Duarte MB, Czermainski J, Ferreira LF, Tovo CV, Carteri RB. Inflammatory parameters and liver fibrosis in patients with steatosis: A cross-sectional analysis. World J Hepatol 2026; 18(3): 111569 [DOI: 10.4254/wjh.v18.i3.111569]
Corresponding Author of This Article
Cristiane V Tovo, Department of Internal Medicine, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245 Centro Histórico, Porto Alegre 90050-170, Rio Grande do Sul, Brazil. cristianev@ufcspa.edu.br
Research Domain of This Article
Multidisciplinary Sciences
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Melina Borba Duarte, Juliana Czermainski, Luis F Ferreira, Cristiane V Tovo, Department of Internal Medicine, Federal University of Health Sciences of Porto Alegre, Porto Alegre 90050-170, Rio Grande do Sul, Brazil
Randhall B Carteri, Department of Nutrition, Centro Universitário CESUCA, Porto Alegre 94935-630, Brazil
Author contributions: Duarte MB and Carteri RB contributed to the methodological development and material support, collected data, interpreted results, conducted data analysis, wrote and revised the manuscript; Czermainski J contributed to methodological development and material support; Ferreira LF conducted data analysis and interpreted the results; Tovo CV contributed to the conception and critical review of the manuscript; Carteri RB designed the research project, collaborated in writing, and critically reviewed the manuscript; all authors have read and approved the final manuscript.
Institutional review board statement: This study used NHANES data, which are publicly available and fully de-identified, containing no personal identifiable information. The original data collection procedures, including survey methodologies and materials, received ethical approval from the Ethics Review Board of the National Center for Health Statistics.
Informed consent statement: All participants provided written informed consent at the time of enrollment.
Conflict-of-interest statement: The authors declare that they have no conflicts of interest in the production of this article.
Data sharing statement: The data used are open access data from NHANES. However, the database used for the analyses presented in this article is available upon request to the corresponding author.
Corresponding author: Cristiane V Tovo, Department of Internal Medicine, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245 Centro Histórico, Porto Alegre 90050-170, Rio Grande do Sul, Brazil. cristianev@ufcspa.edu.br
Received: July 3, 2025 Revised: August 20, 2025 Accepted: January 16, 2026 Published online: March 27, 2026 Processing time: 266 Days and 5.2 Hours
Abstract
BACKGROUND
Inflammation is a central mechanism in the progression of metabolic dysfunction-associated steatotic liver disease. Because direct inflammatory biomarkers are not cost-effective for routine use in clinical health systems, indices derived from peripheral blood counts, such as the neutrophil-to-lymphocyte ratio (NLR), aggregate index of systemic inflammation (AISI), and systemic inflammation response index (SIRI), have emerged as practical prognostic markers of systemic inflammation.
AIM
To evaluate the predictive value of whole blood cell-based inflammatory indices for liver fibrosis in adults with hepatic steatosis.
METHODS
This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2017-March 2020 pre-pandemic cycle (n = 16427) and the 2021-2023 cycle (n = 11933). Participants were classified into a control group (n = 3281) or a liver fibrosis group (n = 950). The predictive performance of inflammatory indices was evaluated using the area under the receiver operating characteristic curve (AUROC) and multivariable binary logistic regression models.
RESULTS
C-reactive protein (CRP), NLR, and SIRI were independently associated with steatosis in multivariable logistic regression analyses [P = 0.001, Exp(B) = 1.01, 1.00, and 1.12, respectively]. However, none of the evaluated indices demonstrated clinically meaningful predictive performance. Receiver operating characteristic analyses showed statistically significant but modest discrimination, with AUCROC values ranging from 0.53 to 0.61.
CONCLUSION
Whole-blood cell-based inflammatory indices are not reliable predictors of liver fibrosis and were consistently outperformed by CRP. These findings suggest that alternative direct inflammatory biomarkers should be further evaluated as cost-effective tools for prognostic assessment in liver fibrosis.
Core Tip: This study evaluated low-cost inflammatory indices derived from whole blood cell counts - such as the neutrophil-to-lymphocyte ratio, aggregate index of systemic inflammation, and systemic inflammation response index - as potential noninvasive predictors of liver fibrosis in adults with metabolic dysfunction-associated steatotic liver disease using National Health and Nutrition Examination Survey data. Although these indices showed statistically significant associations with liver injury, their overall predictive performance was poor, with no meaningful positive predictive value and low area under the receiver operating characteristic curve. C-reactive protein consistently outperformed the cell-based indices. These findings suggest that, despite their ease of calculation, inflammatory ratios are insufficient as standalone markers for fibrosis prediction, underscoring the need for more accurate and cost-effective direct biomarkers.
Citation: Duarte MB, Czermainski J, Ferreira LF, Tovo CV, Carteri RB. Inflammatory parameters and liver fibrosis in patients with steatosis: A cross-sectional analysis. World J Hepatol 2026; 18(3): 111569
Liver diseases account for approximately 2 million deaths worldwide, with steatotic liver disease (SLD) representing one of the leading causes of chronic liver disease (CLD) and affecting an estimated 32.4% of adults[1]. More specifically, metabolic dysfunction-associated SLD is a multifactorial disorder driven by environmental, metabolic, and genetic factors; however, its progression is closely linked to comorbidities such as obesity, insulin resistance, and type 2 diabetes mellitus. By 2040, it is projected to affect more than half of the global population[2-4].
Between 12% and 40% of individuals with SLD progress to metabolic dysfunction-associated steatohepatitis, a more severe condition characterized by proinflammatory cell infiltration and hepatic necrosis. In addition, approximately 39% of patients develop varying degrees of liver fibrosis[5]. Chronic inflammation and sustained tissue remodeling drive ongoing liver injury, impair hepatic function and systemic metabolism, and ultimately promote fibrogenesis[6,7].
Liver fibrotic progression is often driven by persistent inflammation, including metabolic dysfunction, viral infection, and autoimmune disease. This chronic inflammatory state activates profibrotic signaling pathways, disrupting the balance between tissue repair and extracellular matrix deposition and ultimately leading to sustained injury and fibrotic scarring[8-10]. Proinflammatory cytokines, including interleukin (IL)-12, IL-6, IL-1β, and tumor necrosis factor (TNF), contribute to the progression of steatosis by promoting hepatic inflammation, necrosis, apoptosis, and fibrosis, whereas the anti-inflammatory cytokine IL-10 regulates these processes and supports liver regeneration[7,11]. During acute inflammation, IL-6 stimulates hepatic production of high-sensitivity C-reactive protein (hs-CRP), which correlates with disease severity and can distinguish advanced from mild fibrosis. Elevated hs-CRP levels are also predictive of cardiovascular complications. Elevated inflammatory mediators reflect underlying liver injury and may serve as diagnostic and prognostic markers in SLD[12,13].
Several noninvasive models incorporating clinical and serum-based parameters have been developed for the assessment and early detection of liver fibrosis. These serum-based markers are simple, cost-effective, and widely accessible and have demonstrated high accuracy in detecting advanced fibrosis[14,15].
The neutrophil-to-lymphocyte ratio (NLR) reflects systemic inflammatory responses and correlates with histological characteristics across stages of steatosis and fibrosis[16-18].
The systemic inflammation response index (SIRI), which integrates neutrophil, monocyte, and lymphocyte counts, serves as a marker of chronic low-grade inflammation and has been identified as an independent prognostic factor in cancer, rheumatoid arthritis, and intracerebral hemorrhage, as well as a risk factor for recurrence in patients with early-stage hepatocellular carcinoma (HCC)[19,20].
The aggregate systemic inflammation index (AISI), a composite biomarker derived from neutrophil, monocyte, and platelet counts, has been associated with cardiovascular mortality in hypertension, poor prognosis in idiopathic pulmonary fibrosis, and increased liver fibrosis severity in psoriasis vulgaris[21-23].
The prognostic nutritional index (PNI), derived from lymphocyte count and serum albumin levels, reflects both nutritional and inflammatory status and has demonstrated prognostic utility in CLD and HCC[24,25]. Accordingly, accurate diagnostic tools for advanced fibrosis are a critical component of managing metabolic dysfunction-associated SLD (MASLD)[26]. This study aimed to evaluate the predictive potential of various inflammatory indices for liver fibrosis in patients with steatosis.
MATERIALS AND METHODS
Design study and population
The National Health and Nutrition Examination Survey (NHANES) is a comprehensive cross-sectional survey conducted by the National Center for Health Statistics that collects nationally representative health data through interviews, physical examinations, and laboratory testing. NHANES uses a complex, multistage probability sampling design to ensure accurate representation of the United States population.
Ethical considerations
This study used publicly available, fully de-identified NHANES data that contains no personally identifiable information. The original data collection protocols, including survey methods and study materials, were approved by the Ethics Review Board of the National Center for Health Statistics. All participants provided written informed consent at the time of enrollment.
Study sample
Data from the NHANES 2017-March 2020 pre-pandemic cycle (16427 participants) and the 2021-2023 cycle (11933 participants) were combined for this analysis. Demographic, dietary, examination, laboratory, and questionnaire data were included, yielding a total study population of 28360 participants.
The following exclusion criteria were applied: Participants younger than 18 years (n = 18713); participants without complete elastography data (n = 14192); participants with missing data or positivity for hepatitis B surface antigen (n = 9844); participants with incomplete blood count data (9821), missing CRP data (9681), or missing body mass index (BMI) data (9623); and participants with a controlled attenuation parameter (CAP) < 275 dB/m (4231). Ultimately, 4231 participants were included in the analysis, comprising 3281 patients in the control group and 950 patients in the fibrosis group, as illustrated in the study flow diagram (Figure 1).
Figure 1 Participant screening flowchart.
NHANES: National Health and Nutrition Examination Survey; CRP: C-reactive protein; BMI: Body mass index; CAP: Controlled attenuation parameter.
Classification of hepatic fibrosis and steatosis by non-invasive methods
Hepatic fibrosis and steatosis were classified using liver elastography in accordance with the 2021 European Association for the Study of the Liver (EASLD) guidelines. Significant or advanced fibrosis was defined by transient elastography (TE) values ≥ 8 kPa. Hepatic steatosis was quantified using the CAP, with values < 275 dB/m indicating absence of steatosis and values ≥ 275 dB/m indicating presence of hepatic steatosis[27].
Variables and calculations
Variables of interest included inflammatory markers such as CRP, white blood cell count, platelet count, and serum albumin. Covariates included age, sex, race/ethnicity, and BMI.
Inflammation-related indices were calculated using established formulas: NLR = Neutrophils/lymphocytes[16]; SIRI = (neutrophils × monocytes)/lymphocytes[19]; AISI = (neutrophils × monocytes × platelets)/lymphocytes[22]; systemic immune-inflammation index = neutrophil count × platelet count/lymphocyte count[28]; and PNI = Albumin + (0.005 × lymphocytes)[25].
Statistical analysis
Continuous variables were assessed for normality using visual inspection of histograms and the Shapiro-Wilk test. Normally distributed variables were compared using the independent Student’s t test, whereas non-normally distributed variables were analyzed using the Mann–Whitney U test. Categorical variables were compared using the χ2 test. Associations between inflammatory indices and liver fibrosis were evaluated using binary logistic regression. Each inflammatory index was first examined in univariate models, followed by multivariable logistic regression analyses adjusting for established clinical confounders associated with liver fibrosis, including age, BMI, glycohemoglobin, and total cholesterol. Odds ratios (ORs) with 95% confidence intervals (Cis) were calculated, and ORs were expressed as percentage changes in odds using the formula (OR - 1) × 100%. Discriminatory performance was assessed by generating receiver operating characteristic (ROC) curves for each biomarker, with the area under the curve (AUC) and corresponding 95%CI reported. A two-sided P value of < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS version 26.0.
RESULTS
Baseline characteristics of participants with and without liver fibrosis are summarized in Table 1. Patients with fibrosis were significantly older (mean age, 56.81 vs 54.46 years) and had a higher mean BMI (38.23 vs 32.70 kg/m2) compared with those without fibrosis (both P < 0.05). Analysis of BMI categories revealed a substantially higher prevalence of severe obesity among participants with fibrosis, with 37.1% in the highest BMI category compared with 12.0% in the non-fibrosis group. No significant differences were observed in racial or ethnic distribution between the two groups.
Table 2 compares blood biomarkers between patients with MASLD with and without fibrosis. Patients with fibrosis exhibited significantly higher white blood cell counts (7.45 × 103 cells/µL vs 7.73 × 103 cells/µL, P = 0.001), segmented neutrophil counts (4.38 × 103 cells/µL vs 4.63 × 103 cells/µL, P = 0.001), and hs-CRP (6.20 mg/L vs 4.71 mg/L, P = 0.001), indicating an increased inflammatory state. Additionally, inflammatory indices, including the NLR (2.31 vs 2.16, P = 0.001) and SIRI (1.43 vs 1.30, P = 0.001), were significantly higher in the fibrosis group, whereas serum albumin levels were significantly lower (3.96 g/dL vs 4.05 g/dL, P = 0.001).
Table 3 summarizes the logistic regression analyses evaluating inflammatory and nutritional indices as predictors of liver fibrosis. The NLR (OR = 1.104; 95%CI: 1.042–1.169; P = 0.001) and SIRI (OR = 1.128; 95%CI: 1.053–1.209; P = 0.001) were positively associated with liver fibrosis. hs-CRP was also a significant predictor (OR = 1.018; 95%CI: 1.010–1.026; P < 0.001). In contrast, the PNI showed an inverse association with fibrosis (OR = 0.918; 95%CI: 0.891–0.946; P < 0.001), whereas the AISI was not significantly associated with fibrosis (P = 0.134).
ROC analyses are shown in Figure 2, and the diagnostic performance of inflammatory biomarkers for liver fibrosis is summarized in Table 4. All evaluated biomarkers demonstrated lower AUROC values, indicating limited discriminatory ability for liver fibrosis. hs-CRP showed the highest AUROC (0.608; 95%CI: 0.582–0.635; P = 0.001), followed by SIRI (0.563), NLR (0.558), and AISI (0.531). The PNI demonstrated the poorest performance (AUROC = 0.422).
Using data from NHANES 2017-2023, this study evaluated the predictive value of several whole blood cell-based inflammatory indices for detecting liver fibrosis in patients with MASLD. Although CRP, NLR, SIRI, and PNI were significantly altered in individuals with fibrosis, underscoring a strong association between systemic inflammation and disease progression, none of the biomarkers achieved an AUROC ≥ 0.7, limiting their utility as standalone diagnostic tools. CRP demonstrated the strongest association with fibrosis, reinforcing its role as a marker of systemic inflammation. Nevertheless, when compared with validated noninvasive models such as FIB-4, the discriminatory performance of these inflammatory indices remained suboptimal. This study adopts the updated SLD nomenclature and diagnostic criteria in accordance with recent international consensus recommendations[29]; earlier studies were based on the former non-alcoholic fatty liver disease (NAFLD) classification.
Assessing systemic inflammation using blood-based inflammatory indices represents a routine, accessible, noninvasive, and low-cost approach that may aid in disease stratification and monitoring across a range of conditions. Markers derived from neutrophil, lymphocyte, monocyte, and platelet counts have been associated with clinical cardiovascular, hepatic, renal, and pulmonary diseases[20,22,28,30]. Persistent inflammation, mediated by cytokines such as TNF-α, IL-1β, and transforming growth factor-beta, along with inflammatory cells including hepatic macrophages, T and B lymphocytes, and natural killer cells, promotes chronic activation of hepatic stellate cells. This process drives extracellular matrix accumulation, collagen deposition, dysregulated fibrotic tissue formation, and progressive loss of liver function[31-34]. Together, these mechanisms support the need to evaluate more specific inflammatory biomarkers for both the diagnosis and severity assessment of liver fibrosis.
In the present study, NLR and SIRI were significantly higher in patients with liver fibrosis compared with those without fibrosis (2.31 vs 2.16 and 1.43 vs 1.30, P = 0.001), indicating a heightened inflammatory response in this group. These findings are consistent with previous studies demonstrating that NLR is a predictor of NAFLD progression and may help identify patients at increased risk of steatohepatitis and advanced fibrosis[18,35]. Compared with TE and controlled attenuation parameter assessment, NLR has remained significant in evaluating steatosis and fibrosis severity in patients with NAFLD[17]. Using data from six NHANES cycles (2007-2018), another study reported a linear association between systemic inflammatory biomarkers, including NLR, and NAFLD risk, underscoring the complex role of systemic inflammation in disease pathophysiology[36]. In contrast, Zhu et al[37] found that, after adjustment for confounders, lower NLR was associated with a higher risk of MASLD in individuals with type 2 diabetes, suggesting a distinct inflammatory profile in this population. Beyond steatotic liver disease, elevated SIRI values have been linked to shorter recurrence-free survival and overall survival in patients with early-stage HCC treated with radiofrequency ablation who subsequently experienced cancer recurrence[20].
As a marker of both nutritional and immunological status, the PNI underscores the association observed in our study between hypoalbuminemia in the fibrosis group and poorer prognosis. Lower PNI values have been linked to advanced liver fibrosis, suggesting that preserved nutritional status may exert a protective effect against disease progression and highlighting the potential importance of nutritional interventions in patients at risk for fibrosis. Notably, although higher PNI has been associated with an increased risk of NAFLD, it has been inversely correlated with advanced fibrosis, underscoring the complex and stage-dependent role of nutrition in liver disease[38]. Consistently, low PNI values have also been associated with worse overall survival and increased mortality risk, supporting its utility as a prognostic marker in CLD and very early-stage HCC[24,25].
Although AISI was included among the evaluated markers, it showed no significant association with liver fibrosis in either univariate or multivariable analyses (P = 0.134 and P = 0.481, respectively), indicating limited clinical relevance. While previous studies have linked AISI to disease severity or mortality in conditions such as psoriasis vulgaris, idiopathic pulmonary fibrosis, and hypertension[21-23], our findings do not support its utility for prediction of fibrosis in MASLD. Similarly, despite statistically significant differences in NLR, SIRI, and PNI between fibrosis and non-fibrosis groups, all indices demonstrated poor individual predictive performance, with low sensitivity (0%-50%) and modest AUROC values, ranging from 0.421 to 0.609. Consequently, their usefulness as standalone diagnostic tools is limited. Overall, these results are inferior to established noninvasive markers such as FIB-4 or aspartate aminotransferase-to-platelet ratio index (APRI), suggesting that although these indices reflect systemic inflammation, they lack sufficient robustness as independent predictors of liver fibrosis.
CRP is an acute-phase protein and a well-established inflammation-sensitive marker, primarily synthesized by the liver in response to proinflammatory cytokines such as IL-6 and IL-1β. CRP plays multiple roles in immune regulation, including activation of the complement system and modulation of leukocyte activity, and often reflects the severity of underlying pathological processes[39-41]. In the present study, CRP levels were significantly higher in the fibrosis group compared with the non-fibrosis group (6.20 mg/L vs 4.71 mg/L, P = 0.001), supporting its association with systemic inflammation and liver disease progression. These findings are consistent with previous reports linking CRP and hepatic steatosis, steatohepatitis, and fibrosis, as well as to broader inflammatory and metabolic conditions such as cardiovascular disease and cancer[40,42-44]. However, despite its biological plausibility and consistent statistical association, the clinical utility of CRP as an independent marker of liver fibrosis remains limited. In our analysis, CRP demonstrated the highest discriminatory performance among the evaluated biomarkers (AUROC = 0.608; P = 0.001); however, this value falls below the threshold generally considered indicative of moderate diagnostic accuracy. This is consistent with a retrospective study of MASLD populations from the NHANES 2017-2018 cycle) and the Changzhou Third People’s Hospital cohort in China (2018-2023), which reported a nonlinear association between CRP levels and liver fibrosis, with modest discriminatory performance (AUROC values ranging from 0.59 to 0.65) that varied across population subgroups[45]. Similarly, in a cohort of obese adults undergoing bariatric surgery with liver biopsy confirmation, CRP demonstrated moderate sensitivity (60%-69%) for detecting steatosis and fibrosis but markedly lower specificity (24%) compared with elastography[46]. Therefore, although CRP reflects the inflammatory burden associated with MASLD and fibrosis, it should not be used as a standalone diagnostic marker. Its clinical value may therefore lie instead in complementing established noninvasive scores rather than serving as an independent diagnostic marker. Current European Association for the Study of the Liver (EASL) guidelines recommend models such as FIB-4, which incorporates aspartate aminotransferase, alanine aminotransferase, platelet count, and age, as first-line tools, followed by TE for further assessment[27]. A recent systematic review confirmed the utility of FIB-4 and APRI in evaluating liver fibrosis and predicting clinical outcomes in NAFLD, particularly when compared with liver biopsy. However, the review also highlighted their variable accuracy in detecting longitudinal changes in fibrosis stage over time[47]. Complementing these findings, a prospective study of patients undergoing bariatric surgery with liver biopsy found that although the NAFLD fibrosis score, FIB-4, and APRI had limited sensitivity for detecting advanced fibrosis, they were more effective in ruling it out, supporting their use as exclusion tools rather than definitive diagnostic tests[48]. In immune-mediated inflammatory diseases (IMIDs), patients with liver involvement exhibit significantly lower CRP levels during active disease compared with those without liver disease. This pattern has been observed across most IMIDs, apart from systemic lupus erythematosus and inflammatory bowel disease, in which CRP is inherently less sensitive. Notably, CRP levels did not vary according to liver disease severity, suggesting that hepatic dysfunction may confound CRP interpretation and that caution is warranted when using CRP as a sole indicator in clinical decision-making[49]. Similarly, although CRP has been proposed as a biomarker for monitoring pulmonary exacerbations in cystic fibrosis, its clinical utility appears limited. While baseline CRP levels have been associated with symptom severity and treatment response, longitudinal changes in CRP during and after treatment correlate poorly with lung function and symptom scores. Moreover, no reliable CRP threshold has been identified to predict treatment failure, and persistent post-treatment elevation may reflect only short-term exacerbation risk, further underscoring the limitations of CRP as a standalone marker[50]. Although CRP is widely used as a systemic marker of inflammation because of its high sensitivity, its lack of specificity limits its predictive value. Elevated CRP levels may arise from a wide range of conditions, including infections, autoimmune diseases, malignancies, trauma, or non-pathological factors such as age, obesity, and medication use, increasing the risk of false-positive interpretations. Beyond its role as a biomarker, CRP also actively participates in inflammatory processes, particularly in its modified forms, which can amplify local inflammation through endothelial activation and complement system engagement. Consequently, CRP interpretation requires clinical context, with consideration of coexisting inflammatory processes that may influence its diagnostic and prognostic accuracy[51,52]. These findings highlight the need to develop more precise and sensitive predictive models, potentially by integrating inflammatory markers such as CRP into established algorithms like FIB-4 and APRI to enhance diagnostic performance and clinical applicability. Although non-hepatic inflammatory conditions can elevate systemic markers like CRP and NLR and introduce potential confounding when evaluating their association with liver fibrosis in steatosis, large cohort studies that adjust for infections, autoimmune diseases, tumors, and other inflammatory comorbidities consistently demonstrate that these markers remain significantly associated with steatosis and fibrosis. This suggests that, although nonspecific, systemic inflammatory markers retain a robust independent association with liver pathology after adjustment for major sources of extrahepatic inflammation. However, this relationship appears to be limited to group-level associations and statistical significance, without demonstrable prognostic value at the individual level, as shown in the present study.
Strengths and limitations
The main strengths of this study include an adequate sample size, which ensures statistical power, and the use of robust, appropriate analyses to identify independent predictors of fibrosis and assess diagnostic performance. However, several limitations should be acknowledged. The cross-sectional design precludes any inference of causality. Although the evaluated indices demonstrated high specificity, their low sensitivity limits their clinical utility, especially for screening purposes, as many true cases of fibrosis may go undetected.
We analyzed the 2017-March 2020 and 2021-2023 NHANES cycles because the former provides the most comprehensive set of clinical, laboratory, and imaging variables currently available, allowing greater statistical power and improved control of confounders. The 2021–2023 cycle was included because it contains updated hepatic elastography data and differential blood cell counts, which were essential for calculating the inflammatory indices in liver investigation.
The current classification considers only fibrosis and steatosis, without addressing liver disease or grading fibrosis severity, which may limit the results interpretation and understanding of clinical heterogeneity of the sample.
The high prevalence of severe obesity (37.1% with BMI ≥ 40 kg/m2) in the fibrosis group may have compromised the accuracy of TE, as has been documented in consensus guidelines[46]. Signal attenuation in patients with BMI ≥ 35 kg/m2 may lead to misclassifications of fibrosis, introducing measurement bias. Future studies should consider alternative methods for populations with advanced obesity, such as elastography and magnetic resonance imaging.
While individuals with hepatitis B infection were excluded and self-reported alcohol consumption data were used to minimize the inclusion of alcoholic liver disease, it was not possible to systematically exclude other potential causes of steatosis, such as autoimmune hepatitis or drug-induced liver injury. We acknowledge this potential for misclassification bias; however, it does not undermine the study’s primary objective, which was to explore associations between blood cell–based inflammatory markers and liver fibrosis in a sample with characteristics consistent with SLD. Also, because NHANES represents the United States population, it is important to note that metabolic profiles and SLD prevalence significantly differ across ethnic groups, and these findings may not be fully generalizable to global populations.
The absence of exclusion criteria for comorbid inflammatory conditions, combined with the non-specificity of CRP, NLR, and SIRI may have confounded the associations with liver fibrosis, potentially leading to overestimation.
Finally, liver enzymes were not incorporated into the analysis models because the study's primary objective was to assess whether blood cell–based inflammatory indices could independently predict liver fibrosis. While this decision aligns with the study aim, it may limit comparability with other established models that include transaminases.
The results of this study reinforce the contribution of inflammation in the progression to liver fibrosis; however, the biomarkers evaluated are not robust enough for isolated clinical use. Additional research is necessary to investigate the integration of these indices with established models and methodologies to ascertain their diagnostic accuracy.
CONCLUSION
This study demonstrates that patients with steatosis and liver fibrosis present clinical and biochemical profiles marked by elevated systemic inflammation. Although blood-based inflammatory biomarkers showed high specificity, their limited sensitivity is insufficient as standalone tools for predicting liver fibrosis. The CRP protein exhibited moderate discriminatory capability; however, its performance was insufficient for reliable diagnostic accuracy. These results highlight the ongoing need for reliable, cost-effective, and easily accessible biomarkers to improve early detection and prognosis of liver fibrosis. Furthermore, the low AUROC values reinforce the limited clinical utility of these markers when used in isolation.
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