Abstract
Objective
This study aimed to investigate the short-term effects of pemafibrate (PEMA) on the Fibrosis-4 index (FIB-4) and Aspartate Aminotransferase to Platelet Ratio Index (APRI) across three subgroups stratified according to FIB-4 for assessing the risk of liver fibrosis in patients with type 2 diabetes (T2D) and hypertriglyceridemia.
Methods
A total of 114 patients were stratified into three subgroups based on their FIB-4 score at the initiation of PEMA, following the FIB-4 classification: Group 1 (G1) (FIB-4＜1.30, n=46), Group 2 (G2) (FIB-4 1.30 to ＜2.67, n=56), and Group 3 (G3) (FIB-4 ≥2.67, n=12). We evaluated the changes in FIB-4 and APRI three months after the initiation of PEMA in each subgroup. Subsequently, we compared the changes (Δ) in FIB-4 and APRI scores across the three subgroups. Additionally, we investigated the baseline parameters and changes in these parameters correlated with ΔFIB-4.
Results
The FIB-4 index exhibited a significant increase in G1 (p=0.003) but decrease in G3 (p=0.041). The APRI showed a significant reduction in both G2 (p＜0.001) and G3 (p=0.034). ΔFIB-4 in G3 was significantly greater than that observed in G1 (p＜0.001) and G2 (p=0.026), whereas ΔAPRI in G3 was significantly higher than that in G1 (p=0.002). ΔFIB-4 was inversely correlated with baseline FIB-4 and positively correlated with Δγ-glutamyl transpeptidase.
Conclusion
The short-term effect of PEMA on liver fibrosis markers was more pronounced in patients with T2D and hypertriglyceridemia who exhibited elevated baseline FIB-4 values.
Keywords: type 2 diabetes, hypertriglyceridemia, liver fibrosis marker, pemafibrate
Introduction
Hepatic steatosis in individuals with type 2 diabetes mellitus
Fatty liver is present in 70% of individuals with type 2 diabetes (T2D) (1), and non-alcoholic fatty liver disease (NAFLD) has been shown to have more than double the risk of developing T2D (2), underscoring a strong interrelationship between the two conditions. Furthermore, the concurrence of diabetes and NAFLD serves as a significant risk factor for the advancement of liver fibrosis (3) while also increasing the likelihood of chronic kidney disease (CKD) (4), liver-related complications, and overall mortality (5). Individuals with both diabetes and NAFLD exhibit a two-fold increased risk of cardiovascular disease (CVD) in comparison to diabetic patients without NAFLD (6), indicating the compounding impact of NAFLD on CVD risk in T2D patients. In May 2020, fatty liver disease linked to metabolic dysfunction was reclassified as metabolic dysfunction-associated fatty liver disease (MAFLD) (7), with revised diagnostic criteria encompassing the presence of fatty liver alongside “obesity," “T2D," or “two or more metabolic abnormalities," irrespective of alcohol intake (8). Although a definitive diagnosis of NAFLD typically requires a liver biopsy, MAFLD can be identified through imaging modalities, such as ultrasound and computed tomography scans, as well as biomarker analyses (8). Given the non-invasive nature of these methods, MAFLD detection is anticipated to become more proactive and widespread. Concerns have been raised that the term “fatty” could carry a stigmatizing connotation, leading to the subsequent renaming of MAFLD as metabolic dysfunction-associated steatotic liver disease (MASLD) (9).
The prognostic and predictive utility of liver fibrosis markers
Liver fibrosis is recognized as a critical determinant of liver-related mortality and the overall prognosis (10,11). Noninvasive assessment methods for liver fibrosis include the NAFLD fibrosis score (NFS) (12), Fibrosis-4 index (FIB-4) (13,14), and aspartate aminotransferase-to-platelet ratio index (APRI) (15). FIB-4 has been identified as a predictive marker for ischemic heart disease in individuals with fatty liver (16), and as a risk factor for cardiovascular events and all-cause mortality in patients with atrial fibrillation (17). The FIB-4, NFS, and APRI scores are correlated with a higher prevalence of heart failure (18), establishing liver fibrosis markers as prognostic indicators not only for liver disease, but also for cardiovascular disease.
The effects of pemafibrate on liver fibrosis markers
Pemafibrate, a pharmacological agent for hypertriglyceridemia, exhibits high selectivity and potency toward peroxisome proliferator-activated receptor α and has been reported to confer superior lipid metabolism enhancement with fewer adverse effects than conventional fibrate formulations (19). Studies have demonstrated that pemafibrate administration in patients with hypertriglyceridemia and either NAFLD (20-22) or MAFLD (23,24) leads to improvements in liver function and fibrosis markers including FIB-4 and APRI. Among patients with T2D, the reduction in FIB-4 after 52 weeks of pemafibrate treatment was more pronounced in those with elevated baseline alanine transaminase (ALT) levels (exceeding twice the upper limit of normal) than in those with baseline ALT levels within the normal range (25). To date, no studies have investigated the short-term effects of pemafibrate administration on the liver function and fibrosis markers in patients with T2D. Therefore, this study aimed to address this gap.
Materials and Methods
1. Study design
This single-center, retrospective, observational study used a prospectively maintained database. The study adhered to the ethical principles of the Declaration of Helsinki and the protocol was approved by the Minoh City Hospital Ethics Committee (No. R0610B51). Informed consent was obtained using an opt-out procedure.
2. Subjects
This study included 114 consecutive patients with T2D and hypertriglyceridemia who were initiated on pemafibrate between April 2019 and May 2024. We excluded patients younger than 20 years of age; patients with other chronic liver diseases, such as viral hepatitis and autoimmune hepatitis, patients for whom any changes were made to antidiabetic, antihypertensive, or lipid-lowering medications within the three months preceding or following the initiation of pemafibrate; patients who discontinued pemafibrate within three months after the initiation of pemafibrate; patients with incomplete data; and patients deemed unsuitable for the study by the attending physician. Fig. 1 shows the flowchart of the study population.
Figure 1.
Flowchart of the study population.
3. Pemafibrate dosage
Pemafibrate was initiated primarily at a dose of 0.2 mg/day, although some patients were started at a dose of 0.1 mg/day at the discretion of their physician.
4. Data collection
We extracted demographic information, including age, sex, and body mass index, and clinical data such as medical history, comorbidities, medications, and laboratory data from medical records. Baseline laboratory data were evaluated at the initiation of the pemafibrate treatment. The patients were monitored at least monthly by the attending physician, and blood tests were performed at each visit. FIB-4 and APRI values at baseline and three months after the initiation of treatment were analyzed.
5. Classification of subjects
A total of 114 patients with T2DM and hypertriglyceridemia were classified into three subgroups based on their FIB-4 at the initiation of pemafibrate treatment in accordance with the FIB-4 classification, which is a tool for assessing the risk of liver fibrosis in patients with MASLD, as outlined in Evidence-based Clinical Practice Guidelines for Nonalcoholic Fatty Liver Disease/Nonalcoholic Steatohepatitis 2020 (26): Group 1 (G1) (low risk, FIB-4＜1.30, n=46), Group 2 (G2) (middle risk, FIB-4 1.30 to ＜2.67, n=56), and Group 3 (G3) (high risk, FIB-4 ≥2.67, n=12).
6. Outcomes
We evaluated the changes in FIB-4 or APRI three months after pemafibrate initiation in each subgroup. Subsequently, we compared the changes (Δ) in FIB-4 and APRI scores across the three subgroups. Additionally, we investigated the baseline parameters and changes (Δ) in the parameters correlated with ΔFIB-4.
7. Statistical analysis
Continuous variables are presented as medians [interquartile ranges], whereas categorical data are expressed as percentages. Statistical significance was assessed using the Wilcoxon signed-rank test, Kruskal-Wallis test, and Steel-Dwass test for continuous variables, and Fisher's exact test for categorical variables. Univariate and multivariate analyses were performed using a linear regression model to assess baseline parameters and changes in parameters associated with ΔFIB-4. A multivariate analysis of baseline parameters associated with ΔFIB-4 was adjusted to account for body mass index (BMI), diabetes duration, estimated glomerular filtration rate (eGFR), hemoglobin A1c (HbA1c), serum albumin, γ-glutamyl transpeptidase (γ-GTP), triglycerides, and the FIB-4 index. Meanwhile, the multivariate analysis of changes in parameters associated with ΔFIB-4 was adjusted to account for ΔeGFR, ΔHbA1c, Δserum albumin, Δtotal bilirubin, Δγ-GTP, Δlow-density lipoprotein cholesterol (LDL-C), Δhigh-density lipoprotein cholesterol (HDL-C), and Δtriglyceride. p values of ＜0.05 were considered to indicate statistical significance. All analyses were conducted using the Bell Curve for Excel statistical software program (ver. 4.08, Bell Curve for Excel, Social Survey Research Information, Tokyo, Japan).
Results
1. Patient characteristics at the initiation of pemafibrate across the three groups
Table 1 presents the patient characteristics across the three subgroups, classified based on their FIB-4 score at the initiation of pemafibrate treatment, in accordance with the FIB-4 classification for assessing the risk of liver fibrosis. Three patients within the population transitioned from fenofibrate to pemafibrate, one in group G2 and two in group G3. The median age of all patients was 68 (56, 74) years, and 71% of the patients were men. The median body mass index was 25.8 (range: 23.9, 28.8) kg/m2. The median FIB-4 and APRI level were 1.49 (range: 1.04, 2.02) and 0.32 (range: 0.22, and 0.48), respectively. The median platelet count and aspartate aminotransferase (AST), ALT, and γ-GTP levels were 21.3 (range: 17.9, 24.5)×104/μL, 25 (range: 18, 35) IU/L, 27 (range: 20, 46) IU/L, and 45 (range: 27, 89) IU/L, respectively. The median initial dose of pemafibrate was 0.2 (range: 0.1, 0.2) mg/day. The administration rates of sodium-glucose cotransporter-2 inhibitor (SGLT2i), angiotensin-converting enzyme inhibitor (ACEi)/angiotensin II receptor blocker (ARB) and glucagon-like peptide-1 receptor agonist (GLP-1Ra) were 58%, 57%, and 25%, respectively. Significant differences across the three subgroups were observed in the APRI, age, duration of diabetes, smoking status, platelet count, eGFR, AST levels, LDL-C, and the prevalence of biguanide administration.
Table 1.
Baseline Characteristics of Patients at the Initiation of Pemafibrate, Stratified into Three Subgroups according to Their FIB-4 Index.
| Clinical data | Overall n=114 | FIB-4 index | p value | ||
|---|---|---|---|---|---|
|
G1 n=46
<1.30 |
G2 n=56
1.30 ≤, <2.67 |
G3 n=12
2.67 ≤ |
|||
| FIB-4 index | 1.49 [1.04, 2.02] | 0.99 [0.78, 1.12] | 1.81 [1.56, 2.14] | 3.17 [2.79, 3.46] | - |
| APRI | 0.32 [0.22, 0.48] | 0.23 [0.17, 0.34] | 0.36 [0.27, 0.49] | 0.69 [0.49, 0.99] | <0.001 |
| Pemafibrate dosage (mg/day) | 0.2 [0.1, 0.2] | 0.2 [0.1, 0.2] | 0.2 [0.1, 0.2] | 0.2 [0.1, 0.2] | 0.86 |
| Age (years) | 68 [56, 74] | 59 [52, 67] | 71 [63, 78] | 75 [67, 81] | <0.001 |
| Male | 81 (71%) | 35 (76%) | 39 (70%) | 7 (58%) | 0.46 |
| Body mass index (kg/m2) | 25.8 [23.9, 28.8] | 26.2 [23.9, 30.5] | 25.5 [23.8, 28.2] | 25.3 [23.2, 28.4] | 0.68 |
| Systolic blood pressure (mmHg) | 131 [120, 138] | 127 [118, 140] | 131 [120, 137] | 135 [130, 143] | 0.21 |
| Heart rate (bpm) | 81 [72, 90] | 83 [72, 91] | 82 [72, 89] | 77 [67, 89] | 0.62 |
| Duration of diabetes (years) | 7 [2, 17] | 3 [1, 12] | 10 [3, 20] | 10 [4, 16] | 0.022 |
| Hypertension | 94 (82%) | 34 (74%) | 51 (91%) | 9 (75%) | 0.059 |
| Chronic kidney disease | 45 (39%) | 14 (30%) | 24 (43%) | 7 (58%) | 0.16 |
| Current smoker | 16 (14%) | 11 (24%) | 5 (9%) | 0 (0%) | 0.032 |
| Coronary artery disease | 12 (11%) | 5 (11%) | 5 (9%) | 2 (17%) | 0.73 |
| Laboratory data | |||||
| Hemoglobin (g/dL) | 14.8 [13.8, 15.9] | 15.3 [13.7, 16.1] | 14.8 [13.9, 15.7] | 13.7 [12.5, 15.4] | 0.12 |
| Platelet (×104/μL) | 21.3 [17.9, 24.5] | 24.6 [22.4, 27.3] | 19.5 [16.9, 22.2] | 16.8 [15.0, 18.9] | <0.001 |
| HbA1c (%) | 7.6 [6.7, 8.5] | 7.8 [6.9, 8.8] | 7.3 [6.6, 8.3] | 7.9 [7.1, 9.5] | 0.25 |
| eGFR (mL/min/1.73 m2) | 65 [52, 80] | 73 [52, 90] | 63 [51, 73] | 54 [39, 77] | 0.031 |
| serum Albumin (g/dL) | 4.2 [4.0, 4.5] | 4.2 [4.0, 4.5] | 4.2 [4.0, 4.4] | 4.4 [4.2, 4.6] | 0.20 |
| Uric acid (mg/dL) | 5.6 [4.6, 6.5] | 5.3 [4.4, 6.4] | 5.5 [4.9, 6.6] | 5.8 [5.5, 7.2] | 0.16 |
| AST (IU/L) | 25 [18, 35] | 21 [16, 32] | 26 [20, 35] | 46 [30, 57] | <0.001 |
| ALT (IU/L) | 27 [20, 46] | 28 [20, 52] | 26 [18, 40] | 28 [24, 51] | 0.53 |
| γ-GTP (IU/L) | 45 [27, 89] | 45 [32, 76] | 43 [23, 82] | 82 [45, 128] | 0.20 |
| Total bilirubin (mg/dL) | 0.54 [0.40, 0.73] | 0.50 [0.40, 0.76] | 0.54 [0.42, 0.73] | 0.61 [0.39, 0.71] | 0.99 |
| LDL-cholesterol (mg/dL) | 97 [71, 121] | 108 [83, 135] | 85 [61, 112] | 97 [68, 127] | 0.037 |
| non-HDL-cholesterol (mg/dL) | 158 [127, 187] | 168 [140, 195] | 145 [121, 183] | 153 [131, 184] | 0.14 |
| HDL-cholesterol (mg/dL) | 47 [40, 57] | 47 [42, 57] | 46 [38, 58] | 48 [42, 51] | 0.88 |
| Triglyceride (mg/dL) | 305 [224, 392] | 307 [264, 386] | 300 [213, 508] | 298 [167, 332] | 0.46 |
| C-reactive protein (mg/dL) | 0.12 [0.08, 0.24] | 0.12 [0.08, 0.22] | 0.12 [0.06, 0.25] | 0.12 [0.08, 0.16] | 0.87 |
| Medication | |||||
| ACEi/ARB | 65 (57%) | 23 (50%) | 35 (63%) | 7 (58%) | 0.44 |
| β blocker | 21 (18%) | 10 (22%) | 14 (25%) | 1 (8%) | 0.45 |
| MRA | 18 (16%) | 6 (13%) | 7 (13%) | 1 (8%) | 0.90 |
| Biguanide | 54 (47%) | 26 (57%) | 26 (46%) | 2 (17%) | 0.047 |
| DPP-4i | 57 (50%) | 18 (39%) | 32 (57%) | 7 (58%) | 0.94 |
| GLP-1Ra | 29 (25%) | 14 (30%) | 12 (21%) | 3 (25%) | 0.58 |
| SGLT2i | 66 (58%) | 26 (57%) | 35 (63%) | 5 (42%) | 0.40 |
| Statin | 70 (61%) | 29 (63%) | 33 (59%) | 8 (67%) | 0.84 |
| Ezetimib | 32 (28%) | 13 (28%) | 13 (23%) | 6 (50%) | 0.17 |
| Eicosapentaenoic acid | 5 (4%) | 1 (2%) | 4 (7%) | 0 (0%) | 0.35 |
Continuous variables are presented as median [interquartile range]. Categorical data are presented as n (%). Tests for significance were conducted using the Kruskal-Wallis test for continuous variables and Fisher’s exact test for categorical data. ACEi: angiotensin-convertingenzyme inhibitor, ALT: alanine transaminase, APRI: aspartate aminotransferase to platelet ratio index, ARB: angiotensin II receptor blocker, AST: aspartate aminotransferase, DPP-4i: dipeptidyl peptidase 4 inhibitor, eGFR: estimated glomerular filtration rate, FIB-4 index: fibrosis-4 index, GLP-1Ra: glucagon-like peptide-1 receptor antagonist, γ-GTP: γ-glutamyl transpeptidase, HbA1c: hemoglobin A1c, HDL: high-density lipoprotein, LDL: low-density lipoprotein, MRA: mineralocorticoid receptor antagonist, SGLT2i: sodium/glucose cotransporter 2 inhibitor
2. Outcomes
2.1 Changes in variables three months after the initiation of pemafibrate across three subgroups
Table 2 and Fig. 2 present the changes in the variables three months after the initiation of pemafibrate. Overall, significant reductions were observed in APRI, AST, ALT, γ-GTP, non-HDL-C, and triglycerides, whereas, platelet counts, LDL-C, and HDL-C were significantly increased. Notably, ALT, γ-GTP, non-HDL-C, and triglyceride levels significantly decreased, while platelet counts significantly increased across all subgroups. The AST levels were significantly reduced in G2 and G3. FIB-4 displayed significant increases in G1 (p=0.003) and significant reductions in G3 (p=0.041), whereas the APRI was significantly reduced in G2 (p＜0.001) and G3 (p=0.034).
Table 2.
Variations in Parameters Three Months after the Initiation of Pemafibrate across Three Subgroups.
| Laboratory data | Overall n=114 | FIB-4 index | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
G1 n=46
<1.30 |
G2 n=56
1.30 ≤, <2.67 |
G3 n=12
2.67 ≤ |
|||||||||||||
| 0M | 3M | p value | 0M | 3M | p value | 0M | 3M | p value | 0M | 3M | p value | ||||
| FIB-4 index | 1.49 [1.04, 2.02] | 1.43 [1.03, 1.96] | 0.35 | 0.99 [0.78, 1.12] | 1.03 [0.82, 1.27] | 0.003 | 1.81 [1.56, 2.14] | 1.66 [1.37, 2.13] | 0.07 | 3.17 [2.79, 3.46] | 2.55 [2.31, 3.82] | 0.041 | |||
| APRI | 0.32 [0.22, 0.48] | 0.26 [0.18, 0.38] | <0.001 | 0.23 [0.17, 0.34] | 0.22 [0.16, 0.28] | 0.22 | 0.36 [0.27, 0.49] | 0.28 [0.20, 0.37] | <0.001 | 0.69 [0.49, 0.99] | 0.45 [0.34, 0.63] | 0.034 | |||
| Platelet (×104/μL) | 21.3 [17.9, 24.5] | 23.5 [19.2, 26.8] | <0.001 | 24.6 [22.4, 27.3] | 26.3 [23.6, 29.7] | <0.001 | 19.5 [16.9, 22.2] | 21.1 [18.4, 24.9] | <0.001 | 16.8 [15.0, 18.9] | 18.2 [16.7, 19.6] | 0.010 | |||
| AST (IU/L) | 25 [18, 35] | 22 [18, 32] | <0.001 | 21 [16, 32] | 22 [16, 28] | 1.00 | 26 [20, 35] | 21 [18, 31] | <0.001 | 46 [30, 57] | 31 [23, 53] | 0.041 | |||
| ALT (IU/L) | 27 [20, 46] | 19 [13, 33] | <0.001 | 28 [20, 52] | 21 [13, 38] | <0.001 | 26 [18, 40] | 17 [13, 29] | <0.001 | 28 [24, 51] | 23 [14, 34] | 0.031 | |||
| γ-GTP (IU/L) | 45 [27, 89] | 30 [19, 58] | <0.001 | 45 [33, 77] | 28 [20, 41] | <0.001 | 43 [23, 82] | 30 [16, 58] | 0.033 | 82 [45, 128] | 54 [29, 88] | 0.006 | |||
| HbA1c (%) | 7.6 [6.7, 8.5] | 7.3 [6.7, 8.4] | 0.63 | 7.8 [6.9, 8.4] | 7.7 [6.9, 8.4] | 0.62 | 7.5 [6.6, 8.3] | 7.3 [6.6, 8.0] | 0.99 | 7.9 [7.1, 9.5] | 7.0 [6.9, 9.2] | 0.66 | |||
| LDL-C (mg/dL) | 86 [58, 114] | 95 [78, 121] | 0.005 | 101 [76, 122] | 96 [78, 121] | 0.77 | 71 [44, 108] | 95 [79, 124] | <0.001 | 89 [62, 112] | 90 [79, 129] | 0.33 | |||
| non-HDL-C (mg/dL) | 157 [126, 186] | 132 [112, 159] | <0.001 | 168 [140, 195] | 132 [112, 156] | <0.001 | 145 [120, 181] | 134 [112, 170] | 0.007 | 153 [131, 184] | 123 [109, 181] | 0.026 | |||
| HDL-C (mg/dL) | 47 [40, 57] | 54 [46, 60] | <0.001 | 47 [42, 57] | 52 [48, 58] | 0.002 | 46 [38, 58] | 55 [46, 61] | <0.001 | 48 [42, 51] | 50 [41, 58] | 0.69 | |||
| Triglyceride (mg/dL) | 305 [224, 392] | 164 [127, 219] | <0.001 | 307 [264, 386] | 169 [129, 221] | <0.001 | 300 [213, 508] | 161 [119, 233] | <0.001 | 298 [167, 332] | 147 [124, 187] | 0.010 | |||
Variables are presented as median [interquartile range]. Tests for significance were conducted using the Wilcoxon signed-rank test. ALT: alanine transaminase, APRI: aspartate aminotransferase to platelet ratio index, AST: aspartate aminotransferase, FIB-4 index: fibrosis-4 index, γ-GTP: γ-glutamyl transpeptidase, HbA1c: hemoglobin A1c, HDL-C: high-density lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol
Figure 2.
Variations in parameters three months after the initiation of pemafibrate across three subgroups.
2.2 Comparison of changes (Δ) in FIB-4 and APRI across three subgroups
Table 3 and Fig. 3 present a comparative analysis of the changes (Δ) in FIB-4 and APRI across the three subgroups. Significant differences in ΔFIB-4 and ΔAPRI were observed across subgroups (p＜0.001 for both ΔFIB-4 and ΔAPRI). ΔFIB-4 in G3 was significantly greater than that in G1 (p＜0.001) and G2 (p=0.026), while ΔFIB-4 in G2 exceeded that in G1 (p=0.005). Similarly, the ΔAPRI in G3 was significantly greater than that in G1 (p=0.002), and the ΔAPRI in G2 surpassed that in G1 (p=0.009).
Table 3.
Comparison of Changes in FIB-4 Index and APRI among the Three Subgroups.
| Clinical data | Overall n=114 | FIB-4 index | p value | ||
|---|---|---|---|---|---|
| G1 n=46<1.30 | G2 n=56 1.30 ≤, <2.67 | G3 n=12 2.67 ≤ | |||
| ΔFIB-4 index | -0.01 [-0.26, 0.18] | 0.09 [-0.02, 0.22] | -0.05 [-0.35, 0.15] | -0.58 [-1.08, -0.15] | <0.001 |
| ΔAPRI | -0.04 [-0.14, 0.01] | -0.01 [-0.05, 0.03] | -0.07 [-0.15, -0.01] | -0.18 [-0.28, -0.12] | <0.001 |
Variables are presented as median [interquartile range]. Tests for significance were conducted using the Kruskal-Wallis test. APRI: aspartate aminotransferase to platelet ratio index, FIB-4 index: fibrosis-4 index
Figure 3.
Comparison of changes in FIB-4 index and APRI among the three subgroups.
2.3. Baseline parameters and changes (Δ) in parameters correlated with ΔFIB-4
Table 4 presents the baseline parameters correlated with ΔFIB-4 at three months after the initiation of pemafibrate. ΔFIB-4 was inversely correlated with baseline FIB-4 (β=-0.328, p=0.001). Table 5 presents the changes (Δ) in parameters correlated with ΔFIB-4 at three months after the initiation of pemafibrate. ΔFIB-4 demonstrated a significant positive correlation with Δγ-GTP (β=0.375, p=0.005).
Table 4.
Baseline Parameters Correlated with ΔFIB-4 Index.
| Variables | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|
| β | p value | β | p value | ||
| Dose of pemafibrate (mg/day) | 0.048 | 0.61 | |||
| Age (years) | -0.015 | 0.87 | |||
| Body mass index (kg/m2) | 0.011 | 0.91 | -0.002 | 0.98 | |
| Systolic blood pressure (mmHg) | -0.014 | 0.89 | |||
| Duration of diabetes (years) | 0.080 | 0.40 | 0.064 | 0.53 | |
| Platelet (×104/μL) | 0.127 | 0.18 | |||
| eGFR (mL/min/1.73 m2) | 0.008 | 0.94 | 0.045 | 0.68 | |
| HbA1c (%) | 0.084 | 0.38 | 0.059 | 0.56 | |
| serum Albumin (g/dL) | -0.192 | 0.046 | -0.139 | 0.16 | |
| Total bilirubin (mg/dL) | -0.024 | 0.81 | |||
| AST (IU/L) | -0.324 | <0.001 | |||
| ALT (IU/L) | -0.053 | 0.57 | |||
| γ-GTP (IU/L) | -0.325 | <0.001 | -0.210 | 0.052 | |
| LDL-C (mg/dL) | -0.090 | 0.38 | |||
| non HDL-C (mg/dL) | -0.164 | 0.08 | |||
| HDL-C (mg/dL) | -0.086 | 0.36 | |||
| Triglyceride (mg/dL) | -0.222 | 0.018 | -0.129 | 0.21 | |
| FIB-4 index | -0.422 | <0.001 | -0.328 | 0.001 | |
| APRI | -0.276 | 0.003 | |||
Tests for significance were conducted using linear regression model.
β: Standard Partial Regression Coefficient
ALT: alanine transaminase, APRI: aspartate aminotransferase to platelet ratio index, AST: aspartate aminotransferase, eGFR: estimated glomerular filtration rate, FIB-4 index: fibrosis-4 index, γ-GTP: γ-glutamyl transpeptidase, HbA1c: hemoglobin A1c, HDL-C: high-density lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol
Table 5.
Changes in Parameters Correlated with ΔFIB-4 Index.
| Variables | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|
| β | p value | β | p value | ||
| ΔPlatelet (×104/μL) | -0.382 | <0.001 | |||
| ΔeGFR (mL/min/1.73 m2) | -0.075 | 0.43 | -0.048 | 0.69 | |
| ΔHbA1c (%) | -0.085 | 0.37 | -0.079 | 0.51 | |
| Δserum Albumin (g/dL) | 0.102 | 0.29 | 0.085 | 0.51 | |
| ΔTotal bilirubin (mg/dL) | 0.118 | 0.24 | -0.05 | 0.69 | |
| ΔAST (IU/L) | 0.538 | <0.001 | |||
| ΔALT (IU/L) | 0.183 | 0.051 | |||
| Δγ-GTP (IU/L) | 0.380 | <0.001 | 0.372 | 0.005 | |
| ΔLDL-C (mg/dL) | 0.024 | 0.82 | -0.076 | 0.54 | |
| Δnon HDL-C (mg/dL) | 0.049 | 0.61 | |||
| ΔHDL-C (mg/dL) | 0.091 | 0.34 | 0.078 | 0.54 | |
| ΔTriglyceride (mg/dL) | 0.167 | 0.08 | 0.072 | 0.58 | |
| ΔAPRI | 0.749 | <0.001 | |||
Tests for significance were conducted using linear regression model.
β: Standard Partial Regression Coefficient
ALT: alanine transaminase, APRI: aspartate aminotransferase to platelet ratio index, AST: aspartate aminotransferase, eGFR: estimated glomerular filtration rate, FIB-4 index: fibrosis-4 index, γ-GTP: γ-glutamyl transpeptidase, HbA1c: hemoglobin A1c, HDL-C: high-density lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol
Discussion
1 Main findings
1. In patients with T2D and hypertriglyceridemia, liver enzyme levels, FIB-4, and APRI exhibited significant reductions from baseline, whereas platelet counts showed a significant increase three months after the initiation of pemafibrate.
2. The reductions in FIB-4 and APRI at three months following the initiation of pemafibrate were statistically significant in the high-risk group according to the FIB-4 classification.
3. The reduction in FIB-4 was more substantial in individuals with higher baseline FIB-4 levels and was positively associated with a reduction in γ-GTP.
2 Previous study
Effects on liver enzymes at three months after the initiation of pemafibrate
In patients with MAFLD and hypertriglyceridemia, AST and ALT levels exhibited a significant reduction at three months after pemafibrate (27), aligning with the findings of this study. Among nonalcoholic steatohepatitis patients with pronounced disease activity and advanced fibrosis, the AST and ALT levels decreased significantly. However, no significant changes in AST or ALT levels were observed in patients without marked activity or advanced fibrosis (27). Despite the limited sample size (n=10), histological liver evaluation via biopsy revealed a noteworthy finding; the effects of pemafibrate on liver enzymes may vary depending on the degree of disease activity and fibrosis progression in MAFLD. Although histological liver evaluations were not conducted in this study, a significant reduction in AST and ALT levels was observed in the elevated FIB-4 group (FIB-4 ≥1.3), whereas no significant change in AST levels was detected in the normal FIB-4 group (FIB-4＜1.3). In patients with MAFLD and hypertriglyceridemia, AST, ALT, and γ-GTP levels were significantly reduced at 12 weeks (22), which is consistent with the findings of this study. While the APRI did not show a significant decrease at 12 weeks, a significant reduction was observed at 48 weeks (22). The timing of significant APRI reduction differed from the findings of this study. No significant reduction in FIB-4 score was observed (22). In this study, while the overall FIB-4 levels remained unchanged, a significant reduction was observed in patients with high baseline FIB-4 levels (FIB-4 ≥2.67), suggesting that the impact of pemafibrate on FIB-4 may vary based on the initial FIB-4 levels. In patients with MAFLD, ALT and γGTP levels demonstrated a significant reduction 12 weeks after pemafibrate administration (24), consistent with the findings of this study. A significant reduction in AST levels was observed at 36 weeks post-administration (24); thus, the timing differed from the findings in this study.
Relationship between liver fibrosis markers at baseline and the hepatoprotective effects
Among patients with hypertriglyceridemia, those with elevated baseline FIB-4 levels (FIB-4 ≥1.45) exhibited a significant reduction in FIB-4 one year after pemafibrate administration (28). This finding underscores the efficacy of pemafibrate in lowering FIB-4 levels in individuals with hypertriglyceridemia-induced elevations, which is consistent with the results of the present study. The magnitude of FIB-4 reduction was inversely correlated with baseline FIB-4 levels (28), a trend that is consistent with the findings of this study. Among patients with MAFLD, T2D, and hypertriglyceridemia, those with elevated baseline ALT levels exhibited a significant reduction in FIB-4 levels after 52 weeks of pemafibrate administration (25). This finding highlights the FIB-4-lowering effect of pemafibrate in MAFLD patients with elevated ALT levels and is comparable to the results of the present study. While previous findings indicated a correlation between changes in FIB-4 and LDL-C levels (25), the present study did not observe such an association. Instead, changes in FIB-4 were correlated with variations in γ-GTP levels. Among patients with MASLD and hypertriglyceridemia, a significant reduction in liver stiffness, as assessed by FibroScan, was observed 0.5 years after pemafibrate administration in those with elevated baseline FIB-4 values (FIB-4 ≥1.3) (29). This finding underscores the efficacy of pemafibrate in improving imaging-based liver fibrosis markers in patients with MASLD with high baseline fibrosis indicators. Among MASLD patients with hypertriglyceridemia, the magnetic resonance imaging-AST (MAST) score significantly decreased after 48 weeks of pemafibrate administration (23), suggesting that pemafibrate enhances liver fibrosis indices on imaging assessments in MASLD patients. The reduction in MAST score was inversely correlated with baseline FIB-4 (23), whereas changes in MAST score showed a positive correlation with changes in FIB-4, γ-GTP, and AST (23), which are considered to be of comparable significance to the correlations observed in the present study. This study suggests that in patients with T2D and hypertriglyceridemia, pemafibrate may exert a hepatoprotective effect, with greater efficacy observed in patients with higher liver fibrosis markers, which is consistent with previous findings. Moreover, these changes were detected within a relatively shorter timeframe in comparison to previous studies.
The liver fibrosis score changed in a shorter period relative to previous studies
This study focused on patients with T2D, among whom the concomitant use rates of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers (30), SGLT2i (31), and GLP-1Ra (32) - agents reported to possess hepatoprotective properties - were relatively high at 57%, 58%, and 25%, respectively, which may have contributed to the observed reductions in liver enzyme levels and liver fibrosis scores over a shorter period in comparison to previous studies. Moreover, in many previous studies, the mean or median baseline FIB-4 corresponded to a middle-risk classification; similarly, in this study, no significant change in FIB-4 was observed within the middle-risk group at three months after the initiation of pemafibrate. However, consistent with findings from previous studies (23,25,28,29), in this study, a higher baseline FIB-4 value was associated with a greater subsequent change, which may account for the significant reduction observed in the high-risk group at three months after the initiation of pemafibrate. Nevertheless, as this study did not verify improvements in liver fibrosis through imaging modalities or histological assessments, it remains possible that the histological amelioration of liver fibrosis may require a longer duration following improvements in liver fibrosis scores.
3 Significance of liver fibrosis risk assessment in the management of T2D
In cases of NAFLD, diabetes serves as a risk factor for the progression of liver fibrosis (3) and is closely associated with liver-related events and overall mortality (5). Accordingly, assessing the presence or absence of MASLD during T2D management is critical for the prevention of liver fibrosis, liver-related events, and overall mortality in this patient population. Conversely, in previous studies investigating the effects of pemafibrate in patients with NAFLD, the prevalence of T2D among participants was reported to be 56.3% (20), 24.6% (22), 43.0% (23), and 47.3% (24), with only one study exclusively targeting individuals with T2D (25). Therefore, this study assessed the distribution of liver fibrosis risk among patients with T2D and hypertriglyceridemia utilizing the FIB-4, and evaluated the necessity for regular monitoring of liver fibrosis risk as part of T2D management. In this cohort, 60% (n=68) of patients exhibited a middle to high risk of liver fibrosis, accounting for more than half of the study population, thereby underscoring the critical importance of the routine assessment of the risk of liver fibrosis in individuals with T2D.
4 The importance of longitudinal evaluation of liver fibrosis scores
As repeated assessment of the FIB-4 enhances the identification of individuals at high risk for advanced liver disease (33), it is essential to routinely monitor liver fibrosis scores alongside HbA1c levels in patients with T2D and to track their changes over time in order to mitigate the progression of liver fibrosis and liver-related events. Furthermore, previous studies have reported that histological improvement in liver fibrosis is accompanied by corresponding improvements in liver fibrosis scores (34). In the present study, the FIB-4 values in the high-risk group were significantly reduced following the initiation of pemafibrate therapy, suggesting that the administration of pemafibrate to patients with T2D, elevated FIB-4 levels, and hypertriglyceridemia may contribute to long-term reductions in liver fibrosis and liver-related complications. It has been reported that among patients with obesity and/or T2D, those with increased FIB-4 levels 12 months after baseline have more than twice the risk of mortality, as well as cardiovascular and hepatic events, relative to those with decreased FIB-4, irrespective of their baseline FIB-4 levels (35). Regular evaluation of FIB-4 is essential in patients with T2D, and for those with elevated or rising FIB-4 levels, the administration of hepatoprotective agents with established efficacy, such as thiazolidinedione (36), SGLT2i (31), GLP-1Ra (32), and, should be considered based on individual indications.
5 Impact of age on the FIB-4 index
In this study, the FIB-4, a blood test based score of liver fibrosis that has been extensively reported as a predictor of both cardiovascular and liver-related events, was utilized as the primary index for liver fibrosis assessment. However, given that age is incorporated into the FIB-4 calculation, there is concern regarding its potential age-related bias; therefore, we additionally evaluated the APRI, a liver fibrosis score designed to minimize the influence of age. Among the three liver fibrosis risk groups classified by FIB-4 values, baseline APRI was significantly higher in both the middle and high-risk groups in comparison to the low-risk group (both p＜0.001 by Steel-Dwass test), and the reduction in APRI following the administration of pemafibrate was also significantly greater in the middle and high-risk groups in comparison to the low-risk group. The similarity between baseline APRI levels and their changes with those observed in FIB-4 suggests that the influence of age on FIB-4 may be minimal. Future studies with larger sample sizes will be necessary to further validate the effects of pemafibrate on liver fibrosis scores using alternative indices, such as FIB-3 and FIB-5, which exclude the influence of age.
6 Clinical implications
In patients with T2D, hypertriglyceridemia, and elevated liver fibrosis scores such as FIB-4 and APRI, pemafibrate may effectively improve liver enzyme levels and fibrosis scores within a relatively short timeframe. This study evaluated the liver fibrosis scores in diabetic patients with hypertriglyceridemia and highlighted the potential of pemafibrate intervention in patients with elevated fibrosis scores.
The present study was associated with several limitations. First, this was a single-center retrospective analysis. Second, the sample size was relatively small, particularly in the high-risk group (G3). Third, this was a single-arm study with no control group. Fourth, the data were derived only from cases in which no changes were made to antidiabetic, antihypertensive, or lipid-lowering medications within three months preceding or following the initiation of pemafibrate. Fifth, the high-risk group (G3) is affected by an age-related bias. To verify the results of this study and address these limitations, future studies should employ larger sample sizes, adopt a multicenter, prospective, controlled design, and utilize liver fibrosis scoring systems such as the FIB-3 or FIB-5 indices, which exclude age from their calculations.
7 Conclusion
The short-term impact of pemafibrate on FIB-4 and APRI scores in patients with type 2 diabetes and hypertriglyceridemia appears to be more pronounced in the high-risk category of the FIB-4 classification, highlighting its potential as a therapeutic option for patients with concomitant fatty liver disease.
The authors state that they have no Conflict of Interest (COI).
Acknowledgments
The authors thank Naoko Fukuda for handling the Ethics Committee approval procedure and Tomoko Nishi for technical assistance with the data collection.
References
- 1.Leite NC, Salles GF, Araujo AL, Villela-Nogueira CA, Cardoso CR. Prevalence and associated factors of non-alcoholic fatty liver disease in patients with type-2 diabetes mellitus. Liver Int 29: 113-119, 2009. [DOI] [PubMed] [Google Scholar]
- 2.Mantovani A, Byrne CD, Bonora E, Targher G. Nonalcoholic fatty liver disease and risk of incident type 2 diabetes: a meta-analysis. Diabetes Care 41: 372-382, 2018. [DOI] [PubMed] [Google Scholar]
- 3.Nakahara T, Hyogo H, Yoneda M, et al.; Japan Study Group of Nonalcoholic Fatty Liver Disease (JSG-NAFLD) . Type 2 diabetes mellitus is associated with the fibrosis severity in patients with nonalcoholic fatty liver disease in a large retrospective cohort of Japanese patients. J Gastroenterol 49: 1477-1484, 2014. [DOI] [PubMed] [Google Scholar]
- 4.Seko Y, Yano K, Takahashi A, et al. FIB-4 index and diabetes mellitus are associated with chronic kidney disease in Japanese patients with non-alcoholic fatty liver disease. Int J Mol Sci 25: 171, 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Hirose S, Matsumoto K, Tatemichi M, et al. Nineteen-year prognosis in Japanese patients with biopsy-proven nonalcoholic fatty liver disease: lean versus overweight patients. PLoS One 13: 15, 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Zhou YY, Zhou XD, Wu SJ, et al. Synergistic increase in cardiovascular risk in diabetes mellitus with nonalcoholic fatty liver disease: a meta-analysis. Eur J Gastroenterol Hepatol 30: 631-636, 2018. [DOI] [PubMed] [Google Scholar]
- 7.Eslam M, Sanyal AJ, George Jthe International Consensus Panel . MAFLD: a consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology 158: 1999-2014, 2020. [DOI] [PubMed] [Google Scholar]
- 8.Eslam M, Newsome PN, Sarin SK, et al. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol 73: 202-209, 2020. [DOI] [PubMed] [Google Scholar]
- 9.Rinella ME, Lazarus JV, Ratziu V, et al.; the NAFLD Nomenclature consensus group . A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol 79: 1542-1556, 2023. [DOI] [PubMed] [Google Scholar]
- 10.Ekstedt M, Hagström H, Nasr P, et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology 61: 1547-1554, 2015. [DOI] [PubMed] [Google Scholar]
- 11.Younossi ZM, Stepanova M, Rafiq N, et al. Pathologic criteria for nonalcoholic steatohepatitis: interprotocol agreement and ability to predict liver-related mortality. Hepatology 53: 1874-1882, 2011. [DOI] [PubMed] [Google Scholar]
- 12.Angulo P, Hui JM, Marchesini G, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 45: 846-854, 2007. [DOI] [PubMed] [Google Scholar]
- 13.Sterling RK, Lissen E, Clumeck N, et al.; the APRICOT Clinical Investigators . Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 43: 1317-1325, 2006. [DOI] [PubMed] [Google Scholar]
- 14.Shah AG, Lydecker A, Murray K, Tetri BN, Contos MJ, Sanyal AJNash Clinical Research Network . Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 7: 1104-1112, 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Wai CT, Greenson JK, Fontana RJ, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology 38: 518-526, 2003. [DOI] [PubMed] [Google Scholar]
- 16.Higashiura Y, Tanaka M, Mori K, et al. High fibrosis-4 index predicts the new onset of ischaemic heart disease during a 10-year period in a general population. Eur Heart J Open 16: oeac030, 2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Saito Y, Okumura Y, Nagashima K, et al. Impact of the fibrosis-4 index on risk stratification of cardiovascular events and mortality in patients with atrial fibrillation: findings from a Japanese multicenter registry. J Clin Med 21: 584, 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Liu X, Zhang HJ, Fang CC, et al. Association between noninvasive liver fibrosis scores and heart failure in a general population. J Am Heart Assoc 19: 13, 2024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Arai H, Yamashita S, Yokote K, Araki E, Suganami H, Ishibashi SK-877 Study Group . Efficacy and safety of pemafibrate versus fenofibrate in patients with high triglyceride and low HDL cholesterol levels: a multicenter, placebo-controlled, double-blind, randomized trial. J Atheroscler Thromb 25: 521-538, 2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ikeda S, Sugihara T, Kihara T, et al. Pemafibrate ameliorates liver dysfunction and fatty liver in patients with non-alcoholic fatty liver disease with hypertriglyceridemia: a retrospective study with the outcome after a mid-term follow-up. Diagnostics (Basel) 11: 2316, 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Hatanaka T, Kosone T, Saito N, et al. Effect of 48-week pemafibrate on non-alcoholic fatty liver disease with hypertriglyceridemia, as evaluated by the FibroScan-aspartate aminotransferase score. JGH Open 5: 1183-1189, 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Morishita A, Oura K, Takuma K, et al. Pemafibrate improves liver dysfunction and non-invasive surrogates for liver fibrosis in patients with non-alcoholic fatty liver disease with hypertriglyceridemia: a multicenter study. Hepatol Int 17: 606-614, 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Ichikawa T, Oba H, Owada M, et al. Evaluation of the effects of pemafibrate on metabolic dysfunction-associated steatotic liver disease with hypertriglyceridemia using magnetic resonance elastography combined with fibrosis-4 index and the magnetic resonance imaging-aspartate aminotransferase score. JGH Open 7: 959-965, 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Ono H, Atsukawa M, Tsubota A, et al. Impact of pemafibrate in patients with metabolic dysfunction-associated steatotic liver disease complicated by dyslipidemia: a single-arm prospective study. JGH Open 8: e13057, 2024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Nomoto H, Kito K, Iesaka H, et al. Preferable effects of pemafibrate on liver function and fibrosis in subjects with type 2 diabetes complicated with liver damage. Diabetol Metab Syndr 15: 214, 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Tokushige K, Ikejima K, Ono M, et al. Evidence-based clinical practice guidelines for nonalcoholic fatty liver disease/nonalcoholic steatohepatitis 2020. Hepatol Res 51: 1013-1025, 2021. [DOI] [PubMed] [Google Scholar]
- 27.Hatanaka T, Kakizaki S, Saito N, et al. Impact of pemafibrate in patients with hypertriglyceridemia and metabolic dysfunction-associated fatty liver disease pathologically diagnosed with non-alcoholic steatohepatitis: a retrospective, single-arm study. Intern Med 60: 2167-2174, 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Katsuyama H, Yanai H, Adachi H, Hakoshima M. A significant effect of pemafibrate on hepatic steatosis and fibrosis indexes in patients with hypertriglyceridemia. Gastroenterology Res 16: 240-243, 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ichikawa T, Yamashima M, Yamamichi S, et al. Pemafibrate reduced liver stiffness in patients with metabolic dysfunction-associated steatotic liver disease complicated with hyperlipidemia and liver fibrosis with a fibrosis-4 index above 1.3. Intern Med 64: 1296-1302, 2025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Georgescu EF, Ionescu R, Niculescu M, Mogoanta L, Vancica L. Angiotensin-receptor blockers as therapy for mild-to-moderate hypertension-associated non-alcoholic steatohepatitis. World J Gastroenterol 15: 942-954, 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Takeshita Y, Honda M, Harada K, et al. Comparison of tofogliflozin and glimepiride effects on nonalcoholic fatty liver disease in participants with type 2 diabetes: a randomized, 48-week, open-label, active-controlled trial. Diabetes Care 45: 2064-2075, 2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Newsome PN, Buchholtz K, Cusi K, et al.; the NN9931-4296 Investigators . A placebo-controlled trial of subcutaneous semaglutide in nonalcoholic steatohepatitis. N Engl J Med 384: 1113-1124, 2021. [DOI] [PubMed] [Google Scholar]
- 33.Hagström H, Talbäck M, Andreasson A, Walldius G, Hammar N. Repeated FIB-4 measurements can help identify individuals at risk of severe liver disease. J Hepatol 73: 1023-1029, 2020. [DOI] [PubMed] [Google Scholar]
- 34.Chalasani N, Abdelmalek MF, Loomba R, et al. Relationship between three commonly used non-invasive fibrosis biomarkers and improvement in fibrosis stage in patients with NASH. Liver Int 39: 924-932, 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Anstee QM, Berentzen TL, Nitze LM, et al. Prognostic utility of Fibrosis-4 Index for risk of subsequent liver and cardiovascular events, and all-cause mortality in individuals with obesity and/or type 2 diabetes: a longitudinal cohort study. Lancet Reg Health Eur 36: 100780, 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Belfort R, Harrison SA, Brown K, et al. A placebo-controlled trial of pioglitazone in subjects with nonalcoholic steatohepatitis. N Engl J Med 355: 2297-2307, 2006. [DOI] [PubMed] [Google Scholar]