necroinflammation, and steatosis, as well as an increased risk of developing HCC. 11 , 12 Furthermore, elevated ferritin levels can impact antiviral responses and on-treatment viral kinetics to interferon (IFN)-based treatments. 13 , 14 Before utilizing serum ferritin as a marker for chronic implications in HCV, it is essential to understand potential factors contributing to its elevation. Our study aims to identify factors contributing to pre-treatment hyperferritinemia in HCV, enabling a more precise interpretation of serum ferritin and enhancing the assessment and management of the disease. Materials and methods Patients Between January 2015 and December 2023, we prospective recruited participants aged ≥ 18 years who had been diagnosed as chronic HCV infection, defined as detectable HCV antibody (anti-HCV) (Abbott HCV EIA 2.0, Abbott Laboratories, Abbott Park, Illinois, USA) and quantifiable serum HCV ribonucleic acid (RNA) (Cobas TaqMan HCV Test v2.0, Roche Diagnostics, Mannheim, Germany, lower limit of quantification (LLOQ): 15 IU/mL) for ≥ 6 months at the National Taiwan University Hospital (NTUH) and NYUH Yun-Lin Branch. Participants with decompensated cirrhosis, a history of HCC, end-stage kidney disease (ESKD), human immunodeficiency virus (HIV) co-infection, iron deficiency anemia, increased alcohol consumption which was defined as ≥ 140 g/week for females and ≥ 210 g/week for males or those who had undergone organ transplantation were excluded from the study. All methods followed relevant guidelines and regulations. Experimental protocols were approved by the 7th Core Lab of the National Taiwan University Hospital and the 1st Common Laboratory of the National Taiwan University Hospital, Yun-Lin Branch. Informed consent was obtained from all subjects and/or their legal guardians. Study design Participant’s baseline demographics, including age, sex, history of type 2 diabetes (T2D), hypertension (HTN) and hyperlipidemia, body mass index (BMI) with a cut-off of ≥ 23 kg/m 2 to denote overweight/obesity, platelet counts, international normalized ratio (INR), serum albumin, total bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT) with an upper limit of normal (ULN) of 30 U/L for males and 19 U/L for females, estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, fasting glucose, glycosylated hemoglobin (HbA1c), triglyceride, high-density lipoprotein-cholesterol (HDL-C), ferritin, hepatitis B virus (HBV) surface antigen (HBsAg) (Abbott Architect HBsAg qualitative assay, Abbott Laboratories, Abbott Park, Illinois, USA), HBV deoxyribonucleic acid (DNA) (Cobas AmpliPrep/Cobas TaqMan HBV DNA test, v.2.0, Roche Diagnostics, Mannheim, Germany, LLOQ): 20 IU/mL), HCV RNA, and HCV genotype (Roche Cobas HCV GT, Roche Diagnostics, Mannheim, Germany or Abbott RealTime HCV GT II, Abbott Laboratories, Abbott Park, Illinois, USA) were assessed. 8 , 15 – 18 Liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) were determined using vibration-controlled transient elastography (VCTE) (FibroScan, Echosens, Paris, France) equipped with an M or XL probe. The cut-off values of LSM for a hepatic fibrosis stages of F0-1, F2, F3, and F4 are ≤ 7.0 kPa, 7.1–9.4 kPa, 9.5–12.4 kPa, and ≥ 12.5 kPa, respectively. 19 Metabolic dysfunction-associated steatotic liver disease (MASLD) was characterized by the presence of steatotic liver disease (SLD) with a CAP cut-off value of ≥ 248 dB/m, in addition to at least one out of five cardiometabolic risk factors. 20 , 21 The fibrosis index based on four parameters (FIB-4) was calculated for all participants. 22 Hyperferritinemia was defined as a serum ferritin level exceeding 300 ng/mL for males and 200 ng/mL for females. 2 Statistical analysis All statistical analyses were conducted using the Statistical Package for Social Science (SPSS version 26.0 (IBM)). Continuous variables were present as median (interquartile range [IQR]), while categorical data were present as numbers (percentage). Univariate logistic regression analysis was utilized to explore the relationship between hyperferritinemia and host/viral factors of interest, including age, sex, HBV coinfection, HCV viral load, HCV genotype, hepatic fibrosis stage, FIB-4 score, MASLD, ALT quotient, and eGFR level in the entire population. The results were reported as crude odds ratios (ORs) with 95% confidence intervals (CIs). Among participants with MASLD, we further analyzed this association with the aforementioned factors, as well as with T2D and BMI. Multivariate logistic regression analysis was performed for factors with a p-value less than 0.10 in the univariate analysis to identify independent variables associated with hyperferritinemia, and these were reported as adjusted ORs with 95% CIs. Spearman’s rank correlation was used to evaluate the correlation between the log 10 value of HBV viral load or log 10 value of HCV viral load and the log 10 serum ferritin level, ALT level and FIB-4 score. Among participants with HBV coinfection, those with a viral load below the LLOQ had their log 10 value of HBV viral load set as 0. All statistical analyses were two-tailed, and statistical significance was defined as a p-value less than 0.05. Results Patient characteristics Of 2343 participants diagnosed with chronic HCV infection, 661 were excluded from the study because of decompensated cirrhosis (n = 21), a history of HCC (n = 75), organ transplantation (n = 35), ESKD (n = 240), HIV coinfection (n = 253), increased alcohol consumption (n = 34), and iron deficiency anemia (n = 3). The remaining 1682 eligible participants were included in the study (Fig. 1 .) The median age was 56 years (IQR: 48–63 years) and 864 (51.4%) participants were males. The median log 10 HCV viral load was 6.07 IU/mL and 991 (58.9%) participants were infected with HCV genotype 1. One hundred forty-four (8.6%) participants were coinfected with HBV. The median log 10 HBV viral load was 0.00 IU/mL (IQR: 0.00-2.73 IU/mL). With regard to LSM, 699 (42.4%), 416 (25.3%), 199 (12.1%), and 333 (20.2%) participants had a fibrosis stage of F0-F1, F2, F3 and F4. MASLD was present in 635 (38.6%) participants, of whom T2D, overweight/obesity, and lean/normal weight were present in 221, 407 and 7 participants. Furthermore, 1294 (76.9%), 1505 (89.5%), and 782 (46.5%) participants had ALT level > 2 folds ULN, an eGFR > 60 mL/min/1.73m 2 , and hyperferritinemia (Table 1 ). Table 1 Baseline characteristics Characteristics a Participants (N = 1682) Age, year 56 (48–63) Age > 50 years, n (%) 1161 (69.0) Male, n (%) 864 (51.4) HBV coinfection, n (%) 144 (8.6) HCV RNA, log 10 , IU/mL 6.07 (5.37–6.56) HCV RNA > 2,000,000 IU/mL, n (%) 638 (37.9) HCV genotype 1, (%) b 991 (58.9) HBV DNA, log 10 IU/mL c 0.00 (0.00-2.73) LSM, kPa d 7.5 (6.1–11.1) Fibrosis stage (METAVIR), n (%) e F0-F1 699 (42.4) F2 416 (25.3) F3 199 (12.1) F4 333 (20.2) FIB-4 2.23 (1.42–3.73) FIB-4 > 3.25, n (%) 515 (30.6) CAP, dB/m d 238 (214–268) MASLD, n (%) 635 (38.6) T2D 221 (13.4) BMI ≥ 23 kg/m 2 407 (24.7) BMI, kg/m 2 25.3 (23.0-27.6) BMI ≥ 23 kg/m 2 , n (%) 1263 (76.9) Platelet count, 10 9 /L 174 (134–213) INR 1.00 (0.96–1.04) Albumin, g/dL 4.3 (4.1–4.5) Total bilirubin, mg/dL 0.9 (0.7–1.1) AST, U/L 63 (40–103) ALT, U/L 86 (51–146) ALT > 2 folds ULN, n (%) f 1294 (76.9) eGFR, mL/min/1.73m 2 g 79 (68–94) eGFR ≥ 60 mL/min/1.73m 2 g 1505 (89.5) Ferritin, ng/mL 231 (131–400) Hyperferritinemia, n (%) h 782 (46.5) HBV, hepatitis B virus; HCV, hepatitis C virus; RNA, ribonucleic acid; IU, international unit; DNA, deoxyribonucleic acid, LSM, liver stiffness measurement; kPa, kilo Pascal; FIB-4, fibrosis index based on four parameters; CAP, controlled attenuation parameter; dB, decibel; MASLD, metabolic dysfunction-associated steatotic liver disease; T2D, type 2 diabetes; BMI, body mass index; INR, international normalized ratio; AST, aspartate transaminase; ALT, alanine transaminase; ULN, upper limit of normal; eGFR, estimated glomerular filtration rate. a Data are shown in median (interquartile range, IQR) unless otherwise indicated. b Participants with HCV genotype 1a, genotype 1b, genotype 1a plus 1b, or unsubtypable genotype 1 were regarded as HCV genotype 1 infection. c Data was set as 0 for serum HBV DNA level < lower limit of quantification (LLOQ)21 d Assessed by vibration-controlled transient elastography (VETE). Thirty-five participants without valid or reliable LSM or CAP were excluded from the analysis. e The cutoff values of LSM for a hepatic fibrosis stage of F0-1, F2, F3, and F4 are ≤ 7.0 kPa, 7.1–9.4 kPa, 9.5–12.4 kPa, and ≥ 12.5 kPa, respectively. f The ULN of ALT are 30 U/L for males and 19 U/L for females, respectively. g Calculated by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. h Serum ferritin levels are > 300 ng/mL for males and > 200 ng/mL for females, respectively. Pre-treatment factors associated with hyperferritinemia in the entire population In the univariate logistic regression analysis, age > 50 year (crude OR: 1.73; 95% CI: 1.40–2.14, p < 0.001), fibrosis stage ≥ F3 (crude OR: 2.22; 95% CI: 1.80–2.74, p 3.25 (crude OR: 2.39; 95% CI: 1.93–2.95, p < 0.001), presence of MASLD (crude OR: 1.51; 95% CI: 1.23–1.84, p 2 folds ULN (crude OR: 3.55; 95% CI: 2.75–4.59, p < 0.001), and eGFR < 60 mL/min/1.73m 2 (crude OR: 1.38; 95% CI: 1.01–1.89, p = 0.04) were significantly associated with hyperferritinemia, while sex, HBV coinfection, HCV RNA at a cut-off value of 2,000,000 IU/mL, and HCV genotype were not associated with hyperferritinemia (Table 2 ). Table 2 Univariate and multivariate regression analysis for factors associated with hyperferritinemia Parameter Univariate analysis Multivariate analysis a Hyperferritinemia Crude OR (95% CI) c p value Adjusted OR (95% CI) p value No (n = 900) b Yes (n = 782) b Age, years > 50 573 (63.7) 588 (75.2) 1.73 (1.40–2.14) < 0.001 1.38 (1.09–1.74) 0.008 ≤ 50 327 (36.3) 194 (24.8) Ref Ref Sex Male 472 (49.1) 392 (50.1) 0.91 (0.75–1.10) 0.34 - - Female 428 (50.9) 390 (49.9) Ref HBV coinfection Yes 73 (8.1) 71 (9.1) 1.13 (0.80–1.59) 0.48 - - No 827 (91.9) 711 (90.9) Ref HCV RNA > 2,000,000 IU/mL 337 (37.4) 301 (38.5) 1.05 (0.86–1.27) 0.66 - - ≤ 2,000,000 IU/mL 563 (62.6) 481 (61.5) Ref HCV genotype 1 Yes 514 (57.1) 477 (61.0) 1.17 (0.97–1.43) 0.11 - - No 386 (42.9) 305 (39.0) Ref Fibrosis stage a ≥ F3 212 (24.2) 320 (41.5) 2.22 (1.80–2.74) < 0.001 1.36 (1.04–1.77) 0.02 3.25 199 (22.1) 316 40.4) 2.39 (1.93–2.95) < 0.001 1.46 (1.11–1.92) 0.01 ≤ 3.25 701 (77.9) 466 (59.6) Ref Ref MASLD a Present 298 (34.0) 337 (43.7) 1.51 (1.23–1.84) 2 folds 606 (67.3) 688 (88.0) 3.55 (2.75–4.59) < 0.001 2.87 (2.20–3.75) < 0.001 ≤ 2 folds 294 (32.7) 94 (12.0) Ref Ref eGFR, mL/min/1.73m 2 < 60 82 (19.1) 95 (12.1) 1.38 (1.01–1.89) 0.04 - - ≥ 60 818 (90.9) 687 (87.9) Ref OR, odds ration; CI, confidence interval; HBV, hepatitis B virus; HCV, hepatitis C virus; RNA, ribonucleic acid; IU, international unit; FIB-4, fibrosis index based on four parameters; MASLD, metabolic dysfunction-associated steatotic liver disease; ALT, alanine transaminase; ULN, upper limit of normal; eGFR; estimated glomerular filtration rate. a Thirty-five participants without valid or reliable LSM or CAP were excluded from the univariate and multivariate analyses b Values in the corresponding columns are shown as numbers (percentages) unless otherwise indicated. c Factors with a p value of 50 year (adjusted OR: 1.38; 95% CI: 1.09–1.74, p = 0.008), fibrosis stage ≥ F3 (adjusted OR: 1.36; 95% CI: 1.04–1.77, p = 0.02), FIB-4 score > 3.25 (adjusted OR: 1.46; 95% CI: 1.11–1.92, p = 0.01), presence of MASLD (adjusted OR: 1.43; 95% CI: 1.12–1.76, p = 0.001), ALT > 2 folds ULN (adjusted OR: 2.87; 95% CI: 2.20–3.75, p < 0.001) were independent factors associated with hyperferritinemia (Table 2 ). Pre-treatment factors associated with hyperferritinemia in participants with MASLD Univariate logistic regression analysis revealed that age > 50 years (crude OR: 1.68; 95% CI: 1.20–2.35, p = 0.003), fibrosis stage ≥ F3 (crude OR: 1.90; 95% CI: 1.38–2.63, p 3.25 (crude OR: 2.29; 95% CI: 1.62–3.23, p 2 folds ULN (crude OR: 3.12; 95% CI: 2.07–4.71, p < 0.001) were significantly associated with hyperferritinemia among participants with concurrent MASLD. In contrast, T2D, BMI at a cut-off of 23 kg/m 2 , sex, HBV coinfection, HCV RNA at a cut-off value of 2,000,000 IU/mL, HCV genotype, and eGFR at a cut-off value of 60 mL/min/1.73m 2 were not associated with hyperferritinemia (Table 3 ). Table 3 Univariate and multivariate regression analysis for factors associated with hyperferritinemia in participants with MASLD Parameter Univariate analysis Multivariate analysis Hyperferritinemia Crude OR (95% CI) c p value Adjusted OR (95% CI) p value No (n = 298) b Yes (n = 337) b T2D Present 96 (32.2) 125 (37.1) 1.24 (0.89–1.72) 0.20 - - Absent 202 (67.8) 212 (62.9) Ref BMI ≥ 23 kg/m 2 292 (98.0) 324 (96.1) 0.51 (0.19–1.37) 0.18 - - 50 113 (37.9) 90 (26.7) 1.68 (1.20–2.35) 0.003 1.24 (0.87–1.79) 0.24 ≤ 50 185 (62.1) 247 (73.3) Ref Ref Sex Male 172 (57.7) 178 (52.8) 0.82 (0.60–1.12) 0.22 - - Female 126 (42.3) 159 (47.2) Ref HBV coinfection Yes 27 (19.1) 38 (11.3) 1.28 (0.76–2.15) 0.36 - - No 271 (90.9) 299 (88.7) Ref HCV RNA > 2,000,000 IU/mL 124 (41.6) 122 (36.2) 0.80 (0.58–1.10) 0.16 - - ≤ 2,000,000 IU/mL 174 (58.4) 215 (63.8) Ref HCV genotype 1 Yes 169 (56.7) 202 (59.9) 1.14 (0.83–1.57) 0.41 - - No 129 (43.3) 135 (40.1) Ref Fibrosis stage ≥ F3 96 (32.2) 160 (47.5) 1.90 (1.38–2.63) < 0.001 1.20 (0.81–1.79) 0.37 3.25 70 (23.5) 139 (41.2) 2.29 (1.62–3.23) 2 folds 208 (69.8) 296 (87.8) 3.12 (2.07–4.71) < 0.001 2.55 (1.67–3.90) < 0.001 ≤ 2 folds 90 (30.2) 41 (12.2) Ref Ref eGFR, mL/min/1.73m 2 < 60 39 (13.1) 45 (13.4) 1.02 (0.65–1.62) 0.92 - - ≥ 60 259 (86.9) 292 (86.6) Ref OR, odds ration; CI, confidence interval; MASLD, metabolic dysfunction-associated steatotic liver disease; T2D, type 2 diabetes; BMI, body mass index; HBV, hepatitis B virus; HCV, hepatitis C virus; RNA, ribonucleic acid; IU, international unit; FIB-4, fibrosis index based on four parameters; ALT, alanine transaminase; ULN, upper limit of normal; eGFR; estimated glomerular filtration rate. a Values in the corresponding columns are shown as numbers (percentages) unless otherwise indicated. b Factors with a p value of 3.25 (adjusted OR: 1.62; 95% CI: 1.05–2.50, p = 0.03) and ALT > 2 folds ULN (adjusted OR: 2.55; 95% CI: 1.67–3.90, p < 0.001) were independent factors associated with hyperferritinemia (Table 3 ). Correlation of serum HBV DNA with ferritin, ALT and FIB-4 Among the 144 participants with HBV coinfection, 74 (53.5%) had an HBV DNA level < LLOQ and 40 (28.8%) had an HBV DNA level between LLOQ and 2000 IU/mL. After log 10 transforming serum HBV DNA and ferritin levels, the Spearman’s rank correlation coefficient ( r ) between log 10 HBV DNA level and log 10 ferritin level was − 0.025 (p = 0.81) (Fig. 2 A). Regarding hepatic necroinflammation, the Spearman’s rank correlation coefficients ( r ) were − 0.099 (p = 0.24) between log 10 HBV DNA level and ALT level (Fig. 3 A). Moreover, the Spearman’s rank correlation coefficients ( r ) were − 0.140 (p = 0.09) between log 10 HBV DNA level and FIB-4 score (Fig. 3 C). Correlation of serum HCV DNA with ferritin, ALT and FIB-4 The Spearman’s rank correlation coefficient ( r ) between log 10 HCV RNA level and log 10 ferritin level was 0.002 (p = 0.92) (Fig. 2 B). Regarding hepatic necroinflammation, the Spearman’s rank correlation coefficients ( r ) were − 0.025 (p = 0.31) between log 10 HCV RNA level and ALT level (Fig. 3 B). Moreover, the Spearman’s rank correlation coefficients ( r ) were − 0.043 (p = 0.08) between log 10 HCV RNA level and FIB-4 score (Fig. 3 D). Discussion Our study, encompassing a sample size of 1,682 patients, represents the most extensive population analyzed to date in examining the factors and their correlation with pre-treatment ferritin levels in patients with HCV. To ensure the robustness of our study and minimize confounding variables, we diligently excluded patients with decompensated cirrhosis, a history of HCC, ESKD, HIV coinfection, organ transplantation, heightened alcohol consumption, and iron deficiency anemia that enhanced the reliability and validity. We demonstrated that individuals aged > 50 years and those with ALT levels exceeding > 2 folds ULN were more likely to exhibit hyperferritinemia, consistent with previous researches. 9 , 23 , 24 . Conversely, sex and eGFR at a cut-off of 60 mL/min/1.73m 2 were not found to be correlated with hyperferritinemia. The apparent discrepancy in the influence of eGFR on ferritin dynamics compared to earlier reports may be attributed to our exclusion of participants with ESKD and the inclusion of a limited number of participants with an eGFR below 60 mL/min/1.73m 2 , who were susceptible to hyperferritinemia. 25 Patients with HCV are at risk of developing insulin resistance, which can lead to MS. 26 – 28 The prevalence of NAFLD among individuals with HCV is estimated to be as high as 55%, with a range spanning from 40–86%, influenced by the distribution of MS and HCV genotypes. 29 According to the diagnostic criteria of MASLD, an updated nomenclature aimed at encompassing a broader spectrum of etiologies for steatotic liver disease, our population exhibits a prevalence rate of MASLD of 38.6%. 20 Within MASLD alone, there is a notable correlation between hyperferritinemia and the severity of liver fibrosis. 30 , 31 While no studies have specifically examined the prevalence rate of hyperferritinemia in individuals with concurrent HCV and MASLD, it can be inferred that this population likely exhibits greater rates compared to HCV or MASLD alone. The prevalence rate of hyperferritinemia among our patients reached 53%, significantly higher than the reported prevalence rates of approximately 30% in subjects with MASLD alone. 32 Chronic HCV infection induces hepatocyte injury, accompanied by the accumulation of extracellular matrix (ECM) proteins, ultimately resulting in accelerating hepatic fibrotic. The process of fibrotic change is dynamic, with later stages indicating increased severity. 33 , 34 While the stage of hepatic fibrosis and hyperferritinemia indicate the severity of hepatocyte damage, previous studies have provided limited evidence linking the severity of hepatic fibrosis to hyperferritinemia. Our study is the first to demonstrate a positive correlation between hyperferritinemia and the severity of hepatic fibrosis, utilizing two noninvasive indices, the FIB-4 scores and LSMs, as assessment tools. Univariate analysis revealed either higher FIB-4 scores (> 3.25) or LSMs (≥ 9.5 kPa) were associated with hyperferritinemia in both the entire population and those with MASLD. Due to the high collinearity between the FIB-4 score and LSM, and a relatively smaller sample size compared to the entire population, LSM was excluded as an independent risk factor in the multivariate model for association with hyperferritinemia among participants with MASLD. We also demonstrated that within the context of MASLD, T2D or obesity did not increase the risk of hyperferritinemia. This implies that the presence of MS, regardless of the potential contributing factors, may lead to systemic inflammation, thus resulting in hyperferritinemia. 20 , 35 , 36 Current evidence indicates that neither the HCV vial load nor genotype correlates with ALT levels or histological presentation, including necroinflammation or fibrosis. This is evident from our observations, showing no correlation between either ALT level or FIB-4 score with HCV viral load. 37 However, to date, no studies have investigated the correlation of hyperferritinemia with HCV viral load or genotype. This study is the first to demonstrate a lack of significant correlation between HCV viral load/genotype and hyperferritinemia. With regard to HBV infection, prior studies hypothesized that active HBV replication may result in elevated serum levels of iron and ferritin. 38 However, our participants with HBV coinfection, characterized by an almost negligible median log 10 HBV viral load of 0 and more than half of them without detectable HBV DNA, demonstrated that neither HBsAg nor the viral load were associated with hyperferritinemia. Additionally, the median log 10 HBV viral load did not show a significant association with ALT levels or FIB-4 scores. While our observation fails to confirm the proposed hypothesis, the lack of association of hyperferritinemia with HBV DNA due to the suppression of HBV load from active HCV replication may not be extrapolated to individuals with HBV alone, where the HBV viral load tends to be higher than that in HBV/HCV-coinfected subjects. 39 , 40 Although the risk of hyperferritinemia is consistently increased among individuals with chronic HCV infection, it remains unclear if there is a dosing effect of viral load on serum ferritin levels. In contrast to the low HBV load in our coinfected participants, most of whom had active HCV replication, as evidenced by a high median viral load. However, the HCV load did not exhibit a significant association with serum ferritin levels, ALT levels, or FIB-4 scores. Based on the similar trends observed in the association of HBV or HCV load with serum ferritin levels, we deduce that rather than direct virological effects, the serum level of ferritin is augmented indirectly through immune responses to HBV or HCV. Despite enrolling a sizable number of participants and meticulously excluding potential confounders to mitigate the imprecise risk estimates, several limitations are present in the current study. Firstly, this study was conducted exclusively in East Asians, and external validation should be conducted to confirm our findings in other ethnic populations. Secondly, we did not conduct HFE C282Y and H63D testing to exclude participants with HFE hemochromatosis. However, the presence of C282Y homozygotes and C282Y/H63D heterozygote in Asians is rare, rendering the genetic testing unnecessary. 5 Thirdly, we did not analyze the serum iron and transferrin saturation because only a minority of subjects with chronic viral hepatitis exhibit these derangements. 2 In conclusion, our study reveals that hyperferritinemia in patients with chronic HCV infection is primarily influenced by host factors such as age, severity of hepatic fibrosis, MASLD, and ALT levels, rather than viral factors. While viral factors may not directly predispose to hyperferritinemia, vigilant management of HBV and HCV using effective antiviral therapies remains essential to indirectly mitigate hyperferritinemia by reducing viral-induced hepatic necroinflammation and fibrosis. Declarations Acknowledgements: The authors thank Hui-Ju Lin and Pin-Chin Huang for clinical data management; the 7 th Core Lab of the National Taiwan University Hospital, and the 1 st Common Laboratory of the National Taiwan University Hospital, Yun-Lin Branch, for the instrumental and technical support. Author Contributions: Conceptualization: Chun-Jen Liu, Chen-Hua Liu. Data curation: Chen-Hua Liu. Formal analysis: Yu-Ping Chang, Chen-Hua Liu. Investigation: Yu-Ping Chang, Chiuan-Bo Huang, Jia-Horng Kao, Tung-Hung Su, Shang-Chin Huang, Tai-Chung Tseng, Pei-Jer Chen, Chun-Jen Liu, Chen-Hua Liu. Methodology: Yu-Ping Chang, Chun-Jen Liu, Chen-Hua Liu. Project administration: Yu-Ping Chang, Chun-Jen Liu, Chen-Hua Liu. Resources: Yu-Ping Chang, Chiuan-Bo Huang, Jia-Horng Kao, Tung-Hung Su, Shang-Chin Huang, Tai-Chung Tseng, Pei-Jer Chen, Chun-Jen Liu, Chen-Hua Liu. Software: Yu-Ping Chang, Chen-Hua Liu. Supervision: Chen-Hua Liu. Validation: Yu-Ping Chang, Chen-Hua Liu. Visualization: Yu-Ping Chang, Chen-Hua Liu. Writing – original draft: Yu-Ping Chang, Chun-Jen Liu, Chen-Hua Liu. Writing – review & editing: Yu-Ping Chang, Chiuan-Bo Huang, Jia-Horng Kao, Tung-Hung Su, Shang-Chin Huang, Tai-Chung Tseng, Pei-Jer Chen, Chun-Jen Liu, Chen-Hua Liu. Funding: The study was supported by the National Taiwan University Hospital (112-IF0004). Conflicts of interest: All authors declare no competing interests. Data availability statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. References Cui, F. et al. Global reporting of progress towards elimination of hepatitis B and hepatitis C. The Lancet Gastroenterology & Hepatology 8, 332–342 (2023). Sandnes, M., Ulvik, R. J., Vorland, M. & Reikvam, H. Hyperferritinemia-A Clinical Overview. J Clin Med 10, doi: 10.3390/jcm10092008 (2021). Koperdanova, M. & Cullis, J. O. Interpreting raised serum ferritin levels. bmj 351 (2015). Wang, W., Knovich, M. A., Coffman, L. G., Torti, F. M. & Torti, S. V. Serum ferritin: Past, present and future. Biochim Biophys Acta 1800, 760–769, doi: 10.1016/j.bbagen.2010.03.011 (2010). Adams, P. C. et al. Hemochromatosis and iron-overload screening in a racially diverse population. N Engl J Med 352, 1769–1778, doi: 10.1056/NEJMoa041534 (2005). Gensluckner, S. et al. Prevalence and Characteristics of Metabolic Hyperferritinemia in a Population-Based Central-European Cohort. Biomedicines 12, doi: 10.3390/biomedicines12010207 (2024). Ogilvie, C., Fitzsimons, K. & Fitzsimons, E. J. Serum ferritin values in primary care: are high values overlooked? J Clin Pathol 63, 1124–1126, doi: 10.1136/jcp.2010.083188 (2010). Moreira, A. C., Mesquita, G. & Gomes, M. S. Ferritin: an inflammatory player keeping iron at the core of pathogen-host interactions. Microorganisms 8, 589 (2020). Di Bisceglie, A. M., Axiotis, C. A., Hoofnagle, J. H. & Bacon, B. R. Measurements of iron status in patients with chronic hepatitis. Gastroenterology 102, 2108–2113, doi: 10.1016/0016-5085(92)90339-z (1992). Georgopoulou, U., Dimitriadis, A., Foka, P., Karamichali, E. & Mamalaki, A. Hepcidin and the iron enigma in HCV infection. Virulence 5, 465–476 (2014). Chapoutot, C. et al. Liver iron excess in patients with hepatocellular carcinoma developed on viral C cirrhosis. Gut 46, 711–714, doi: 10.1136/gut.46.5.711 (2000). Lambrecht, R. W. et al. Iron levels in hepatocytes and portal tract cells predict progression and outcomes of patients with advanced chronic hepatitis C. Gastroenterology 140, 1490–1500.e1493, doi: 10.1053/j.gastro.2011.01.053 (2011). Ikura, Y., Morimoto, H., Johmura, H., Fukui, M. & Sakurai, M. Relationship between hepatic iron deposits and response to interferon in chronic hepatitis C. Am J Gastroenterol 91, 1367–1373 (1996). Ackerman, Z., Pappo, O. & Ben-Dov, I. Z. The prognostic value of changes in serum ferritin levels during therapy for hepatitis C virus infection. J Med Virol 83, 1262–1268, doi: 10.1002/jmv.22093 (2011). Bonkovsky, H. L., Banner, B. F. & Rothman, A. L. Iron and chronic viral hepatitis. Hepatology 25, 759–768, doi: 10.1002/hep.510250345 (1997). Prati, D. et al. Updated definitions of healthy ranges for serum alanine aminotransferase levels. Ann Intern Med 137, 1–10, doi: 10.7326/0003-4819-137-1-200207020-00006 (2002). Levey, A. S. et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 150, 604–612, doi: 10.7326/0003-4819-150-9-200905050-00006 (2009). Liu, C. H. et al. Comparison of Abbott RealTime HCV Genotype II with Versant line probe assay 2.0 for hepatitis C virus genotyping. J Clin Microbiol 53, 1754–1757, doi: 10.1128/jcm.03548-14 (2015). Castera, L., Forns, X. & Alberti, A. Non-invasive evaluation of liver fibrosis using transient elastography. J Hepatol 48, 835–847, doi: 10.1016/j.jhep.2008.02.008 (2008). Rinella, M. E. et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol 79, 1542–1556, doi: 10.1016/j.jhep.2023.06.003 (2023). Karlas, T. et al. Individual patient data meta-analysis of controlled attenuation parameter (CAP) technology for assessing steatosis. J Hepatol 66, 1022–1030, doi: 10.1016/j.jhep.2016.12.022 (2017). Sterling, R. K. et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 43, 1317–1325, doi: 10.1002/hep.21178 (2006). McKinnon, E. J., Rossi, E., Beilby, J. P., Trinder, D. & Olynyk, J. K. Factors that affect serum levels of ferritin in Australian adults and implications for follow-up. Clinical Gastroenterology and Hepatology 12, 101–108. e104 (2014). Choi, K. M. et al. Association among serum ferritin, alanine aminotransferase levels, and metabolic syndrome in Korean postmenopausal women. Metabolism 54, 1510–1514, doi: 10.1016/j.metabol.2005.05.018 (2005). Branten, A. J., Swinkels, D. W., Klasen, I. S. & Wetzels, J. F. Serum ferritin levels are increased in patients with glomerular diseases and proteinuria. Nephrology Dialysis Transplantation 19, 2754–2760 (2004). Moucari, R. et al. Insulin resistance in chronic hepatitis C: association with genotypes 1 and 4, serum HCV RNA level, and liver fibrosis. Gastroenterology 134, 416–423, doi: 10.1053/j.gastro.2007.11.010 (2008). Maeno, T. et al. Mechanisms of increased insulin resistance in non-cirrhotic patients with chronic hepatitis C virus infection. J Gastroenterol Hepatol 18, 1358–1363, doi: 10.1046/j.1440-1746.2003.03179.x (2003). Negro, F. HCV infection and metabolic syndrome: which is the chicken and which is the egg? Gastroenterology 142, 1288–1292, doi: 10.1053/j.gastro.2011.12.063 (2012). Adinolfi, L. E. et al. NAFLD and NASH in HCV Infection: Prevalence and Significance in Hepatic and Extrahepatic Manifestations. Int J Mol Sci 17, 803, doi: 10.3390/ijms17060803 (2016). Kowdley, K. V. et al. Serum ferritin is an independent predictor of histologic severity and advanced fibrosis in patients with nonalcoholic fatty liver disease. Hepatology 55, 77–85, doi: 10.1002/hep.24706 (2012). Manousou, P. et al. Serum ferritin is a discriminant marker for both fibrosis and inflammation in histologically proven non-alcoholic fatty liver disease patients. Liver Int 31, 730–739, doi: 10.1111/j.1478-3231.2011.02488.x (2011). Moris, W., Verhaegh, P., Jonkers, D., Deursen, C. V. & Koek, G. Hyperferritinemia in Nonalcoholic Fatty Liver Disease: Iron Accumulation or Inflammation? Semin Liver Dis 39, 476–482, doi: 10.1055/s-0039-1693114 (2019). Pinzani, M., Rombouts, K. & Colagrande, S. Fibrosis in chronic liver diseases: diagnosis and management. J Hepatol 42 Suppl, S22–36, doi: 10.1016/j.jhep.2004.12.008 (2005). Ginès, P. et al. Screening for liver fibrosis in the general population: a call for action. Lancet Gastroenterol Hepatol 1, 256–260, doi: 10.1016/s2468-1253(16)30081-4 (2016). Younes, R. et al. Caucasian lean subjects with non-alcoholic fatty liver disease share long-term prognosis of non-lean: time for reappraisal of BMI-driven approach? Gut 71, 382–390, doi: 10.1136/gutjnl-2020-322564 (2022). Armandi, A. et al. Serum ferritin levels can predict long-term outcomes in patients with metabolic dysfunction-associated steatotic liver disease. Gut 73, 825–834, doi: 10.1136/gutjnl-2023-330815 (2024). Gervais, A. et al. Quantitation of hepatic hepatitis C virus RNA in patients with chronic hepatitis C. Relationship with severity of disease, viral genotype and response to treatment. J Hepatol 35, 399–405, doi: 10.1016/s0168-8278(01)00138-6 (2001). Luo, J. et al. Serum ferritin diagnosis and prediction of hepatitis B virus-related acute-on-chronic liver failure. J Med Virol 95, e28183, doi: 10.1002/jmv.28183 (2023). Mavilia, M. G. & Wu, G. Y. HBV-HCV Coinfection: Viral Interactions, Management, and Viral Reactivation. J Clin Transl Hepatol 6, 296–305, doi: 10.14218/jcth.2018.00016 (2018). Dai, C. Y. et al. Influence of hepatitis C virus on the profiles of patients with chronic hepatitis B virus infection. J Gastroenterol Hepatol 16, 636–640, doi: 10.1046/j.1440-1746.2001.02494.x (2001). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4445076","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":313339395,"identity":"fbb42ba5-5b1b-480d-b72f-85544b7635bd","order_by":0,"name":"Yu Ping Chang","email":"","orcid":"","institution":"National Taiwan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"Ping","lastName":"Chang","suffix":""},{"id":313339396,"identity":"247eda73-5125-4ca0-9ddc-4a2a394a4db4","order_by":1,"name":"Chiuan-Bo Huang","email":"","orcid":"","institution":"National Taiwan University 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02:26:10","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":93544,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-4445076/v1/f0a862bd22ceb11ce02f219c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Factors associated with pre-treatment hyperferritinemia in patients with chronic hepatitis C virus infection","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobally, an estimated 58\u0026nbsp;million people have chronic hepatitis C virus (HCV) infection, with about 1.5\u0026nbsp;million new infections occurring annually.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The complications of HCV, including cirrhosis, hepatic decompensation and hepatocellular carcinoma (HCC), significantly contribute to the global health and economic burdens. In 2019, an estimated 290,000 deaths were attributed to HCV, primarily as a result of these complications.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFerritin is essential for iron storage and homeostasis, protecting cells from iron toxicity through ferroxidase activity on its heavy chain.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Serum ferritin has been extensively studied for decades as a noninvasive and affordable laboratory test.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Elevated serum ferritin levels, which are observed with a prevalence of 5.9\u0026ndash;19.0% in healthy individuals, vary among different ethnic groups.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e This condition is often overlooked by general practitioners despite its wide range of etiologies, including inflammatory and infectious diseases, chronic liver disorders like cirrhosis, non-alcoholic fatty liver disease (NAFLD), and viral hepatitis, metabolic syndrome (MS), malignancies and immune-mediated syndromes such as adult-onset Still's disease, hemophagocytic lymphohistiocytosis, hemochromatosis.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Hyperferritinemia, once considered an indirect sign of increased iron stores, is now understood to result from complex mechanisms, including hepatocyte damage leading to ferritin release and acute phase reactions that stimulate ferritin synthesis and secretion.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e While the physiological significance of ferritin is not yet fully understood, research regarding ferritin as a biomarker in relation to inflammatory diseases, cancer, neurodegeneration, and infections is currently emerging.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSerum levels of ferritin were first described to be linked to chronic HCV infection in 1990s.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Approximately 30\u0026ndash;40% of individuals with HCV exhibit increased levels of serum iron, transferrin saturation, and ferritin.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e However, it is not fully understood whether the hyperferritinemia is caused by the virus itself, other host factors, or the interaction between the virus and the host. Serum ferritin has been suggested as a potential predictor of treatment response and disease progression in HCV infections. Elevated ferritin levels in patients with chronic HCV infection are highly correlated with advanced hepatic fibrosis, necroinflammation, and steatosis, as well as an increased risk of developing HCC.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Furthermore, elevated ferritin levels can impact antiviral responses and on-treatment viral kinetics to interferon (IFN)-based treatments.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBefore utilizing serum ferritin as a marker for chronic implications in HCV, it is essential to understand potential factors contributing to its elevation. Our study aims to identify factors contributing to pre-treatment hyperferritinemia in HCV, enabling a more precise interpretation of serum ferritin and enhancing the assessment and management of the disease.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003e Between January 2015 and December 2023, we prospective recruited participants aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years who had been diagnosed as chronic HCV infection, defined as detectable HCV antibody (anti-HCV) (Abbott HCV EIA 2.0, Abbott Laboratories, Abbott Park, Illinois, USA) and quantifiable serum HCV ribonucleic acid (RNA) (Cobas TaqMan HCV Test v2.0, Roche Diagnostics, Mannheim, Germany, lower limit of quantification (LLOQ): 15 IU/mL) for \u0026ge;\u0026thinsp;6 months at the National Taiwan University Hospital (NTUH) and NYUH Yun-Lin Branch. Participants with decompensated cirrhosis, a history of HCC, end-stage kidney disease (ESKD), human immunodeficiency virus (HIV) co-infection, iron deficiency anemia, increased alcohol consumption which was defined as \u0026ge;\u0026thinsp;140 g/week for females and \u0026ge;\u0026thinsp;210 g/week for males or those who had undergone organ transplantation were excluded from the study. All methods followed relevant guidelines and regulations. Experimental protocols were approved by the 7th Core Lab of the National Taiwan University Hospital and the 1st Common Laboratory of the National Taiwan University Hospital, Yun-Lin Branch. Informed consent was obtained from all subjects and/or their legal guardians.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eParticipant\u0026rsquo;s baseline demographics, including age, sex, history of type 2 diabetes (T2D), hypertension (HTN) and hyperlipidemia, body mass index (BMI) with a cut-off of \u0026ge;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e to denote overweight/obesity, platelet counts, international normalized ratio (INR), serum albumin, total bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT) with an upper limit of normal (ULN) of 30 U/L for males and 19 U/L for females, estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, fasting glucose, glycosylated hemoglobin (HbA1c), triglyceride, high-density lipoprotein-cholesterol (HDL-C), ferritin, hepatitis B virus (HBV) surface antigen (HBsAg) (Abbott Architect HBsAg qualitative assay, Abbott Laboratories, Abbott Park, Illinois, USA), HBV deoxyribonucleic acid (DNA) (Cobas AmpliPrep/Cobas TaqMan HBV DNA test, v.2.0, Roche Diagnostics, Mannheim, Germany, LLOQ): 20 IU/mL), HCV RNA, and HCV genotype (Roche Cobas HCV GT, Roche Diagnostics, Mannheim, Germany or Abbott RealTime HCV GT II, Abbott Laboratories, Abbott Park, Illinois, USA) were assessed.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLiver stiffness measurement (LSM) and controlled attenuation parameter (CAP) were determined using vibration-controlled transient elastography (VCTE) (FibroScan, Echosens, Paris, France) equipped with an M or XL probe. The cut-off values of LSM for a hepatic fibrosis stages of F0-1, F2, F3, and F4 are \u0026le;\u0026thinsp;7.0 kPa, 7.1\u0026ndash;9.4 kPa, 9.5\u0026ndash;12.4 kPa, and \u0026ge;\u0026thinsp;12.5 kPa, respectively.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Metabolic dysfunction-associated steatotic liver disease (MASLD) was characterized by the presence of steatotic liver disease (SLD) with a CAP cut-off value of \u0026ge;\u0026thinsp;248 dB/m, in addition to at least one out of five cardiometabolic risk factors.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e The fibrosis index based on four parameters (FIB-4) was calculated for all participants.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Hyperferritinemia was defined as a serum ferritin level exceeding 300 ng/mL for males and 200 ng/mL for females.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using the Statistical Package for Social Science (SPSS version 26.0 (IBM)). Continuous variables were present as median (interquartile range [IQR]), while categorical data were present as numbers (percentage). Univariate logistic regression analysis was utilized to explore the relationship between hyperferritinemia and host/viral factors of interest, including age, sex, HBV coinfection, HCV viral load, HCV genotype, hepatic fibrosis stage, FIB-4 score, MASLD, ALT quotient, and eGFR level in the entire population. The results were reported as crude odds ratios (ORs) with 95% confidence intervals (CIs). Among participants with MASLD, we further analyzed this association with the aforementioned factors, as well as with T2D and BMI. Multivariate logistic regression analysis was performed for factors with a p-value less than 0.10 in the univariate analysis to identify independent variables associated with hyperferritinemia, and these were reported as adjusted ORs with 95% CIs. Spearman\u0026rsquo;s rank correlation was used to evaluate the correlation between the log\u003csub\u003e10\u003c/sub\u003e value of HBV viral load or log\u003csub\u003e10\u003c/sub\u003e value of HCV viral load and the log\u003csub\u003e10\u003c/sub\u003e serum ferritin level, ALT level and FIB-4 score. Among participants with HBV coinfection, those with a viral load below the LLOQ had their log\u003csub\u003e10\u003c/sub\u003e value of HBV viral load set as 0. All statistical analyses were two-tailed, and statistical significance was defined as a p-value less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eOf 2343 participants diagnosed with chronic HCV infection, 661 were excluded from the study because of decompensated cirrhosis (n\u0026thinsp;=\u0026thinsp;21), a history of HCC (n\u0026thinsp;=\u0026thinsp;75), organ transplantation (n\u0026thinsp;=\u0026thinsp;35), ESKD (n\u0026thinsp;=\u0026thinsp;240), HIV coinfection (n\u0026thinsp;=\u0026thinsp;253), increased alcohol consumption (n\u0026thinsp;=\u0026thinsp;34), and iron deficiency anemia (n\u0026thinsp;=\u0026thinsp;3). The remaining 1682 eligible participants were included in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe median age was 56 years (IQR: 48\u0026ndash;63 years) and 864 (51.4%) participants were males. The median log\u003csub\u003e10\u003c/sub\u003e HCV viral load was 6.07 IU/mL and 991 (58.9%) participants were infected with HCV genotype 1. One hundred forty-four (8.6%) participants were coinfected with HBV. The median log\u003csub\u003e10\u003c/sub\u003e HBV viral load was 0.00 IU/mL (IQR: 0.00-2.73 IU/mL). With regard to LSM, 699 (42.4%), 416 (25.3%), 199 (12.1%), and 333 (20.2%) participants had a fibrosis stage of F0-F1, F2, F3 and F4. MASLD was present in 635 (38.6%) participants, of whom T2D, overweight/obesity, and lean/normal weight were present in 221, 407 and 7 participants. Furthermore, 1294 (76.9%), 1505 (89.5%), and 782 (46.5%) participants had ALT level\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN, an eGFR\u0026thinsp;\u0026gt;\u0026thinsp;60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, and hyperferritinemia (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants (N\u0026thinsp;=\u0026thinsp;1682)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (48\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50 years, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1161 (69.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e864 (51.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBV coinfection, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (8.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV RNA, log\u003c/b\u003e\u003csub\u003e\u003cb\u003e10\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003eIU/mL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.07 (5.37\u0026ndash;6.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV RNA\u0026thinsp;\u0026gt;\u0026thinsp;2,000,000 IU/mL, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e638 (37.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV genotype 1, (%)\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e991 (58.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBV DNA, log\u003c/b\u003e\u003csub\u003e\u003cb\u003e10\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eIU/mL\u003c/b\u003e \u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 (0.00-2.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLSM, kPa\u003c/b\u003e \u003csup\u003e\u003cb\u003ed\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5 (6.1\u0026ndash;11.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis stage (METAVIR), n (%)\u003c/b\u003e \u003csup\u003e\u003cb\u003ee\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF0-F1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e699 (42.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e416 (25.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199 (12.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e333 (20.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFIB-4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.23 (1.42\u0026ndash;3.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFIB-4\u0026thinsp;\u0026gt;\u0026thinsp;3.25, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e515 (30.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCAP, dB/m\u003c/b\u003e \u003csup\u003e\u003cb\u003ed\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e238 (214\u0026ndash;268)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASLD, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e635 (38.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e407 (24.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI, kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3 (23.0-27.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;23 kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1263 (76.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlatelet count, 10\u003c/b\u003e\u003csup\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174 (134\u0026ndash;213)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.96\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin, g/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 (4.1\u0026ndash;4.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal bilirubin, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.7\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAST, U/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (40\u0026ndash;103)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT, U/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86 (51\u0026ndash;146)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN, n (%)\u003c/b\u003e \u003csup\u003e\u003cb\u003ef\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1294 (76.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR, mL/min/1.73m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2 g\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (68\u0026ndash;94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR\u0026thinsp;\u0026ge;\u0026thinsp;60 mL/min/1.73m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2 g\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1505 (89.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFerritin, ng/mL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e231 (131\u0026ndash;400)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHyperferritinemia, n (%)\u003c/b\u003e \u003csup\u003e\u003cb\u003eh\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e782 (46.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eHBV, hepatitis B virus; HCV, hepatitis C virus; RNA, ribonucleic acid; IU, international unit; DNA, deoxyribonucleic acid, LSM, liver stiffness measurement; kPa, kilo Pascal; FIB-4, fibrosis index based on four parameters; CAP, controlled attenuation parameter; dB, decibel; MASLD, metabolic dysfunction-associated steatotic liver disease; T2D, type 2 diabetes; BMI, body mass index; INR, international normalized ratio; AST, aspartate transaminase; ALT, alanine transaminase; ULN, upper limit of normal; eGFR, estimated glomerular filtration rate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ea\u003c/sup\u003e Data are shown in median (interquartile range, IQR) unless otherwise indicated.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003eb\u003c/sup\u003e Participants with HCV genotype 1a, genotype 1b, genotype 1a plus 1b, or unsubtypable genotype 1 were regarded as HCV genotype 1 infection.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ec\u003c/sup\u003e Data was set as 0 for serum HBV DNA level\u0026thinsp;\u0026lt;\u0026thinsp;lower limit of quantification (LLOQ)21\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ed\u003c/sup\u003e Assessed by vibration-controlled transient elastography (VETE). Thirty-five participants without valid or reliable LSM or CAP were excluded from the analysis.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ee\u003c/sup\u003e The cutoff values of LSM for a hepatic fibrosis stage of F0-1, F2, F3, and F4 are \u0026le;\u0026thinsp;7.0 kPa, 7.1\u0026ndash;9.4 kPa, 9.5\u0026ndash;12.4 kPa, and \u0026ge;\u0026thinsp;12.5 kPa, respectively.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ef\u003c/sup\u003e The ULN of ALT are 30 U/L for males and 19 U/L for females, respectively.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003eg\u003c/sup\u003e Calculated by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003eh\u003c/sup\u003e Serum ferritin levels are \u0026gt;\u0026thinsp;300 ng/mL for males and \u0026gt;\u0026thinsp;200 ng/mL for females, respectively.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePre-treatment factors associated with hyperferritinemia in the entire population\u003c/h2\u003e \u003cp\u003eIn the univariate logistic regression analysis, age\u0026thinsp;\u0026gt;\u0026thinsp;50 year (crude OR: 1.73; 95% CI: 1.40\u0026ndash;2.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), fibrosis stage\u0026thinsp;\u0026ge;\u0026thinsp;F3 (crude OR: 2.22; 95% CI: 1.80\u0026ndash;2.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FIB-4 score\u0026thinsp;\u0026gt;\u0026thinsp;3.25 (crude OR: 2.39; 95% CI: 1.93\u0026ndash;2.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of MASLD (crude OR: 1.51; 95% CI: 1.23\u0026ndash;1.84, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ALT\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN (crude OR: 3.55; 95% CI: 2.75\u0026ndash;4.59, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and eGFR\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e (crude OR: 1.38; 95% CI: 1.01\u0026ndash;1.89, p\u0026thinsp;=\u0026thinsp;0.04) were significantly associated with hyperferritinemia, while sex, HBV coinfection, HCV RNA at a cut-off value of 2,000,000 IU/mL, and HCV genotype were not associated with hyperferritinemia (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate regression analysis for factors associated with hyperferritinemia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMultivariate analysis \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHyperferritinemia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCrude OR (95% CI) \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;900) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;782) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e573 (63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e588 (75.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.73 (1.40\u0026ndash;2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.38 (1.09\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e327 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e194 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e472 (49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e392 (50.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.75\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e428 (50.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e390 (49.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBV coinfection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13 (0.80\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e827 (91.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e711 (90.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV RNA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2,000,000 IU/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e337 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e301 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.86\u0026ndash;1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2,000,000 IU/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e563 (62.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e481 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV genotype 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e514 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e477 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17 (0.97\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e386 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e305 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis stage\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; F3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e320 (41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.22 (1.80\u0026ndash;2.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.36 (1.04\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; F3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e664 (75.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e451 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFIB-4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e199 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e316 40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.39 (1.93\u0026ndash;2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.46 (1.11\u0026ndash;1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e701 (77.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e466 (59.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASLD\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e298 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e337 (43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.51 (1.23\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.43 (1.12\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e578 (66.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e434 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT, ULN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 folds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e606 (67.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e688 (88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.55 (2.75\u0026ndash;4.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.87 (2.20\u0026ndash;3.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2 folds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e294 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR, mL/min/1.73m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 (1.01\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e818 (90.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e687 (87.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eOR, odds ration; CI, confidence interval; HBV, hepatitis B virus; HCV, hepatitis C virus; RNA, ribonucleic acid; IU, international unit; FIB-4, fibrosis index based on four parameters; MASLD, metabolic dysfunction-associated steatotic liver disease; ALT, alanine transaminase; ULN, upper limit of normal; eGFR; estimated glomerular filtration rate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e Thirty-five participants without valid or reliable LSM or CAP were excluded from the univariate and multivariate analyses\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003e Values in the corresponding columns are shown as numbers (percentages) unless otherwise indicated.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ec\u003c/sup\u003e Factors with a p value of \u0026lt;\u0026thinsp;0.10 in univariate analysis entered multivariate analysis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis identified age\u0026thinsp;\u0026gt;\u0026thinsp;50 year (adjusted OR: 1.38; 95% CI: 1.09\u0026ndash;1.74, p\u0026thinsp;=\u0026thinsp;0.008), fibrosis stage\u0026thinsp;\u0026ge;\u0026thinsp;F3 (adjusted OR: 1.36; 95% CI: 1.04\u0026ndash;1.77, p\u0026thinsp;=\u0026thinsp;0.02), FIB-4 score\u0026thinsp;\u0026gt;\u0026thinsp;3.25 (adjusted OR: 1.46; 95% CI: 1.11\u0026ndash;1.92, p\u0026thinsp;=\u0026thinsp;0.01), presence of MASLD (adjusted OR: 1.43; 95% CI: 1.12\u0026ndash;1.76, p\u0026thinsp;=\u0026thinsp;0.001), ALT\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN (adjusted OR: 2.87; 95% CI: 2.20\u0026ndash;3.75, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent factors associated with hyperferritinemia (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePre-treatment factors associated with hyperferritinemia in participants with MASLD\u003c/h2\u003e \u003cp\u003eUnivariate logistic regression analysis revealed that age\u0026thinsp;\u0026gt;\u0026thinsp;50 years (crude OR: 1.68; 95% CI: 1.20\u0026ndash;2.35, p\u0026thinsp;=\u0026thinsp;0.003), fibrosis stage\u0026thinsp;\u0026ge;\u0026thinsp;F3 (crude OR: 1.90; 95% CI: 1.38\u0026ndash;2.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FIB-4 score\u0026thinsp;\u0026gt;\u0026thinsp;3.25 (crude OR: 2.29; 95% CI: 1.62\u0026ndash;3.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ALT\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN (crude OR: 3.12; 95% CI: 2.07\u0026ndash;4.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with hyperferritinemia among participants with concurrent MASLD. In contrast, T2D, BMI at a cut-off of 23 kg/m\u003csup\u003e2\u003c/sup\u003e, sex, HBV coinfection, HCV RNA at a cut-off value of 2,000,000 IU/mL, HCV genotype, and eGFR at a cut-off value of 60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e were not associated with hyperferritinemia (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate regression analysis for factors associated with hyperferritinemia in participants with MASLD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHyperferritinemia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCrude OR (95% CI) \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;298) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;337) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT2D\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (0.89\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e202 (67.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e212 (62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e292 (98.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e324 (96.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51 (0.19\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e113 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.68 (1.20\u0026ndash;2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.24 (0.87\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e185 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e247 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e178 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82 (0.60\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e159 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBV coinfection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28 (0.76\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e271 (90.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e299 (88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV RNA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2,000,000 IU/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e122 (36.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80 (0.58\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2,000,000 IU/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e174 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCV genotype 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169 (56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e202 (59.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.83\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e129 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e135 (40.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; F3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e160 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.90 (1.38\u0026ndash;2.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20 (0.81\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; F3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e202 (67.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e177 (52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFIB-4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e139 (41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.29 (1.62\u0026ndash;3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.62 (1.05\u0026ndash;2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e228 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e198 (58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT, ULN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 folds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e208 (69.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e296 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.12 (2.07\u0026ndash;4.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.55 (1.67\u0026ndash;3.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2 folds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR, mL/min/1.73m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 (0.65\u0026ndash;1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e259 (86.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e292 (86.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eOR, odds ration; CI, confidence interval; MASLD, metabolic dysfunction-associated steatotic liver disease; T2D, type 2 diabetes; BMI, body mass index; HBV, hepatitis B virus; HCV, hepatitis C virus; RNA, ribonucleic acid; IU, international unit; FIB-4, fibrosis index based on four parameters; ALT, alanine transaminase; ULN, upper limit of normal; eGFR; estimated glomerular filtration rate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e Values in the corresponding columns are shown as numbers (percentages) unless otherwise indicated.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003e Factors with a p value of \u0026lt;\u0026thinsp;0.10 in univariate analysis entered multivariate analysis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis identified FIB-4 score\u0026thinsp;\u0026gt;\u0026thinsp;3.25 (adjusted OR: 1.62; 95% CI: 1.05\u0026ndash;2.50, p\u0026thinsp;=\u0026thinsp;0.03) and ALT\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN (adjusted OR: 2.55; 95% CI: 1.67\u0026ndash;3.90, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent factors associated with hyperferritinemia (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation of serum HBV DNA with ferritin, ALT and FIB-4\u003c/h2\u003e \u003cp\u003eAmong the 144 participants with HBV coinfection, 74 (53.5%) had an HBV DNA level\u0026thinsp;\u0026lt;\u0026thinsp;LLOQ and 40 (28.8%) had an HBV DNA level between LLOQ and 2000 IU/mL. After log\u003csub\u003e10\u003c/sub\u003e transforming serum HBV DNA and ferritin levels, the Spearman\u0026rsquo;s rank correlation coefficient (\u003cem\u003er\u003c/em\u003e) between log\u003csub\u003e10\u003c/sub\u003e HBV DNA level and log\u003csub\u003e10\u003c/sub\u003e ferritin level was \u0026minus;\u0026thinsp;0.025 (p\u0026thinsp;=\u0026thinsp;0.81) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Regarding hepatic necroinflammation, the Spearman\u0026rsquo;s rank correlation coefficients (\u003cem\u003er\u003c/em\u003e) were \u0026minus;\u0026thinsp;0.099 (p\u0026thinsp;=\u0026thinsp;0.24) between log\u003csub\u003e10\u003c/sub\u003e HBV DNA level and ALT level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Moreover, the Spearman\u0026rsquo;s rank correlation coefficients (\u003cem\u003er\u003c/em\u003e) were \u0026minus;\u0026thinsp;0.140 (p\u0026thinsp;=\u0026thinsp;0.09) between log\u003csub\u003e10\u003c/sub\u003e HBV DNA level and FIB-4 score (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation of serum HCV DNA with ferritin, ALT and FIB-4\u003c/h2\u003e \u003cp\u003eThe Spearman\u0026rsquo;s rank correlation coefficient (\u003cem\u003er\u003c/em\u003e) between log\u003csub\u003e10\u003c/sub\u003e HCV RNA level and log\u003csub\u003e10\u003c/sub\u003e ferritin level was 0.002 (p\u0026thinsp;=\u0026thinsp;0.92) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Regarding hepatic necroinflammation, the Spearman\u0026rsquo;s rank correlation coefficients (\u003cem\u003er\u003c/em\u003e) were \u0026minus;\u0026thinsp;0.025 (p\u0026thinsp;=\u0026thinsp;0.31) between log\u003csub\u003e10\u003c/sub\u003e HCV RNA level and ALT level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Moreover, the Spearman\u0026rsquo;s rank correlation coefficients (\u003cem\u003er\u003c/em\u003e) were \u0026minus;\u0026thinsp;0.043 (p\u0026thinsp;=\u0026thinsp;0.08) between log\u003csub\u003e10\u003c/sub\u003e HCV RNA level and FIB-4 score (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study, encompassing a sample size of 1,682 patients, represents the most extensive population analyzed to date in examining the factors and their correlation with pre-treatment ferritin levels in patients with HCV. To ensure the robustness of our study and minimize confounding variables, we diligently excluded patients with decompensated cirrhosis, a history of HCC, ESKD, HIV coinfection, organ transplantation, heightened alcohol consumption, and iron deficiency anemia that enhanced the reliability and validity.\u003c/p\u003e \u003cp\u003eWe demonstrated that individuals aged\u0026thinsp;\u0026gt;\u0026thinsp;50 years and those with ALT levels exceeding\u0026thinsp;\u0026gt;\u0026thinsp;2 folds ULN were more likely to exhibit hyperferritinemia, consistent with previous researches.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Conversely, sex and eGFR at a cut-off of 60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e were not found to be correlated with hyperferritinemia. The apparent discrepancy in the influence of eGFR on ferritin dynamics compared to earlier reports may be attributed to our exclusion of participants with ESKD and the inclusion of a limited number of participants with an eGFR below 60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, who were susceptible to hyperferritinemia.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePatients with HCV are at risk of developing insulin resistance, which can lead to MS.\u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e The prevalence of NAFLD among individuals with HCV is estimated to be as high as 55%, with a range spanning from 40\u0026ndash;86%, influenced by the distribution of MS and HCV genotypes.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e According to the diagnostic criteria of MASLD, an updated nomenclature aimed at encompassing a broader spectrum of etiologies for steatotic liver disease, our population exhibits a prevalence rate of MASLD of 38.6%.\u003csup\u003e20\u003c/sup\u003e Within MASLD alone, there is a notable correlation between hyperferritinemia and the severity of liver fibrosis.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e While no studies have specifically examined the prevalence rate of hyperferritinemia in individuals with concurrent HCV and MASLD, it can be inferred that this population likely exhibits greater rates compared to HCV or MASLD alone. The prevalence rate of hyperferritinemia among our patients reached 53%, significantly higher than the reported prevalence rates of approximately 30% in subjects with MASLD alone.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eChronic HCV infection induces hepatocyte injury, accompanied by the accumulation of extracellular matrix (ECM) proteins, ultimately resulting in accelerating hepatic fibrotic. The process of fibrotic change is dynamic, with later stages indicating increased severity.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e While the stage of hepatic fibrosis and hyperferritinemia indicate the severity of hepatocyte damage, previous studies have provided limited evidence linking the severity of hepatic fibrosis to hyperferritinemia. Our study is the first to demonstrate a positive correlation between hyperferritinemia and the severity of hepatic fibrosis, utilizing two noninvasive indices, the FIB-4 scores and LSMs, as assessment tools. Univariate analysis revealed either higher FIB-4 scores (\u0026gt;\u0026thinsp;3.25) or LSMs (\u0026ge;\u0026thinsp;9.5 kPa) were associated with hyperferritinemia in both the entire population and those with MASLD. Due to the high collinearity between the FIB-4 score and LSM, and a relatively smaller sample size compared to the entire population, LSM was excluded as an independent risk factor in the multivariate model for association with hyperferritinemia among participants with MASLD. We also demonstrated that within the context of MASLD, T2D or obesity did not increase the risk of hyperferritinemia. This implies that the presence of MS, regardless of the potential contributing factors, may lead to systemic inflammation, thus resulting in hyperferritinemia.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCurrent evidence indicates that neither the HCV vial load nor genotype correlates with ALT levels or histological presentation, including necroinflammation or fibrosis. This is evident from our observations, showing no correlation between either ALT level or FIB-4 score with HCV viral load.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e However, to date, no studies have investigated the correlation of hyperferritinemia with HCV viral load or genotype. This study is the first to demonstrate a lack of significant correlation between HCV viral load/genotype and hyperferritinemia.\u003c/p\u003e \u003cp\u003eWith regard to HBV infection, prior studies hypothesized that active HBV replication may result in elevated serum levels of iron and ferritin.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e However, our participants with HBV coinfection, characterized by an almost negligible median log\u003csub\u003e10\u003c/sub\u003e HBV viral load of 0 and more than half of them without detectable HBV DNA, demonstrated that neither HBsAg nor the viral load were associated with hyperferritinemia. Additionally, the median log\u003csub\u003e10\u003c/sub\u003e HBV viral load did not show a significant association with ALT levels or FIB-4 scores. While our observation fails to confirm the proposed hypothesis, the lack of association of hyperferritinemia with HBV DNA due to the suppression of HBV load from active HCV replication may not be extrapolated to individuals with HBV alone, where the HBV viral load tends to be higher than that in HBV/HCV-coinfected subjects.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAlthough the risk of hyperferritinemia is consistently increased among individuals with chronic HCV infection, it remains unclear if there is a dosing effect of viral load on serum ferritin levels. In contrast to the low HBV load in our coinfected participants, most of whom had active HCV replication, as evidenced by a high median viral load. However, the HCV load did not exhibit a significant association with serum ferritin levels, ALT levels, or FIB-4 scores. Based on the similar trends observed in the association of HBV or HCV load with serum ferritin levels, we deduce that rather than direct virological effects, the serum level of ferritin is augmented indirectly through immune responses to HBV or HCV.\u003c/p\u003e \u003cp\u003eDespite enrolling a sizable number of participants and meticulously excluding potential confounders to mitigate the imprecise risk estimates, several limitations are present in the current study. Firstly, this study was conducted exclusively in East Asians, and external validation should be conducted to confirm our findings in other ethnic populations. Secondly, we did not conduct HFE C282Y and H63D testing to exclude participants with HFE hemochromatosis. However, the presence of C282Y homozygotes and C282Y/H63D heterozygote in Asians is rare, rendering the genetic testing unnecessary.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Thirdly, we did not analyze the serum iron and transferrin saturation because only a minority of subjects with chronic viral hepatitis exhibit these derangements.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn conclusion, our study reveals that hyperferritinemia in patients with chronic HCV infection is primarily influenced by host factors such as age, severity of hepatic fibrosis, MASLD, and ALT levels, rather than viral factors. While viral factors may not directly predispose to hyperferritinemia, vigilant management of HBV and HCV using effective antiviral therapies remains essential to indirectly mitigate hyperferritinemia by reducing viral-induced hepatic necroinflammation and fibrosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors thank Hui-Ju Lin and Pin-Chin Huang for clinical data management; the 7\u003csup\u003eth\u003c/sup\u003e Core Lab of the National Taiwan University Hospital, and the 1\u003csup\u003est\u003c/sup\u003e Common Laboratory of the National Taiwan University Hospital, Yun-Lin Branch, for the instrumental and technical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eData curation: Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eFormal analysis: Yu-Ping Chang, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eInvestigation: Yu-Ping Chang,\u0026nbsp;Chiuan-Bo Huang, Jia-Horng Kao, Tung-Hung Su, Shang-Chin Huang, Tai-Chung Tseng, Pei-Jer Chen, Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eMethodology: Yu-Ping Chang, Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eProject administration: Yu-Ping Chang, Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eResources: Yu-Ping Chang,\u0026nbsp;Chiuan-Bo Huang, Jia-Horng Kao, Tung-Hung Su, Shang-Chin Huang, Tai-Chung Tseng, Pei-Jer Chen, Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eSoftware: Yu-Ping Chang, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eSupervision: Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eValidation: Yu-Ping Chang, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eVisualization: Yu-Ping Chang, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: Yu-Ping Chang, Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: Yu-Ping Chang,\u0026nbsp;Chiuan-Bo Huang, Jia-Horng Kao, Tung-Hung Su, Shang-Chin Huang, Tai-Chung Tseng, Pei-Jer Chen, Chun-Jen Liu, Chen-Hua Liu.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe study was supported by the National Taiwan University Hospital (112-IF0004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u0026nbsp;\u003c/strong\u003eAll authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCui, F. \u003cem\u003eet al.\u003c/em\u003e Global reporting of progress towards elimination of hepatitis B and hepatitis C. 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J Gastroenterol Hepatol 16, 636\u0026ndash;640, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1046/j.1440-1746.2001.02494.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1440-1746.2001.02494.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"hepatitis C virus, hepatitis B virus, hyperferritinemia, metabolic dysfunction-associated steatotic liver disease","lastPublishedDoi":"10.21203/rs.3.rs-4445076/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4445076/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePre-treatment host and viral factors may affect serum ferritin levels in patients with hepatitis C virus (HCV) infection. We delineated pre-treatment factors associated with hyperferritinemia in these patients. 1682 eligible patients underwent pre-treatment assessment for serum ferritin and various host/viral factors. Univariate and multivariate logistic regression analyses were conducted to evaluate factors associated with hyperferritinemia. Multivariate logistic regression analyses revealed that age\u0026thinsp;\u0026gt;\u0026thinsp;50 years (adjusted odds ratio [OR]: 1.38 (95% confidence interval [CI]: 1.09\u0026ndash;1.74), p\u0026thinsp;=\u0026thinsp;0.008), fibrosis stage\u0026thinsp;\u0026ge;\u0026thinsp;F3 (adjusted OR: 1.36 (95% CI: 1.04\u0026ndash;1.77), p\u0026thinsp;=\u0026thinsp;0.02), fibrosis index based on four parameters (FIB-4)\u0026thinsp;\u0026gt;\u0026thinsp;3.25 (adjusted OR: 1.46 (95% CI: 1.11\u0026ndash;1.92), p\u0026thinsp;=\u0026thinsp;0.01), presence of metabolic dysfunction-associated steatotic liver disease (MASLD) (adjusted OR: 1.43 (95% CI: 1.21\u0026ndash;1.76), p\u0026thinsp;=\u0026thinsp;0.001), and alanine transaminase (ALT)\u0026thinsp;\u0026gt;\u0026thinsp;2 folds upper limit of normal (ULN) (adjusted OR: 2.87 (95% CI: 2.20\u0026ndash;3.75), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were associated hyperferritinemia. The log\u003csub\u003e10\u003c/sub\u003e value of HBV or HCV viral load was not associated with the log\u003csub\u003e10\u003c/sub\u003e value of ferritin level (Spearman\u0026rsquo;s rank correlation coefficient: -0.025, p\u0026thinsp;=\u0026thinsp;0.81 and 0.002, p\u0026thinsp;=\u0026thinsp;0.92). In conclusion, host factors, rather than viral factors, are associated with hyperferritinemia in patients with HCV.\u003c/p\u003e","manuscriptTitle":"Factors associated with pre-treatment hyperferritinemia in patients with chronic hepatitis C virus infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-13 02:26:03","doi":"10.21203/rs.3.rs-4445076/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-17T04:11:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-02T09:27:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211492692295450785287599889043311825948","date":"2024-06-01T14:02:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-01T13:22:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-01T13:20:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-29T11:35:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-29T11:28:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-19T16:23:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e0d74e1c-1e78-4713-a6ef-da8dae42c9c8","owner":[],"postedDate":"June 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33128868,"name":"Biological sciences/Microbiology"},{"id":33128869,"name":"Health sciences/Gastroenterology"}],"tags":[],"updatedAt":"2024-08-26T16:08:10+00:00","versionOfRecord":{"articleIdentity":"rs-4445076","link":"https://doi.org/10.1038/s41598-024-70233-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-19 15:56:56","publishedOnDateReadable":"August 19th, 2024"},"versionCreatedAt":"2024-06-13 02:26:03","video":"","vorDoi":"10.1038/s41598-024-70233-9","vorDoiUrl":"https://doi.org/10.1038/s41598-024-70233-9","workflowStages":[]},"version":"v1","identity":"rs-4445076","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4445076","identity":"rs-4445076","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}