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The global increase in the incidence of metabolic dysfunction-associated steatotic liver disease (MASLD), which affects more than one-third of the general population and up to 70% of individuals with type 2 diabetes or obesity, is a critical public health challenge. Given that liver steatosis is often asymptomatic until the advanced stages of disease, early detection is essential to prevent its progression to fibrosis, cirrhosis and, ultimately, hepatocellular carcinoma. However, liver biopsy, the gold-standard diagnostic method, is invasive, costly, and unsuitable for large-scale screening. As a result, noninvasive tests have emerged as practical alternatives, particularly in primary care settings, where early identification is most feasible. The present study explored current perspectives of noninvasive liver disease screening tools and their implementation in primary care. Serum-based indices, along with imaging techniques, have demonstrated promise in identifying patients with advanced fibrosis. Novel biomarkers, including the enhanced liver fibrosis test and Pro-C3, as well as emerging artificial intelligence-assisted diagnostic platforms, yield improved accuracy and risk stratification potential. Despite accumulating evidence supporting the clinical utility and cost-effectiveness of noninvasive tests, several barriers hinder their routine use in primary care settings, which include limited funding, lack of standardized guidelines, insufficient clinician training, and disparities in access to diagnostic tools. The implementation of structured stepwise screening models has demonstrated improved diagnostic efficiency and reduced unnecessary referrals. Future research should emphasize the integration of artificial intelligence, portable diagnostic devices, and personalized risk models to enhance early detection. Ensuring widespread adoption requires coordinated efforts in policy development, provider education, and health-system investment. Noninvasive screening tools offer a feasible and cost-effective pathway for the early detection of MASLD in primary care; however, their successful implementation depends on addressing logistical, educational, and systemic barriers.
The global burden of chronic liver disease has increased markedly. Modern lifestyle trends, particularly in high-income countries, have contributed to an increase in obesity and other metabolic syndrome-related conditions [1]. The role of metabolic dysregulation in the etiopathology of liver steatosis has been underscored in recent years, as reflected by changes in nomenclature. The term “non-alcoholic fatty liver disease” (NAFLD) has been replaced with “steatotic liver disease” (SLD) based on the 2023 Delphi Consensus [2]. According to the current classification, SLD serves as an umbrella designation that includes a wide range of conditions characterized by hepatic steatosis. These include metabolic dysfunction, excessive alcohol consumption, drug-induced liver injury, monogenic liver disorders, and various other causes, including cases with overlapping etiologies (Figure 1) [2]. Based on this new classification, metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most prevalent form of chronic liver disease. A recent meta-analysis comprising >11 million individuals reported a pooled global SLD prevalence of 37.5%. The prevalence was significantly higher among individuals with type 2 diabetes mellitus (T2DM) (70.2%) and in overweight or obese populations (70.7%) [1], highlighting the increasing importance of MASLD in the context of the ongoing global obesity epidemic. According to the World Health Organization (WHO), approximately 2.5 billion adults ≥18 years of age were classified as overweight in 2022, an alarming figure that continues to drive the rising prevalence of MASLD worldwide [3]. Liver steatosis can lead to serious complications, including fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) [4,5]. MASLD has become the fastest growing cause of HCC in several countries and is now the leading cause of HCC in Sweden [4,6,7]. The rapidly increasing prevalence of MASLD underscores the urgent need for effective screening strategies in primary care to prevent disease progression and associated complications, despite the absence of formal screening recommendations [2]. Consequently, there is an urgent need to develop a simple and reliable screening tool that enables primary care physicians to identify patients who may require specialist referral. An ideal tool should be cost effective, widely accessible, and easy to interpret. This review explores the current prospects of noninvasive screening tools and novel biomarkers, examines the rationale for implementing liver disease screening in primary care, and discusses key barriers and facilitators to its implementation. It also reviews evidence regarding the outcomes of such strategies in real-world settings.
Methods
A comprehensive literature search of the PubMed, Scopus, Embase, and Web of Science databases was performed to identify relevant studies investigating the implementation of noninvasive liver disease screening tools in primary care. The search was limited to studies published between January 2015 and May 2025. The following search terms were used in various combinations: (“noninvasive tests” OR “NITs” OR “FIB-4” OR “transient elastography” OR “NAFLD fibrosis score” OR “APRI” OR “elastography” OR “biomarkers” OR “AI in hepatology”) AND (“primary care” OR “general practice” OR “screening” OR “early detection” OR “risk stratification”). Additional sources included official clinical guidelines from the European Association for the Study of the Liver, WHO, and national health authorities, as well as relevant health economic evaluations. Studies were included if they fulfilled the following criteria: evaluated noninvasive methods for liver disease detection in adult patients; discussed implementation in primary care or community settings; assessed clinical performance, cost-effectiveness, or feasibility; and investigated emerging tools, including artificial intelligence (AI)-based models and novel biomarkers. Only full-text studies published in English were included. The exclusion criteria included studies that focused solely on pediatric populations, those with no clinical or implementation relevance, preclinical or animal model research, conference abstracts or editorials, and investigations lacking primary data, peer review, or methodological transparency. Qualitative appraisal of the included studies was based on design, population size, clinical applicability, and reporting transparency. Given the heterogeneity of the study types, ranging from diagnostic accuracy studies and real-world implementation reports to economic modeling and simulation analyses, a formal scoring system was not applied. After applying these criteria to the studies retrieved in the initial database search, 55 studies were ultimately selected for this review.
Rationale for Primary Care-Based Screening
The gold-standard diagnostic method for liver fibrosis, liver biopsy, is inherently limited by its invasive nature, risk for sampling error due to unrepresentative tissue specimens, and impracticality for widespread screening purposes [8]. Furthermore, the procedure is expensive, with an average cost ranging from US$1,500 to $3,000 in developed countries, further restricting its routine use [9]. In contrast, the integration of noninvasive screening methods into primary healthcare is a justified and pragmatic strategy, given the broad accessibility of primary care services and the large patient population that could benefit from early detection. Individuals with metabolic syndrome components can be systematically screened in primary care settings, which serves as a critical first step in identifying MASLD and guiding further diagnostic evaluations [10]. Early detection of high-risk individuals is essential because they are significantly more likely to progress to advanced stages of fibrosis [10]. Moreover, given that MASLD is currently the most prevalent chronic liver disease worldwide, and no pharmacological treatments have been approved to date, screening is even more critical for timely risk stratification and management [11]. In support of this approach, a simulation study by Corey et al. [12] demonstrated the potential clinical benefits. The hypothetical model predicted that screening using ultrasound, followed by treatment with pioglitazone, where appropriate, could result in a 12.0% reduction in the progression of liver fibrosis to cirrhosis and an 11.9% decrease in liver-related mortality compared with a non-screened population. Although indirect blood-based noninvasive tests (NITs) for liver fibrosis yield lower diagnostic accuracy than direct biomarkers or elastography, they offer several advantages, including low(er) cost, wide availability, utility in patients with obesity, and feasibility for point-of-care testing when elastography is not accessible [12]. For example, the body mass index (BMI)-AST/ALT-Ratio-Diabetes (BARD) score, which includes only three parameters—aspartate aminotransferase (AST)/alanine transaminase (ALT) ratio, presence of T2DM, and BMI—excluded 12% of patients at risk for liver disease from further evaluation using transient elastography (TE) [13]. However, reliance solely on NITs for confirmation is problematic. When used as confirmatory tools, the AST-to-Platelet Ratio Index (APRI) and Fibrosis-4 Index (FIB-4) were shown to miss 100% and 82% of cirrhosis cases, respectively, emphasizing their utility primarily as “rule-outs” rather than diagnostic tests [13]. Moreover, expert consensus suggests that cost-effective screening programs must be supported by the availability of effective follow-up treatments [10]. Overall, given the high prevalence of chronic liver diseases, particularly MASLD, which affects more than one-third of the general population, there is a pressing need for a structured, stepwise approach to noninvasive screening in primary care. Such strategies must balance accessibility, cost-effectiveness, and diagnostic accuracy to enable timely detection and improve patient outcomes.
Noninvasive Screening Tools
Several noninvasive screening tools are currently available for use in primary care settings. However, in the absence of strong clinical guidelines and limited specialized training among primary care providers, these tools have not been widely implemented in routine practice.
Serum-based indices
Given the high global prevalence of chronic liver disease, there is increasing interest in identifying alternative, cost-effective, and noninvasive methods for liver fibrosis assessment that can be feasibly integrated into primary care workflows. According to the current European guidelines, the first-line noninvasive tools recommended for use in primary care are the FIB-4 Index and the NAFLD Fibrosis Score (NFS), both of which are derived from routine serum biomarker data readily available in primary care settings [14]. The FIB-4 Index has gained attention as a viable alternative to liver biopsy for the diagnosis and management of liver fibrosis. It is calculated using a combination of patient age, AST and ALT levels, and platelet count, which are routinely measured and easily accessible in the primary care environment [15]. The NFS is another widely used tool that incorporates the same parameters as the FIB-4, with the addition of BMI, impaired fasting glucose, diabetes, and serum albumin levels. The NFS provides a three-tiered interpretation—low likelihood of advanced fibrosis, indeterminate risk, and high likelihood of advanced fibrosis—thereby guiding further diagnostic decisions and potential referrals [14]. However, the diagnostic performances of FIB-4 and NFS remain limited due to their suboptimal sensitivity and specificity [14]. A sequential diagnostic strategy, that is, initial screening with serum-based indices followed by TE in selected cases, has been proposed to yield economic benefits and reduce unnecessary specialist referrals [16]. In a study by Graupera et al. [16], these serum indices were found to carry a substantial risk for false-positives and a minor, although present, risk for false-negative results. Among individuals with FIB-4 values ≥1.3, 29% had a liver stiffness measurement (LSM) value ≤8 kPa and, similarly, 28% of those with NFS ≥−1.45 had LSM values ≤8 kPa. Additionally, the reliability of the FIB-4 Index has been shown to be reduced in specific age groups, particularly those <35 and >65 years of age. Therefore, interpretation in these populations should be approached with caution [17]. Another commonly used index is the APRI, which is calculated using routinely available laboratory parameters, such as AST and platelet counts. A significant correlation was demonstrated with FibroScan (Echosens) results (P<0.001) and has been proposed as a surrogate marker for identifying significant fibrosis, particularly in settings where FibroScan is not available [18,19]. Unlike FibroScan, the APRI can be widely applied without the need for specialized equipment and can be automatically calculated and interpreted using standard clinical software, enabling primary care physicians to use it effectively with minimal additional training. A summary of the required parameters and interpretation criteria for the serum-based indices is presented in Figure 2.
The need for simple and accessible screening tools is particularly evident in the context of MASLD, which affects approximately 30% of the general population and up to 70% of individuals in high-risk groups such as those with obesity or T2DM [1]. These patients are more susceptible to a range of comorbidities, many of which are routinely managed and screened in primary care settings [20]. Several indices are available for MASLD, including the Fatty Liver Index (FLI), NAFLD Liver Fat Score (LFS), Hepatic Steatosis Index (HSI), SteatoTest-2 score, and BARD score [21]. The FLI is based on BMI, waist circumference, and gamma-glutamyltransferase (GGT) and triglyceride levels. It demonstrates good diagnostic performance for detecting hepatic steatosis, with an area under the receiver operating characteristic (AUROC) of 0.85 (95% confidence interval [CI], 0.82–0.89) [21]. Similarly, the LFS detects hepatic steatosis but does not quantify its severity. It uses fasting insulin, AST and ALT levels, the presence of metabolic syndrome, and T2DM, with an AUROC of 0.80 (95% CI, 0.69–0.88) [21]. The HSI incorporates BMI, sex, T2DM status, and AST and ALT levels, with an AUROC of 0.80 (95% CI, 0.801–0.824) [21]. The SteatoTest-2 assesses hepatic steatosis with a sensitivity of 79% and specificity of 50% using parameters such as BMI, serum triglycerides, cholesterol, glucose, GGT, ALT, total bilirubin, haptoglobin, alpha-2 macroglobulin, and apolipoprotein A1 [22]. The BARD score incorporates three clinical parameters, BMI, AST/ALT ratio, and presence of T2DM [21]. A comparative overview of noninvasive screening tools for SLD is presented in Table 1.
Imaging tests
Although liver biopsy remains the gold-standard method for assessing fibrosis in patients with SLD, its invasive nature, risk for complications, and an associated patient discomfort significantly limit its routine use [23]. Additionally, its applicability in primary care is restricted because primary care clinicians are not trained to perform or interpret liver biopsies [23]. Consequently, noninvasive imaging techniques, particularly ultrasound-based methods, have gained prominence for assessing liver stiffness. These include TE techniques such as FibroScan, two-dimensional shear wave elastography, and multidimensional elastography [19]. Among these, the FibroScan is the most commonly used device [24]. It provides simultaneous evaluation of hepatic fat content and liver stiffness, although its diagnostic accuracy may be affected by obesity [19]. FibroScan measures the controlled attenuation parameter (CAP) for steatosis and the LSM for fibrosis [25]. The diagnostic performance of FibroScan varies according to fibrosis stage. Reported AUROC values are 0.86 for ≥F1, 0.80 for ≥F2, 0.94 for ≥F3, and ≥0.97 for F4 fibrosis [25]. A novel tool for assessing steatosis is visual real-time liver steatosis analysis (LiSA), which offers a real-time imaging alternative to CAP. In a study by Ren et al. [26], both the LiSA and CAP demonstrated strong diagnostic performances (AUROC>0.7), with no statistically significant difference (P=0.067). LiSA achieved a sensitivity of 79.16% and a specificity of 89.18% for detecting hepatic steatosis.
Novel Biomarkers
Among the emerging noninvasive tools for liver fibrosis assessment, the enhanced liver fibrosis (ELF) test is one of the most promising. Although it is only currently commercially available, ELF has demonstrated superior diagnostic accuracy in patients with alcohol-related liver disease (ALD) and MASLD [14]. This test measures three serum biomarkers: hyaluronic acid, tissue inhibitor of metalloproteinase-1, and N-terminal type III procollagen peptide [21]. In a population-based study from Denmark, Kjaergaard et al. [14] compared the ELF test with the FIB-4 and NFS tests for screening purposes. The ELF test yielded fewer false positives (11%) than the FIB-4 (35%) and NFS (45%) tests, with a false-negative rate <8%. Diagnostic performance was significantly higher for the ELF test, with an AUROC of 0.85 (95% CI, 0.79–0.92), compared with 0.73 (95% CI, 0.64–0.81) for FIB-4 and 0.66 (95% CI, 0.57–0.76) for NFS [14]. A sequential screening approach using FIB-4 as an initial test, followed by the ELF test in indeterminate cases, optimized the diagnostic yield and correctly identified advanced fibrosis in 88% of cases, with only 8% false positives and 4% false negatives [14]. Another novel biomarker under investigation is Pro-C3, which reflects type III collagen formation and has demonstrated potential as a stand-alone marker for liver fibrosis. Although Pro-C3 has demonstrated reasonable diagnostic accuracy (AUROC=0.75), its use remains limited in routine clinical practice due to its restricted availability and high cost [21].
Outcomes of Implementation
Universal, noninvasive screening for SLD is currently not recommended for the general population. Instead, a targeted approach is advised, focusing on high-risk individuals, particularly those with metabolic comorbidities such as T2DM, hyperlipidemia, or a BMI >25 kg/m2 [27]. Screening this high-risk group is more cost-effective than forgoing screening altogether [27,28]. Implementation of a “FIB-4 first” model, in which initial screening is performed using the FIB-4 Index, followed by TE only in selected cases, has been shown to significantly reduce unnecessary elastography testing and specialist referrals [29]. In a study by Davyduke et al. [29], a FIB-4 threshold of 1.3 was found to be appropriate for ruling out advanced fibrosis. Further modeling demonstrated that factors including age, T2DM, and BMI, only had a moderate influence on the relationship between FIB-4 scores and TE measurements when the 1.3 threshold was applied. Transferring the initial risk stratification process to the primary care level improves diagnostic efficiency, reduces healthcare system burden, and streamlines referral pathways, ensuring that only patients at high(er) risk for advanced fibrosis are referred for further specialist evaluation [29]. When comparing various diagnostic strategies, the combination of FIB-4 and ELF testing in primary care, followed by TE in specialty care, appears to offer the most favorable balance between clinical effectiveness and cost-effectiveness [30]. A similar model has been proven to be effective for ALD, in which the use of ELF as an initial test in primary care, followed by LSM in positive cases, represents a cost-effective approach. In high-prevalence populations, direct referral for LSM may be even more economically favorable [31]. Noninvasive screening tools are both clinically effective and cost-efficient when implemented at the primary care level. A study comparing the performance of FibroSure (LabCorp), FibroSpect II (Prometheus Laboratories) and FibroScan in evaluating liver fibrosis found that FibroScan was the most cost-effective, with the lowest cost per test (US$131) and per correct diagnosis (US$159), resulting in an estimated US$1,124 in savings per patient relative to liver biopsy [32]. The multiple diagnostic methods for SLD vary in terms of both cost and clinical utility. Among the least expensive are index-based tools, such as FLI and HSI, which use routine laboratory parameters but lack accuracy in grading steatosis [27]. Other low-cost tools include the NFS and BARD scores, although these are less reliable in patients with mild disease, particularly in those with obesity or T2DM [27]. Special consideration is warranted when applying noninvasive screening strategies to Asian populations. Several studies have suggested that metabolic risk profiles, body composition, and disease progression patterns in Asian individuals may differ from Western populations [33,34]. For example, advanced fibrosis can develop at lower BMI thresholds in Asians, and NAFLD or MASLD may even be present in individuals without obesity [33,35]. As such, BMI-based screening cut-offs and fibrosis risk models, such as the FIB-4 and NFS, may require population-specific validation or adjusted thresholds [36]. Notably, evidence supporting the cost-effectiveness and diagnostic performance of NITs in Asian populations is limited, highlighting the need for regionally tailored research and implementation strategies.
Barriers to Implementation
Several barriers hinder implementation of NITs in primary care clinics. Because MASLD is typically asymptomatic, diagnoses are often incidental, underscoring the urgent need for optimal and noninvasive screening tools [1]. One of the main concerns surrounding their use is cost-effectiveness. With MASLD affecting nearly one-third of the general population and up to 90% of high-risk groups, such as those with T2DM or obesity, large-scale screening initiatives could impose a substantial economic burden on healthcare systems [1]. However, studies have shown that using tools, such as FIB-4, ELF, or TE in primary care, improves the detection of chronic liver diseases, such as MASLD, and hepatitis C and B virus infection [37-39]. Early diagnosis using these methods can reduce the incidence of complications, which are typically far more expensive to manage than the underlying liver disease itself [40]. The limited funding for NITs remains a significant barrier to their implementation. Evidence suggests that various NITs are not consistently reimbursed or financially supported across various healthcare systems [41,42]. Although these tools are generally less expensive than liver biopsy, their costs can still be considerable, and their availability in primary care settings is often limited [43,44]. An additional concern is the potential bias in costeffectiveness analyses, particularly when designed by statisticians, who may not fully consider the clinical complexity of real-world patient management. Some studies have suggested that optimal accuracy may require multiple NITs to be used simultaneously, which further increases the costs and logistical burden [41]. Notably, a significant barrier to implementation is the insufficient training of primary care clinicians in the use of noninvasive imaging techniques such as elastography, compounded by limited awareness of the current burden of MASLD and time constraints during routine consultations [45]. Vali et al. [42] reported that, among 27 completed surveys and 16 clinician interviews, none used the Pro-C3 test, while FibroScan was widely used and ELF was used by only three respondents, highlighting a lack of training in less familiar tools. Another study involving clinicians from Germany, Italy, United Kingdom, and United States found that many did not fully understand how to interpret NIT results or believed that the absence of disease-modifying therapies rendered testing unjustified [41]. However, the use of simpler screening tools based on routinely available blood tests offers a practical alternative in primary care settings [45]. These tools can effectively stratify patients according to risk, enabling timely referral to specialists for further evaluation using advanced imaging modalities [45]. In addition, diagnostic accuracy may vary across different patient populations. A single test may not be sufficient to assess complex liver pathology and specific subgroups, such as children, remain understudied [46]. Pediatric elastography lacks strong validation and does not provide insights into inflammation, necrosis, or hepatic fat content [46]. There is also a notable lack of research across diverse racial and ethnic populations, which could affect diagnostic sensitivity and generalizability [47]. The lack of clear guidelines regarding when and where patients should be referred for further management remains an ongoing issue [48]. Communication barriers and disease-related stigma also contribute to the low testing uptake. Physicians may hesitate to initiate conversations about liver disease, especially when patients are asymptomatic or overweight, further limiting the use of NITs in primary care [41]. A summary of the barriers to the implementation of NITs is presented in Figure 3. Addressing these barriers is essential to improve the feasibility, accuracy, and clinical impact of noninvasive liver disease screening in primary care settings.
Future Directions
Advances in AI and the development of portable FibroScan devices have opened new possibilities for the early detection of hepatic steatosis and fibrosis in primary care settings [49]. Ongoing research is exploring the integration of AI to support the interpretation of FibroScan results. Preliminary evidence suggests that AI-assisted analysis can significantly improve diagnostic sensitivity and accuracy [50]. For example, Fargose et al. [50] reported that a combined hybrid model integrating fixed probabilities from blood test data with deep-learning predictions based on ultrasound images achieved an overall diagnostic accuracy of 92.5%, highlighting the potential of such integrated AI models to enhance diagnostic precision and support earlier interventions in the management of liver disease. AI-based predictive models are also being developed to assess the clinical trajectories of MASLD [51,52]. Ben-Assuli et al. [51] implemented a noninvasive fibrosis assessment approach derived from routine clinical data, eliminating the need for liver biopsies. Their findings demonstrated that latent class modeling could play a significant role in improving the delivery of care by facilitating earlier and more accurate risk stratification. These applications offer the potential to shift focus from the treatment of advanced diseases to early, cost-effective prevention [51]. However, large-scale validation and real-world testing are necessary before these technologies can be widely adopted in clinical practice. Beyond liver-specific diagnostics, AI can also support broader management of metabolic syndrome by continuously analyzing clinical parameters such as blood pressure, blood glucose, and lipid profiles [53]. Regular monitoring of these metrics enables the early detection of risk factors associated with MASLD and other components of the metabolic syndrome. Patients who use AI-based self-monitoring platforms input their own blood glucose and blood pressure measurements, and receive personalized lifestyle recommendations such as dietary modifications and increased physical activity experienced significant improvements in overall health outcomes, emphasizing the need for tailored, individualized approaches to manage highly prevalent liver diseases in at-risk patient populations [54]. However, further research is needed to establish a robust evidence base for integrating AI into the self-management of chronic conditions to achieve optimal long-term health outcomes [54]. Recent studies have emphasized the diagnostic potential of AI for liver diseases. Popa et al. [55] reported that AI-assisted, noninvasive diagnostic tools for hepatic steatosis and fibrosis demonstrated an accuracy comparable with that of clinical experts. Such technologies offer the ability to automate diagnosis, staging, and risk stratification, potentially overcoming the limitations of current noninvasive methods. One of the key priorities of hepatology experts is the development of clear and accessible guidelines for screening chronic liver diseases in primary care settings. In the absence of such recommendations, many healthcare providers are uncertain when and how to screen patients, leading to underdiagnosis and/or missed opportunities for early intervention. A summary of the recommended actions to facilitate the implementation of noninvasive liver disease screening in primary care is presented in Table 2.
Conclusion
The growing burden imposed by MASLD underscores the urgent need for effective and scalable screening strategies, particularly at the primary care level. Given the high prevalence of MASLD in both the general population and high-risk groups, early identification is essential to prevent its progression to advanced fibrosis, cirrhosis, and HCC. NITs offer practical alternatives that can be integrated into primary care workflows. However, challenges related to diagnostic accuracy, limited accessibility, inconsistent funding, and insufficient training among primary care providers have hindered their widespread use. Notably, variability exists across studies regarding the diagnostic performance of tools, such as FIB-4, NFS, and ELF, often due to differences in patient populations, fibrosis prevalence, BMI thresholds, and clinical settings. The reported false-positive rates and cost-effectiveness vary depending on whether these tools are used in the general population or in high-risk cohorts. Recognizing and addressing these discrepancies is critical for tailoring appropriate implementation models. Although many of the studies included in this review supported the use of NITs, several limitations must be acknowledged. These include small sample sizes, retrospective designs, lack of external validation, and variability in outcome definitions. Economic models are also susceptible to bias, because they rely on theoretical assumptions. These limitations should be considered when interpreting individual study results and translating the findings into practice. Despite these challenges, current evidence suggests that the combination of simple serum-based screening tools, followed by confirmatory elastography in selected cases, represents a cost-effective and clinically viable approach. Early detection using such strategies has the potential to reduce liver-related morbidity and mortality, particularly by facilitating timely intervention before the onset of irreversible liver damage. Moreover, novel biomarkers and advances in AI offer promising avenues for enhancing diagnostic accuracy and enabling individualized risk stratification. To fully realize the potential of noninvasive liver disease screening in primary care, clear clinical guidelines, targeted provider education, improved access to diagnostic tools, and health system-level support are required. These steps will help ensure timely diagnosis, appropriate referral, and improved outcomes in patients at risk for liver-related complications.
Article Information
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Funding
None.
Data availability
Not applicable.
Author contribution
Conceptualization: KN, AN, JJ. Investigation: KN, AN, AJ, AP, JS, ND. Project administration: KN, AP, JS, JJ. Supervision: JJ. Writing–original draft: KN, AN, AJ, AP, JS, ND, JJ. Writing–review & editing: KN, AJ, JS, ND, JJ. Final approval of the manuscript: all authors.
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, Adrian Nowak
