Clin Mol Hepatol > Volume 31(1); 2025 > Article
Kim, Choi, and Jun: Correspondence to editorial on “Prevalence of clinically significant liver fibrosis in the general population: A systematic review and meta-analysis”
Dear Editor,
We sincerely appreciate Dr. Nana Peng and Terry Yip for their thoughtful comments on our recent manuscript published in Clinical and Molecular Hepatology [1,2]. Their letter offers a comprehensive review of our analysis assessing the prevalence of clinically significant liver fibrosis using non-invasive tests (NITs) in the general population, which represents a crucial first step in implementing early identification and targeted interventions before the onset of liver decompensation [3]. Early detection of liver fibrosis in the general population is essential, given the rising global burden of chronic liver diseases (CLD) [4] and the critical role that liver fibrosis, resulting from chronic liver inflammation, plays in liver-related mortality [5]. Although liver biopsy remains the gold standard for assessing fibrosis, its invasive nature and the absence of symptoms until advanced stages limit its practicality as a screening tool, especially in asymptomatic general populations. Consequently, NITs are currently recommended for detecting clinically significant liver fibrosis in the general population [6].
While our study provided valuable insights into the pooled prevalence of clinically significant liver fibrosis and underscored the importance of early detection, we acknowledge the significant challenges that remain, as highlighted in the editorial.
First, we observed considerable heterogeneity among the studies, particularly regarding the use of different cutoffs for defining fibrosis and cirrhosis, as well as regional variations in prevalence rates. We fully agree with their comments that variations in these cut-offs can lead to discrepancies in reported prevalence rates. To address this, we carried out a sensitivity analysis by excluding studies that employed the highest and lowest cut-off values. The results were consistent with our main findings, thereby reinforcing the validity of pooling the data in a meta-analysis. Additionally, we conducted a leave-one-out sensitivity analysis to assess the robustness of our findings, which revealed that the effect size remained stable across all iterations. Nevertheless, further prospective studies are necessary to confirm these findings, particularly given the lack of standardized cut-offs for defining liver fibrosis. The elevated prevalence of liver fibrosis in American regions, which does not align with the previous report [7], also contributes to the observed heterogeneity. As noted in the Global Burden of Disease study, the prevalence of cirrhosis in different regions is influenced by varying risk factors [7]. In our analysis, we observed a higher prevalence of obesity in American populations compared to other regions.
Second, we concur that inconsistencies in defining the general population may introduce bias. The general population data in our analysis primarily comprises individuals participating in health checkups or volunteering, which may not accurately represent the true general population. Furthermore, substantial variations or lack of data on clinical risk factors, such as age, the prevalence of metabolic conditions (including obesity, dyslipidemia, and type 2 diabetes mellitus), and alcohol consumption, limit the generaliz-ability of our findings. To address these limitations, more comprehensive cohort studies that represent the general population and include key clinical risk factors, such as obesity, alcohol consumption, and metabolic profiles, are urgently needed.
Finally, although analyses of publication bias are generally not recommended or performed in proportion metaanalyses due to the lack of direct comparisons needed to evaluate bias towards positive or negative outcomes [8], we still evaluated publication bias using a funnel plot and Egger’s regression (Fig. 1). The results showed no significant publication bias (Egger’s test: P=0.21 for the Fibrosis-4 index, P=0.20 for F2 by vibration-controlled transient elastography [VCTE], P=0.37 for F3 by VCTE, and P=0.75 for F4 by VCTE).
Despite these limitations, we have identified previously undiagnosed asymptomatic clinically significant liver fibrosis in the general population. However, its prevalence varies depending on risk factors, emphasizing the importance of selecting at-risk populations for fibrosis screening. Moving forward, a multi-disciplinary approach involving hepatologists, primary care physicians, and specialists is crucial for improving early detection and intervention for chronic liver diseases. Strengthening public awareness and streamlining referral pathways will optimize patient outcomes and reduce the overall burden of CLD on healthcare systems [9-11].
In conclusion, while our study provides a strong foundation, we agree that further research is necessary to address the heterogeneity in NITs and better understand the prevalence of significant liver fibrosis across diverse populations. We believe that continued efforts to refine screening protocols and enhance interdisciplinary collaboration will be key to improving the early detection and management of liver fibrosis.
Once again, we thank the authors for their valuable editorial.

ACKNOWLEDGMENTS

The authors thank the Non-Invasive Testing (NIT) Guidelines Committee of the Korean Association for the Study of the Liver (KASL) for providing the opportunity to conduct this research.

FOOTNOTES

Authors’ contribution
HY Kim drafted and edited the manuscript. M Choi performed the statistical analyses and edited the manuscript. Dae Won Jun edited the manuscript. All the authors approved the final version of the manuscript.
Conflicts of Interest
The authors have no conflicts to disclose.

Figure 1.
Funnel plot of studies included in the meta-analysis for (A) advanced liver fibrosis by Fibrosis-4 index (P=0.21), (B) significant liver fibrosis (≥F2) by vibration-controlled transient elastography (VCTE) (P=0.20), (C) advanced liver fibrosis (≥F3) by VCTE (P=0.37), and (D) liver cirrhosis (F4) by VCTE (P=0.75). ES, effect size; SE, standard error.

cmh-2024-0777f1.jpg

Abbreviations

CLD
chronic liver disease
FIB-4
fibrosis-4
NIT
noninvasive test
VCTE
vibration-controlled transient elastography

REFERENCES

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