Comparison of various strategies to define the optimal target population for liver fibrosis screening: A population-based cohort study

Prediction of major liver-related events in the population using prognostic models

Liver disease poses a significant global health burden, with steatotic liver disease related to metabolic dysfunction and/or alcohol use being the most prevalent type. Current risk stratification strategies emphasize detecting advanced fibrosis as a surrogate marker for liver-related events (LREs), such as hospitalization, liver cancer, or death. However, fibrosis alone does not adequately predict imminent outcomes, particularly in fast-progressing individuals without advanced fibrosis at evaluation. This underscores the need for models designed specifically to predict LREs, enabling timely interventions. The Chronic Liver Disease (CLivD) risk score, the dynamic aspartate aminotransferase-to-alanine aminotransferase ratio (dAAR), and the Cirrhosis Outcome Risk Estimator (CORE) were explicitly developed to predict LRE risk rather than detect fibrosis. Derived from general population cohorts, these models incorporate either standard liver enzymes (dAAR and CORE) or risk factors (CLivD), enabling broad application in primary care and population-based settings. They directly estimate the risk of future LREs, improving on traditional fibrosis-focused approaches. Conversely, widely used models like the Fibrosis-4 index and newer ones, such as the LiverRisk and LiverPRO scores, were initially developed to detect significant/advanced fibrosis or liver stiffness. While not designed for LRE prediction, they have later been analyzed for this purpose. Integrating fibrosis screening with LRE-focused models like CLivD, dAAR, and CORE can help healthcare systems adopt proactive, preventive care. This approach emphasizes identifying individuals at imminent risk of severe outcomes, potentially ensuring better resource allocation and personalized interventions.

Noninvasive assessment of hepatic decompensation

Noninvasive tests (NITs) are used in all aspects of liver disease management. Their most prominent break-through since the millennium has been in advancing early detection of liver fibrosis, but their use is not limited to this. In contrast to the symptom-driven assessment of decompensation in patients with cirrhosis, NITs provide not only opportunities for earlier diagnoses but also accurate prognostication, targeted treatment decisions, and a means of monitoring disease. NITs can inform disease management and decision-making based on validated cutoffs and standardized interpretations as a valuable supplement to clinical acumen. The Baveno VI and VII consensus meetings resulted in tangible improvements to pathways of care for patients with compensated and decompensated advanced chronic liver disease, including the combination of platelet count and transient elastography to diagnose clinically significant portal hypertension. Furthermore, circulating NITs will play increasingly important roles in assessing the response to interventions against ascites, variceal bleeding, HE, acute kidney injury, and infections. However, due to NITs' wide availability, there is a risk of inaccurate use, leading to a waste of resources and flawed decisions. In this review, we describe the uses and pitfalls of NITs for hepatic decompensation, from risk stratification in primary care to treatment decisions in outpatient clinics, as well as for the in-hospital management of patients with acute-on-chronic liver failure. We summarize which NITs to use when, for what indications, and how to maximize the potential of NITs for improved patient management.

MOVING DIAGNOSIS OF LIVER FIBROSIS INTO THE COMMUNITY

Chronic liver diseases (CLD) are a leading cause of death worldwide, with alcohol consumption and metabolic risk factors as the two reasons accounting for the majority of cases of CLD in many developed countries. Currently there is a lack of specific strategies for early diagnosis of CLD and consequently most cases are diagnosed in advanced stages of the disease, which is associated with negative consequences for disease management and prognosis. Screening for CLD is based on either detection of chronic viral hepatitis B and C, or detection of liver fibrosis in patients with steatotic liver disease related to alcohol or metabolic dysfunction. There are non-invasive tools available for detection of liver fibrosis, including serological and imaging-based tests. Clinical practice guidelines recommend screening for liver fibrosis using algorithms that combine different non-invasive tests, with widely available but low accuracy tests such as FIB-4 for a first screening step in primary care setting, and other tests with less availability but higher accuracy, such as Transient Elastography or Enhanced Liver Fibrosis Test as a second step. There are different pathways for early detection of patients with CLD from primary to specialized care, where primary care providers are key for early detection, management and referral of patients. In addition, intervention on metabolic risk factors and alcohol consumption should be carried out in collaboration between specialized therapy and primary care. This review describes liver fibrosis from the community perspective, highlighting gaps in knowledge on how to define the optimal combination of tests, target population, the ideal pathway of care for CLD, and how to increase implementation of programs for early diagnosis of liver diseases in clinical practice.

Screening for liver fibrosis: lessons from colorectal and lung cancer screening

Many countries have incorporated population screening programmes for cancer, such as colorectal and lung cancer, into their health-care systems. Cirrhosis is more prevalent than colorectal cancer and has a comparable age-standardized mortality rate to lung cancer. Despite this fact, there are no screening programmes in place for early detection of liver fibrosis, the precursor of cirrhosis. In this Perspective, we use insights from colorectal and lung cancer screening to explore the benefits, challenges, implementation strategies and pathways for future liver fibrosis screening initiatives. Several non-invasive methods and referral pathways for early identification of liver fibrosis exist, but in addition to accurate detection, screening programmes must also be cost-effective and demonstrate benefit through a reduction in liver-related mortality. Randomized controlled trials are needed to confirm this. Future randomized screening trials should evaluate not only the screening tests, but also interventions used to halt disease progression in individuals identified through screening.

Algorithms for Early Detection of Silent Liver Fibrosis in the Primary Care Setting

More than one-third of the adult world population has steatotic liver disease (SLD), with a few percent of individuals developing cirrhosis after decades of silent liver fibrosis accumulation. Lack of systematic early detection causes most patients to be diagnosed late, after decompensation, when treatment has limited effect and survival is poor. Unfortunately, no isolated screening test in primary care can sufficiently predict advanced fibrosis from SLD. Recent efforts, therefore, combine several parameters into screening algorithms, to increase diagnostic accuracy. Besides patient selection, for example, by specific characteristics, algorithms include nonpatented or patented blood tests and liver stiffness measurements using elastography-based techniques. Algorithms can be composed as a set of sequential tests, as recommended by most guidelines on primary care pathways. Future use of algorithms that are easy to interpret, cheap, and semiautomatic will improve the management of patients with SLD, to the benefit of global health care systems.

Combined use of the ELF test and CLivD score improves prediction of liver-related outcomes in the general population

BACKGROUND AND AIMS

Effective and feasible population screening strategies are needed for the early detection of individuals at high risk of future severe liver-related outcomes. We evaluated the predictive performance of the combination of liver fibrosis assessment, phenotype profile, and genetic risk.

METHODS

Data from 5795 adults attending the Finnish Health 2000 Survey were linked with healthcare registers for liver-related outcomes (hospitalization, hepatocellular cancer, and death). Fibrosis was assessed using the enhanced liver fibrosis (ELF) test, phenotype profile by the chronic liver disease (CLivD) risk score, and genetic risk by a validated Polygenic Risk Score (PRS-5). Predictive performance was assessed by competing-risk analyses.

RESULTS

During a median 13-year follow-up, 64 liver-related outcome events were recorded. ELF, CLivD score, and PRS-5 were independently associated with liver-related outcomes. The absolute 10-year risk of liver-related outcomes at an ELF value of 11.3 ranged from 0.3% to 33% depending on the CLivD score. The CLivD score added 51% of new predictive information to the ELF test and improved areas under the curve (AUCs) from 0.91, 0.81, and 0.71 for ELF alone to 0.95, 0.85, and 0.80, respectively, for ELF combined with the CLivD score at 1, 5, and 10 years. The greatest improvement was for 10-year predictions (delta-AUC 0.097, p < .0001). Adding PRS-5 did not significantly increase predictive performance. Findings were consistent in individuals with obesity, diabetes, or alcohol risk use, and regardless of whether gamma-glutamyltransferase was used in the CLivD score.

CONCLUSION

A combination of ELF and CLivD score predicts liver-related outcomes significantly better than the ELF test alone.

Using the ELF test, FIB-4 and NAFLD fibrosis score to screen the population for liver disease

BACKGROUND AND AIMS

There is a need for accurate population screening biomarkers for alcohol-related and non-alcoholic fatty liver disease (ALD, NAFLD). We evaluated the Enhanced Liver Fibrosis (ELF) test compared to FIB-4 and NAFLD fibrosis score (NFS) using transient elastography (TE) as fibrosis screening reference.

METHODS

We prospectively included participants from the general population, and people at risk of ALD or NAFLD. Screening positive participants (TE ≥8 kPa) were offered a liver biopsy. We measured concomitant ELF, FIB-4, and NFS using validated cut-offs: ≥9.8, ≥1.3, ≥-1.45, respectively.

RESULTS

We included 3,378 participants (1,973 general population, 953 at risk of ALD, 452 at risk of NAFLD), with a median age of 57 years (IQR: 51-63). Two hundred-and-forty-two were screening positive (3.4% in general population, 12% in ALD, 14% in NAFLD). Most participants with TE <8 kPa also had ELF <9.8 (88%) despite a poor overall correlation between ELF and TE (Spearman´s rho=0.207). ELF had significantly fewer false positives (11%) than FIB-4 and NFS (35% and 45%), while retaining a low rate of false negatives (<8%). A screening strategy of FIB-4 followed by ELF in indeterminate cases resulted in 8% false positives, 4% false negatives and 88% correctly classified. We performed a liver biopsy in 155/242 (64%) screening positives, of those 54 (35%) had advanced fibrosis (≥F3). ELF diagnosed advanced fibrosis with significantly better diagnostic accuracy than FIB-4 and NFS: AUROC 0.85 (95% CI 0.79-0.92) versus 0.73 (0.64-0.81) and 0.66 (0.57-0.76).

CONCLUSION

The ELF test alone or combined with FIB-4 for liver fibrosis screening in the general population and at-risk groups reduces the number of futile referrals compared to FIB-4 and NFS, without overlooking true cases.

IMPACT AND IMPLEMENTATIONS

We need referral pathways that are efficient at detecting advanced fibrosis from alcohol-related and non-alcoholic fatty liver disease in the population, but without causing futile referrals or excessive use of resources. This study indicates that a sequential test strategy of FIB-4, followed by the ELF test in indeterminate cases leads to few patients referred for confirmatory liver stiffness measurement, while retaining a high rate of detected cases, and at low direct costs. This two-step referral pathway could be used by primary care for mass, targeted, or opportunistic screening for liver fibrosis in the population.

CLINICAL TRIAL NUMBER

Clinicaltrials.gov number NCT03308916.

Comparison of various strategies to define the optimal target population for liver fibrosis screening: A population-based cohort study

BACKGROUND & AIMS

Liver fibrosis screening is recommended in high-risk populations, but the optimal definition of "high risk" remains to be established. We compared the performance of several risk-stratification strategies in a population-based setting.

METHODS

Data were obtained from the Finnish population-based health examination surveys Health 2000 and FINRISK 2002-2012. The Chronic Liver Disease Risk Score (CLivD) was compared to previously published risk-stratification strategies based on elevated liver enzymes, alcohol use, diabetes, fatty liver index, body mass index, and/or metabolic risk factors for their ability to detect either advanced liver fibrosis or incident severe liver events. Advanced fibrosis was defined as an Enhanced Liver Fibrosis (ELF^TM ) score >9.8 in the Health 2000 study (n = 6084), and incident liver events were ascertained from registry linkage in the combined FINRISK 2002-2012 and Health 2000 cohort (n = 26,957).

RESULTS

Depending on the cohort, 53%-60% of the population was considered at risk using the CLivD strategy (low-intermediate-high risk, excluding the minimal-risk category), compared to 30%-32% according to the other risk-stratification strategies. The CLivD captured 85%-91% of cases in the population with advanced liver fibrosis and 90% of incident severe liver events within 10 years from baseline. This compares to 33%-44% and 56%-67% captured by the other risk-stratification strategies, respectively. The 10-year cumulative incidence of liver events varied by risk-stratification strategy (1.0%-1.4%).

CONCLUSIONS

Compared to previously reported traditional risk factor-based strategies, use of the CLivD captured substantially more cases with advanced liver disease in the population and may be superior for targeting further fibrosis screening.