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Article

Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis

by
Natchaya Polpichai
1,*,
Sakditad Saowapa
2,
Aunchalee Jaroenlapnopparat
3,
Leandro Sierra
4,
Pojsakorn Danpanichkul
2,
Panisara Fangsaard
5,
Phuuwadith Wattanachayakul
6 and
Apichat Kaewdech
7,*
1
Department of Medicine, Weiss Memorial Hospital, Chicago, IL 60640, USA
2
Department of Medicine, Texas Tech University Health Science Center, Lubbock, TX 79430, USA
3
Digestive Health Institute, Orlando Health, Orlando, FL 32806, USA
4
Department of Medicine, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
5
Department of Internal Medicine, Bassett Medical Center, Cooperstown, NY 13326, USA
6
Department of Internal Medicine, Einstein Medical Center, Philadelphia, PA 19141, USA
7
Gastroenterology and Hepatology Unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
*
Authors to whom correspondence should be addressed.
Livers 2024, 4(4), 677-687; https://doi.org/10.3390/livers4040046
Submission received: 24 October 2024 / Revised: 14 November 2024 / Accepted: 6 December 2024 / Published: 12 December 2024
Browse Figure
Versions Notes

Abstract

:
Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease globally. The impact of statins on liver fibrosis severity in MASLD individuals remains uncertain, despite their known cardiovascular benefits. Methods: A cross-sectional study was performed utilizing the National Health and Nutrition Examination Survey (NHANES) database from 2017 to 2018. MASLD was defined by hepatic steatosis (controlled attenuation parameter [CAP] score ≥ 288 dB/m) without other etiologies. Using inverse probability treatment weighting to minimize confounding, we examined the association between statin use and MASLD outcomes, including at-risk steatohepatitis (FibroScan-aspartate aminotransferase [AST] [FAST] score ≥ 0.67), significant and advanced fibrosis (liver stiffness measurement [LSM] ≥ 8.8 kilopascals [kPa] and ≥ 11.7 kPa), and advanced fibrosis (AGILE 3+ score ≥ 0.68). Results: Of 1283 MASLD patients, 376 were prescribed statins within the past 30 days. After adjustment for confounders, statin use was significantly associated with reduced risks of at-risk steatohepatitis, significant fibrosis, and high AGILE 3+ scores, with odds ratios (ORs) of 0.29 (95% CI: 0.01 to 0.87), 0.54 (95% CI: 0.31 to 0.95), and 0.41 (95% CI: 0.22 to 0.75), respectively. However, a subgroup analysis showed this effect persisted only with lipophilic statins. Conclusions: Statin use was associated with reduced steatohepatitis and fibrosis in patients with MASLD, supported by robust causal inference and vibration-controlled transient elastography-derived scores.

1. Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD), is a prevalent cause of chronic liver disease globally [1]. MASLD is strongly associated with an increased risk of systemic end-organ complications, particularly cardiovascular diseases (CVD) [2,3]. Recent studies, including a comprehensive meta-analysis, have shown that individuals with MASLD are more susceptible to dying from cardiovascular complications than from liver-related issues [4,5]. The progression from MASLD to metabolic dysfunction-associated steatohepatitis (MASH), previously referred to as non-alcoholic steatohepatitis (NASH), is believed to be driven by various mechanisms, such as oxidative stress, lipid toxicity, and cytokine-mediated inflammation. These processes exacerbate liver damage and dysfunction, ultimately increasing the risk of cirrhosis and hepatocellular carcinoma (HCC) [6,7]. Effective management of associated metabolic risks, such as diabetes mellitus and obesity, is essential for slowing disease progression [8]. Recognizing the importance of controlling these factors is crucial in developing comprehensive treatment strategies to mitigate the advancement of liver disease [9].
Statins are a class of medications that inhibit hydroxy-methylglutaryl-coenzyme A (HMG-CoA) reductase, a key enzyme in the cholesterol synthesis pathway in the liver, effectively lowering blood cholesterol levels recommended for prevention of CVD at both primary and secondary levels [10,11]. However, despite the strong association between MASLD and CVD, statins remain underutilized in MASLD patients [12]. In one recent study, only half of MASLD individuals in whom statin treatment is indicated based on high CVD risk take statins [13]. Statin use has also been associated with a lower risk of MASLD and reduced fibrosis in people with MASLD [14,15]. However, these estimates remain confounded by the observational nature of the dataset to which conclusions were drawn upon. Additionally, the recent introduction [16,17] of the FibroScan-aspartate aminotransferase [AST] [FAST] score and AGILE 3+ have provided more accurate estimates of MASLD activity based on FibroScan [16,17]. Therefore, we aimed to analyze the population-level effects of statins on MASLD risk, at-risk steatohepatitis or MASH, and fibrosis by applying inverse probability of treatment weighting (IPTW), a causal inference approach designed to mitigate confounding in observational data [18].

2. Materials and Methods

2.1. Study Population

The National Health and Nutrition Examination Survey (NHANES) study is a cross-sectional survey of the health and nutrition data from a nationally representative sample of the noninstitutionalized civilian population in the United States during the 2017–2018 period, organized by the National Center for Health Statistics (NCHS). In 2017–2018, NHANES participants underwent vibration-controlled transient elastography (VCTE) with FibroScan® model 502 V2 Touch, manufactured by Echosens in Paris, France. The procedure was carried out by trained and certified NHANES health technicians. VCTE, a non-invasive diagnostic method, was performed to evaluate two essential parameters: liver steatosis, as determined by the Controlled Attenuation Parameter (CAP), and liver fibrosis, as assessed through liver stiffness measurement (LSM). Examinations were considered reliable if a minimum of 10 valid LSM readings were obtained after a fasting period of at least 3 h. Only participants in the 2017–2018 cycle who underwent VCTE and had reliable LSM results were included in the study. Additionally, NHANES also collected data on demographics, body mass index (BMI), and routine laboratory values.

2.2. Study Definition

The definition of MASLD refers to a liver disease characterized by excessive fat accumulation in the liver, accompanied by at least one of five cardiometabolic risk factors, and not associated with significant alcohol consumption, as recently proposed [19,20]. Hepatic steatosis and advanced fibrosis were assessed using FibroScan®, which uses the CAP value and LSM value, respectively. MASLD was diagnosed based on a CAP derived from VCTE of ≥288 d/Bm in the absence of other identifiable causes of liver disease and substantial alcohol use (defined as ≥3 drinks/day in men and ≥2 drinks/day in women) [21]. FAST score ≥ 0.67 was used to rule in at-risk NASH/MASH, while a FAST score of ≤0.35 was used to rule out at-risk NASH/MASH, where at-risk NASH/MASH was defined as NAFLD activity score ≥ 4, and fibrosis stage ≥ F2 [16]. The presence of liver fibrosis in MASLD was assessed by LSM using transient elastography with higher values indicating a higher probability of advanced fibrosis. LSM of ≥ 8.8 kilopascals (kPa) and ≥11.7 kPa were defined as significant (≥F2) and advanced (≥F3) fibrosis, respectively [22,23]. Additionally, we also calculated the AGILE 3+ score to examine the risk of advanced fibrosis (≥F3) using a cut-off of 0.68 [24]. The AGILE 3+ score integrates LSM, the AST/alanine transaminase (ALT) ratio, platelet count, sex, diabetes status, and age [17,25]. Data on the prescription of statins were collected using a detailed questionnaire, in which participants reported all medications taken in the past 30 days. We classified statins as hydrophilic (rosuvastatin and pravastatin) or lipophilic (simvastatin, fluvastatin, pitavastatin, lovastatin, and atorvastatin) [26].

2.3. Statistical Analyses

All statistical analysis was performed using STATA (version 16.1; Statacorp, Chicaco, IL, USA) and R version 4.2.3. Statistical significance was set at p < 0.05. Baseline variables were summarized in median and interquartile range (IQR) for continuous variables and proportions for binary and categorical variables. Continuous variables were examined with the non-parametric Wilcoxon ranked sum test analysis of variance, while binary variables were examined with chi-square test and Fisher exact where appropriate. Because the sample size seemed too small for a propensity score analysis, an IPTW analysis was used to reduce selection bias from observational studies [27]. Measures of fibrosis were included both as a continuous variable (e.g., FAST score, LSM values) and discrete variable (e.g., FAST score ≤ 0.35, FAST score ≥ 0.67, LSM values ≥ 8.8 kPa). Logistic regression was used to obtain the odds ratio (OR) to compare the risk of steatohepatitis, significant and advanced fibrosis between statin and non-statin use groups. A nonparametric quantile regression was used to examine the difference between statin users and non-users. The final model included age, gender, race, and BMI with and without diabetic status. Additionally, a subgroup analysis was subsequently conducted to examine the effect of lipophilic vs. hydrophilic statins.

3. Results

3.1. Baseline Characteristics of Population

A total of 5,102 adults were evaluated for MASLD using VCTE, among whom 1283 met the diagnostic criteria. Of these, 376 patients were prescribed statins. The median age of the study participants was 58 years (IQR: 44 to 68) and 52.14% were male. Statin users were generally older (statin user: 66 years [IQR: 58 to 73] vs. non-statin users: 53 years [IQR: 39 to 64]) and more likely to be male (statin users: 57% [95% CI: 52 to 62%] vs. non-statin users: 50% [95% CI: 47 to 53%]). Statin users also exhibited significantly higher rates of diabetes (statin users: 62% [95% CI: 0.57 to 0.67%] vs. non-statin users: 26% [95% CI: 23 to 29%]). Additionally, significant differences in ethnicity were observed between statin users and non-statin users. A comparison between baseline characteristics of statin users and non-statin users in patients with MASLD is summarized in Table 1.

3.2. Fibrosis, At-Risk NASH/MASH, and Statin Use in MASLD

The association between statin use and severity of liver fibrosis in patients with MASLD is presented in Table 2. In the unadjusted model and model one (adjusted for age, gender, ethnicity, and BMI), no significant association was observed between statin use and the risk of at-risk NASH/MASH, severity of liver fibrosis, or a high AGILE 3+ score. However, after further adjustment for gender, age, ethnicity, BMI, and diabetes (model two), statin use was significantly associated with decreased odds for at-risk NASH/MASH (OR: 0.289, 95% CI: 0.096 to 0.867, p = 0.03), significant fibrosis (OR: 0.540, 95% CI: 0.306 to 0.953, p = 0.03), and high AGILE 3+ score (OR: 0.409, 95% CI: 0.224 to 0.747, p < 0.01). There was no significant association between statin use and odds of advanced fibrosis.

3.3. Lipophilic and Hydrophilic Statins in MASLD

Subgroup analysis was performed to investigate the effect of lipophilic and hydrophilic statins, as presented in Table 3. After adjusting for age, gender, ethnicity, BMI and diabetes, the effect was maintained only in lipophilic statins. Lipophilic statins were significantly associated with decreased odds for at-risk NASH/MASH (OR: 0.273, 95% CI: 0.081 to 0.922, p = 0.04), significant fibrosis (OR: 0.506, 95% CI: 0.272 to 0.942, p = 0.03), and high AGILE 3+ score (OR: 0.402, 95% CI: 0.210 to 0.767, p < 0.01) (Figure 1).

4. Discussion

Fibrosis remains a key determinant of adverse outcomes in patients with MASLD [28]. A recent meta-analysis by Ng et al. found that the presence of any degree of fibrosis in MASLD is associated with a 99% increased risk in all-cause mortality. This number increased to 136% when the analysis was stratified only to clinically significant fibrosis [29]. Despite this alarming association, effective and low-cost treatments for fibrosis are limited. Statins, indicated in a substantial proportion of individuals with MASLD due to their cardiovascular benefits, may offer additional non-cardiovascular advantages [30,31]. Emerging evidence suggests that statins may have potential chemoprotective benefits for patients with liver diseases [32,33]. However, our study reveals that only 29.3% of MASLD patients were receiving statin therapy despite clear cardiovascular indications. This underutilization may be attributed to historical concerns regarding potential hepatotoxicity, although current evidence indicates that statins are safe and may offer protective effects [34]. This finding underscores a significant gap in the management of MASLD patients who could potentially benefit from statin therapy. While several studies have reported the effects of statin use in MASLD and its association with reduced odds of fibrosis, the present study contributes to the existing literature by utilizing IPTW to adjust for selection bias in statin use within a population-based study. Furthermore, our study incorporates recent advancements in VCTE, including the FAST score [16] and AGILE 3+ score, enabling a more accurate evaluation of steatohepatitis and hepatic fibrosis in the population [17,24].
Our findings align with previous studies highlighting the hepatoprotective effects of statins in patients with MASLD. For instance, studies have demonstrated that statins are generally well-tolerated and do not increase the risk of liver injury, even in individuals with elevated liver enzymes. Moreover, statin use has been associated with slower progression of liver fibrosis and improvements in liver function markers, suggesting potential antifibrotic and anti-inflammatory effects [35]. In patients with MASLD, statins appear to mitigate the risk of liver-related complications, likely through mechanisms involving reductions in hepatic inflammation, oxidative stress, and stellate cell activation [36]. Our study revealed that statin use was associated with reduced LSM values on VCTE. The recent introduction of the FAST score and the AGILE 3+ score into our analysis enabled a more precise assessment of at-risk NASH/MASH and significant fibrosis, both of which were less common among statin-treated patients.
Yada et al. demonstrated a reduced risk of MASH and fibrosis with statin use, along with an in vitro reduction of lipid droplet accumulation in human liver organoids [36]. Similarly, Nascimbeni et al., in a cross-sectional study of 346 biopsy-confirmed MASLD patients with type two diabetes, reported a negative association between statin use and significant liver fibrosis (≥F2) [37]. Additionally, a recent study by Zhou et al. involving approximately 8000 statin-exposed individuals found that statin use was associated with a lower rate of liver stiffness progression in MASLD, both in patients with LSM ≥ 10 kPa and LSM < 10 kPa, with adjusted hazard ratios (aHR) of 0.542 (95% CI 0.389–0.755) and 0.450 (95% CI 0.342–0.592), respectively [38]. Further supporting these findings, Ciardullo and Perseghin conducted a cross-sectional analysis of the NHANES 2017–2018 database which included 744 patients with type two diabetes who had VCTE results [39]. Their study found that statin use was associated with significantly lower odds of advanced liver fibrosis (OR 0.35; 95% CI 0.13–0.90), although no significant association was observed between statin use and hepatic steatosis as measured by the CAP [39].
Notably, while beneficial effects were observed with both lipophilic and hydrophilic statins, our findings highlight that only lipophilic statins were significantly associated with decreased odds of being at risk for developing MASH, significant fibrosis, and having a high AGILE 3+ score. Lipophilic statins are considered a preferable alternative, as accumulating evidence suggests they may exhibit a greater capacity for preventing hepatocarcinogenesis [40,41]. This distinction underscores the need for personalized approaches when considering statin therapy for MASLD patients.
Statins may provide additional benefits in reducing the mortality risk in patients with MASLD. A study by Zhou et al. demonstrated that statin use significantly reduced the risk of all-cause mortality (HR 0.233; 95% CI 0.127–0.426) [38]. Similarly, Ng et al. found that statins decreased the risk of overall and cancer-related mortality in MASLD, although no significant benefit was observed in reducing CVD-related mortality [13]. The lack of observed benefit in reducing cardiovascular events may be a consequence of selection bias, as the cardiovascular protective effects of statins are well-established [13]. Moreover, statin use has been associated with a reduced risk of HCC. For instance, a study by Zou et al. reported a 53% lower risk of HCC among MASLD patients using statins compared to non-users (HR 0.47; 95% CI 0.36–0.60) [42]. Similarly, a meta-analysis by Zhang et al. in 2023 indicated a significant reduction in HCC risk among statin users with MASLD (OR 0.59; 95% CI 0.39–0.89) [43]. These findings underscore the potential protective effects of statins against HCC development in this patient population [44].
A plausible mechanism underlying the beneficial effect of statin use in reducing steatohepatitis and fibrosis on VCTE in patients with MASLD lies in their pleiotropic effects beyond lipid-lowering. Statins exhibit anti-inflammatory, antioxidant, and antifibrotic properties that may slow MASLD progression [45]. By inhibiting the HMG-CoA reductase pathway, statins not only reduce cholesterol levels but also suppress the production of reactive oxygen species and pro-inflammatory cytokines, such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), which play key roles in hepatic inflammation and fibrosis [36]. In MASLD, hepatic stellate cells (HSCs) become activated in response to chronic liver injury, playing a central role in fibrosis development. Statins have been shown to inhibit HSC activation, thereby reducing the production of extracellular matrix proteins involved in fibrosis [35]. This antifibrotic effect likely explains the observed decrease in liver stiffness and fibrosis progression in statin users. Additionally, statins improve endothelial function and reduce lipid accumulation in hepatocytes, alleviating hepatic steatosis—a precursor to steatohepatitis and fibrosis [36,46]. By reducing hepatic fat content and inflammation, statins may directly reduce the risk of development of steatohepatitis, ultimately lowering the risk of advanced fibrosis in MASLD.
Our study highlights the potential to influence treatment guidelines by expanding the recommended use of statins for patients with MASLD. If further studies confirm the long-term antifibrotic effects of statins, guidelines may advocate for their use not only as cardiovascular protectants but also as a strategy to slow liver disease progression. This shift could lead to more confident prescribing of statins in patients with advanced steatosis or early fibrosis, recognizing their dual role in managing cardiovascular risk and reducing liver fibrosis. Our findings contribute to the growing evidence supporting the safety and efficacy of statin use in patients with liver diseases. Concerns about potential hepatotoxicity have led clinicians to hesitate in prescribing statins to patients with elevated liver enzyme levels. However, current guidelines suggest that statins are safe and should not be withheld in patients with chronic liver diseases, including MASLD [47]. This shift in perspective is crucial for improving patient outcomes, as withholding statins may deprive patients of their potential cardiovascular and hepatic benefits.
A key strength of our study is the use of IPTW, which is particularly effective in observational studies. IPTW creates a pseudo-randomized sample by balancing covariates between treatment groups, thereby minimizing confounding and allowing for a more unbiased estimate of treatment effects [48]. In our study, we applied IPTW to assess the impact of statin use in patients with MASLD. However, this approach could also be extended to other populations, especially those with diverse demographics or complex clinical profiles. IPTW is equally valuable for studying other medications where selection bias or confounding by indication is a concern, as well as in high-risk or rare disease populations where limited sample sizes make traditional RCTs impractical [49].
Nevertheless, there are some limitations to our study. The effects of statin use on steatosis and fibrosis likely depend on the dose and duration of therapy, but we lacked data on the duration of statin use. Statins were not prescribed at random, and there is potential for confounding by indication, although we attempted to mitigate these effects through IPTW analysis. Given the relatively small cohort size, we were unable to adequately assess the impact of statin use on long-term survival. Additionally, the absence of data on statin dosage prevents us from evaluating dose-response relationships, which could provide further insights into optimizing statin therapy for hepatic benefits.

5. Conclusions

Our study suggests that statin use is associated with decreased at-risk steatohepatitis and fibrosis in patients with MASLD. Notably, lipophilic statins may offer greater benefits in reducing the risk of MASH and significant fibrosis. Given the high cardiovascular risk in MASLD patients, statins may offer dual benefits by improving both cardiovascular and hepatic outcomes. Future prospective studies are warranted to explore the mechanistic pathways and to establish the long-term impact of statins on liver fibrosis progression in MASLD.
This article is a revised and expanded version of an abstract entitled Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis, which was presented at The Liver Meeting 2023, Boston, Massachusetts, USA, November 13th, 2023.

Author Contributions

Conceptualization, N.P., S.S. and AK; methodology, A.J.; software, N.P. and L.S.; validation, N.P. and S.S.; formal analysis, A.J. and P.W.; writing—original draft preparation, N.P., P.F. and P.D.; writing—review and editing, S.S., L.S. and A.K.; supervision, A.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study utilized the NHANES publicly available database, which is de-identified and approved by the National Center for Health Statistics Institutional Review Board. This study was exempt from the Ethics committee in accordance with the ethical guidelines of the 1975 Declaration of Helsinki and approved by the Human Research Ethics Unit (HREU) of the Faculty of Medicine, Prince of Songkla University (REC number: 67-453-14-1).

Informed Consent Statement

Written informed consent was obtained from all participants involved in the NHANES study by the dataset creators. No additional consent was obtained for this study.

Data Availability Statement

The data used in this study are from a public database available at https://www.cdc.gov/nchs/nhanes/index.htm (accessed on 3 May 2023), which is accessible to everyone through the provided links.

Acknowledgments

The authors thank all the dedicated staff members and participants involved in the NHANES 2017-2018 for their invaluable contributions in terms of donation, data collection, and data sharing.

Conflicts of Interest

Apichat Kaewdech received research grants or support from Roche, Roche Diagnostics, and Abbott Laboratories, and honoraria from Roche, Roche Diagnostics, Abbott Laboratories, and Esai. However, these roles do not present any conflict of interest concerning the content of this work. The other authors have no relevant conflict of interest to declare.

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Livers 04 00046 g001
Figure 1. Comparison of the effects of hydrophilic and lipophilic statins on at-risk NASH/MASH and fibrosis severity outcomes. The ORs and 95% CIs are displayed for each outcome. Hydrophilic statins are represented in blue, and lipophilic statins are represented in pink. The p-values for the effects of lipophilic statins are less than 0.05 (p = 0.04 for at-risk NASH/MASH (FAST ≥ 0.67), p = 0.03 for significant fibrosis, and p < 0.01 for high AGILE 3+ scores). NASH: Non-alcoholic steatohepatitis; MASH: Metabolic-dysfunction associated steatohepatitis; FAST: FibroScan-AST score; OR: Odds ratio; CI: Confidence interval.
Figure 1. Comparison of the effects of hydrophilic and lipophilic statins on at-risk NASH/MASH and fibrosis severity outcomes. The ORs and 95% CIs are displayed for each outcome. Hydrophilic statins are represented in blue, and lipophilic statins are represented in pink. The p-values for the effects of lipophilic statins are less than 0.05 (p = 0.04 for at-risk NASH/MASH (FAST ≥ 0.67), p = 0.03 for significant fibrosis, and p < 0.01 for high AGILE 3+ scores). NASH: Non-alcoholic steatohepatitis; MASH: Metabolic-dysfunction associated steatohepatitis; FAST: FibroScan-AST score; OR: Odds ratio; CI: Confidence interval.
Livers 04 00046 g001
Table 1. Baseline characteristics.
Table 1. Baseline characteristics.
Statin UsersNon-Statin Usersp-Value
Age (years)66 (IQR: 58 to 73)53 (IQR: 39 to 64)<0.01 *
Male gender (%)57 (95% CI: 52 to 62)50 (95% CI: 47 to 53)0.02 *
Diabetes (%)62 (95% CI: 57 to 67)26 (95% CI: 23 to 29)<0.01 *
Hypertension (%)86 (95% CI: 82 to 89)47 (95% CI: 44 to 51)<0.01 *
HbA1c (%)6.4 (IQR: 5.8 to 7.4)5.7 (IQR: 5.4 to 6.2)<0.01 *
Fasting Glucose (mmol/L)7.05 (IQR: 6.05 to 8.77)6.05 (IQR: 5.61 to 6.77)<0.01 *
Body Mass Index (kg/m2)32.0 (IQR: 28.5 to 37.4)32.5 (IQR: 28.2 to 37.7)0.48
Weight (kg)91.0 (IQR: 76.3 to 104.8)90.9 (IQR: 77.2 to 107.9)0.63
Waist circumference (cm)113.1 (IQR: 102 to 123)108.6 (IQR: 98.9 to 119.7)<0.01 *
Platelet (1000 cells/uL)228 (IQR: 191 to 268)244 (IQR: 207 to 288)<0.01 *
Total Bilirubin (umol/L)6.84 (IQR: 5.13 to 10.26)6.84 (IQR: 5.13 to 8.55)0.02 *
LDL cholesterol (mmol/L)2.25 (IQR: 1.71 to 2.72)3.08 (IQR: 2.46 to 3.57)<0.01 *
HDL cholesterol (mmol/L)1.16 (IQR: 0.88 to 1.4)1.19 (IQR: 1.01 to 1.4)0.54
Total cholesterol (mmol/L)4.27 (IQR: 3.70 to 5.04)5.02 (IQR: 4.42 to 5.72)<0.01 *
Triglycerides (mmol/L)1.42 (IQR: 1.06 to 1.95)1.26 (IQR: 0.9 to 1.86)0.04 *
Ethnicity (%) 0.01 *
Mexican American 11 (95% CI: 15 to 20)17 (95% CI: 15 to 20)
Hispanic9 (95% CI: 7 to 12)8 (95% CI: 6 to 10)
White44 (95% CI: 39 to 49)36 (95% CI: 33 to 39)
Black17 (95% CI: 14 to 21)20 (95% CI: 17 to 22)
Other Race18 (95% CI: 15 to 22)19 (95% CI: 17 to 22)
Liver parameters
CAP Score (dB/m)329 (IQR: 307 to 353)304 (IQR: 304 to 353)0.16
FAST score0.13 (IQR: 0.06 to 0.24)0.12 (IQR: 0.05 to 0.25)0.99
LSM values (kPa)5.8 (IQR: 4.7 to 7.5)5.7 (IQR: 4.5 to 7.4)0.31
At risk of NASH/MASH (FAST ≥ 0.67)0.02 (95% CI: 0.01 to 0.04)0.03 (95% CI: 0.02 to 0.04)0.51
Not at risk of NASH/MASH (FAST ≤ 0.35)0.86 (95% CI: 0.82 to 0.89)0.85 (95% CI: 0.82 to 0.87)0.56
Significant fibrosis0.18 (95% CI: 0.14 to 0.22)0.17 (95% CI: 0.14 to 0.19)0.58
Advanced fibrosis0.09 (95% CI: 0.07 to 0.13)0.09 (95% CI: 0.07 to 0.11)0.93
Legend: IQR—Interquartile range; 95% CI—95% Confidence Interval; LDL—Low-density lipoprotein; HDL—High-density lipoprotein; NASH—Non-alcoholic steatohepatitis; CAP—Controlled Attenuation Parameter score; FAST—FibroScan-AST score; MASH—Metabolic dysfunction-associated steatohepatitis. * p-value ≤ 0.05 denotes statistical significance.
Table 2. Association of statin use with risk of at-risk NASH/MASH and fibrosis severity across unadjusted and adjusted models.
Table 2. Association of statin use with risk of at-risk NASH/MASH and fibrosis severity across unadjusted and adjusted models.
UnadjustedModel 1Model 2
Odd Ratios (95% CI)p ValueOdd Ratios (95% CI)p ValueOdd Ratios (95% CI)p Value
At Risk NASH/MASH 0.393 (95% CI: 0.148 to 1.046)0.060.365 (95% CI: 0.121 to 1.097)0.070.289 (95% CI: 0.096 to 0.867)0.03 *
Significant Fibrosis0.729 (95% CI: 0.466to 1.139)0.170.666 (95% CI: 0.380 to 1.167)0.160.540 (95% CI: 0.306 to 0.953)0.03 *
Advanced Fibrosis0.689 (95% CI: 0.393 to 1.209)0.190.644 (95% CI: 0.318 to 1.302)0.220.524 (95% CI: 0.261 to 1.052)0.07
High AGILE 3+ score0.797 (95% CI 0.477 to 1.330)0.390.580 (95% CI: 0.324 to 1.034)<0.01 *0.409 (95% CI: 0.224 to 0.747)<0.01 *
UnadjustedModel 1 Model 2
Beta (95% CI)β valueBeta (95% CI)β valueBeta(95% CI)β value
LSM
FAST Score		−0.400 (95% CI: −0.915 to −0.115)
−0.005 (95% CI: −0.042 to 0.032)		0.13
0.79		−0.571 (95% CI: −0.994 to −0.148)
−0.023 (95% CI: −0.044 to −0.001)		<0.01 *
0.04		−1.170 (95% CI: −1.664 to −0.676
−0.039 (95% CI: −0.068 to −0.009)		<0.01 *
0.01 *
Legend: OR—Odds ratio; 95% CI—95% Confidence interval; NASH—Non-alcoholic steatohepatitis; FAST—FibroScan-AST score; LSM—Liver stiffness measurement; MASH—Metabolic dysfunction-associated steatohepatitis; Model One—Adjusted for age, gender, ethnicity, BMI.; Model Two—Adjusted for age, gender, ethnicity, BMI, and diabetes. * p-value ≤ 0.05 denotes statistical significance.
Table 3. Comparison of outcomes between hydrophilic and lipophilic statins across unadjusted and adjusted models.
Table 3. Comparison of outcomes between hydrophilic and lipophilic statins across unadjusted and adjusted models.
Hydrophilic StatinsLipophilic Statins
Effect Size (95% CI) Effect Size (95% CI)
Unadjusted model
At Risk NASH/MASH (FAST ≥ 0.67)OR: 0.402 (95% CI: 0.050 to 3.164)p = 0.39OR: 0.392 (95% CI: 0.138 to 1.115)p = 0.08
Significant FibrosisOR: 0.810 (95% CI: 0.365 to1.797)p = 0.61OR: 0.712 (95% CI: 0.438 to 1.157)p = 0.17
Advanced FibrosisOR: 0.731 (95% CI: 0.283 to 1.892)p = 0.52OR: 0.680 (95% CI 0.367 to 1.262)p = 0.22
High AGILE 3+ scoreOR: 0.697 (95% CI: 0.282 to 1.722)p = 0.43OR: 0.819 (95% CI: 0.472 to 1.422)p = 0.48
Model 1
At Risk NASH/MASH (FAST ≥ 0.67)OR: 0.460 (95% CI: 0.057 to 3.681)p = 0.46OR: 0.348 (95% CI: 0.103 to 1.179)p = 0.09
Significant FibrosisOR: 0.873 (95% CI: 0.367 to 2.079)p = 0.76OR: 0.626 (95% CI: 0.334 to 1.174)p = 0.14
Advanced FibrosisOR: 0.820 (95% CI: 0.296 to 2.271)p = 0.70OR: 0.611 (95% CI: 0.276 to 1.350)p = 0.22
High AGILE 3+ score0.637 (95% CI: 0.255 to 1.588)p = 0.33OR: 0.568 (95% CI: 0.300 to 1.074)p = 0.08
LSMBeta −0.529 (95% CI: −0.97 to −0.088)β = 0.02 *Beta −0.805 (95% CI: −1.337 to −0.273)β = <0.01 *
FAST scoreBeta −0.013 (95% CI: −0.092 to 0.066)β = 0.75Beta −0.022 (95% CI: −0.049 to 0.004)β= 0.10
Model 2
At Risk NASH/MASH (FAST ≥ 0.67)OR: 0.384 (95% CI: 0.048 to 3.084)p = 0.37OR: 0.273 (95% CI: 0.081 to 0.922)p = 0.04
Significant FibrosisOR: 0.726 (95% CI: 0.285 to 1.846)p = 0.50OR: 0.506 (95% CI: 0.272 to 0.942)p = 0.03
Advanced FibrosisOR: 0.680 (95% CI: 0.232 to 1.999)p = 0.48OR: 0.496 (95% CI: 0.230 to 1.068)p = 0.07
High AGILE 3+ scoreOR: 0.451 (95% CI: 0.172 to 1.184)p = 0.11OR: 0.402 (95% CI: 0.210 to 0.767)p = <0.01 *
LSMBeta −1.016 (95% CI: −1.456 to −0.576)β ≤ 0.01 *Beta −1.201 (95% CI: −1.765 to −0.638)β = <0.01 *
FAST scoreBeta −0.038 (95% CI: −0.096 to 0.021)β = 0.21Beta −0.039 (95% CI: −0.075 to 0)β = 0.04 *
Legend: OR—Odds ratio; 95% CI—95% Confidence interval; NASH—Non-alcoholic steatohepatitis; FAST—FibroScan-AST score; LSM—Liver stiffness measurement; MASH—Metabolic dysfunction-associated steatohepatitis; Model One—Adjusted for age, gender, ethnicity, BMI; Model Two—Adjusted for age, gender, ethnicity, BMI, and diabetes; Hydrophilic statins—Rosuvastatin, Pravastatin; Lipophilic statins—Simvastatin, Fluvastatin, Pitavastatin, Lovastatin, Atorvastatin. * p-value ≤ 0.05 denotes statistical significance.
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Polpichai, N.; Saowapa, S.; Jaroenlapnopparat, A.; Sierra, L.; Danpanichkul, P.; Fangsaard, P.; Wattanachayakul, P.; Kaewdech, A. Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis. Livers 2024, 4, 677-687. https://doi.org/10.3390/livers4040046

AMA Style

Polpichai N, Saowapa S, Jaroenlapnopparat A, Sierra L, Danpanichkul P, Fangsaard P, Wattanachayakul P, Kaewdech A. Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis. Livers. 2024; 4(4):677-687. https://doi.org/10.3390/livers4040046

Chicago/Turabian Style

Polpichai, Natchaya, Sakditad Saowapa, Aunchalee Jaroenlapnopparat, Leandro Sierra, Pojsakorn Danpanichkul, Panisara Fangsaard, Phuuwadith Wattanachayakul, and Apichat Kaewdech. 2024. "Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis" Livers 4, no. 4: 677-687. https://doi.org/10.3390/livers4040046

APA Style

Polpichai, N., Saowapa, S., Jaroenlapnopparat, A., Sierra, L., Danpanichkul, P., Fangsaard, P., Wattanachayakul, P., & Kaewdech, A. (2024). Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis. Livers, 4(4), 677-687. https://doi.org/10.3390/livers4040046

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