Abstract
Background
With the rate of non-alcoholic fatty liver disease (NAFLD) on the rise, the necessity of identifying patients at risk of cirrhosis and its complications is becoming ever more important. Liver biopsy remains the gold standard for assessing fibrosis, although costs, risks, and availability prohibit its widespread use with at-risk patients. Transient elastography has proven to be a non-invasive and accurate way of assessing fibrosis, although the availability of this modality is often limited in primary care settings. The Fibrosis-4 (FIB-4) and Non-Alcoholic Fatty Liver Disease Fibrosis Score (NFS) are scoring systems that incorporate commonly measured lab parameters and BMI to predict fibrosis.
Method
In this study, we compared FIB-4 and NFS scores with transient elastography scores to assess the accuracy of these inexpensive and readily available scoring systems in detecting fibrosis.
Results
Using an NFS score cut-off of –1.455 and a FibroScan score cut-off of ≥8.7 kPa, the NFS score had a negative predictive value of 94.1%. Using a FibroScan score cut-off of ≥8.7 kPa, the FIB-4 score had a negative predictive value of 91.6%.
Conclusion
The NFS and FIB-4 are non-invasive, inexpensive scoring systems that have high negative predictive value for fibrosis compared with transient elastography scores. These findings suggest that the NFS and FIB-4 can provide adequate reassurance to rule out fibrosis in patients with NAFLD and can be used with select patients to circumvent the need for transient elastography or liver biopsy.
Keywords: cirrhosis, fibrosis, liver, non-alcoholic fatty liver, transient elastography
Introduction
Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder in Western countries, with a reported prevalence of 6%–35% (1–3). NAFLD is defined as evidence of hepatic steatosis, either by imaging or by histology, and no causes for secondary hepatic fat accumulation such as significant alcohol consumption, use of steatogenic medication, or hereditary disorders (4). The major risk factors include central obesity, type 2 diabetes mellitus, dyslipidemia, and metabolic syndrome.
Patients with NAFLD are known to have increased overall mortality compared with matched control populations without NAFLD, with this risk increasing with progression to non-alcoholic steatohepatitis (NASH) and fibrosis. These patients are at increased risk of cardiovascular death, hepatocellular carcinoma (HCC), and other liver-related mortality (5). NAFLD is now considered the third most common cause of HCC in the United States, and NASH is now ranked as the second most common cause of liver transplant and will likely overtake viral hepatitis as the number one cause of liver transplant in the near future (4,6,7).
The most important histological feature of NAFLD associated with long-term mortality is fibrosis, specifically zone 3 sinusoidal fibrosis and periportal fibrosis (stage 2) to advanced fibrosis (bridging; stage 3) or cirrhosis (8). Therefore, identifying where patients lie on this spectrum is of prognostic significance, and it also has the potential to guide pharmacological management. Vitamin E has been shown to reduce steatohepatitis but to have no effect on fibrosis (9), and studies using pioglitazone have had conflicting results (9,10). Recently, interim results of the REGENERATE trial (Randomized Global Phase 3 Study to Evaluate the Impact on NASH With Fibrosis of Obeticholic Acid Treatment) have suggested that obeticholic acid improves fibrosis in patients with NASH (11). In addition to informing prognosis and guiding therapies, identifying the presence of fibrosis in an undifferentiated population of patients with NAFLD can help determine who needs referral to a hepatologist or close monitoring for complications as well as for clinical trial selection.
With the prevalence of NAFLD on the rise, the necessity of identifying patients at risk for NASH and progression to cirrhosis is becoming ever more important. Currently, the American Association for the Study of Liver Diseases does not recommend routine screening for NAFLD or NASH in high-risk groups, given the uncertainty of treatment options and the lack of data supporting long-term benefits from screening, although it does recommend having a high degree of vigilance with patients with type 2 diabetes and suggests screening these patients with lab-based scoring systems or transient elastography (TE) (12). Liver biopsy remains the gold standard for assessing fibrosis, although the costs, risks, and availability prohibit its widespread use for at-risk patients. TE has proven to be a non-invasive and accurate way of assessing fibrosis, although this modality often has limited availability in the primary care setting, where the need for a lab-based risk stratification system is more practical (7). The Fibrosis-4 (FIB-4) and Non-Alcoholic Fatty Liver Disease Fibrosis Score (NFS) are scoring systems that incorporate commonly measured lab parameters. The FIB-4 uses age, aspartate transaminase (AST), alanine aminotransferase (ALT), and platelet count and has been shown to predict the absence of significant fibrosis (13,14). The NFS uses the same parameters as the FIB-4 and additionally incorporates BMI, albumin, and presence of diabetes in the calculation. Angulo et al reported that NFS accurately predicted fibrosis when compared with liver histology (15).
The decision to pursue liver biopsy in the setting of chronic liver disease requires careful consideration of multiple variables, one of which is often the TE score. Establishing a high level of accuracy of non-invasive scoring systems to predict fibrosis could potentially reduce the number of TE scans needed among patients with NAFLD and moreover may circumvent the need for liver biopsy. It would also allow clinicians to inexpensively and efficiently follow the trajectory of disease. This study aimed to establish the accuracy of FIB-4 and NFS for detecting fibrosis in NAFLD in comparison with TE scores.
Methods
The study was conducted at the Vancouver General Hospital hepatology clinic and was approved by the University of British Columbia Research Ethics Board. We performed a retrospective chart review of clinical data collected at patients’ visits. We reviewed the clinical data of patients who received a diagnosis of NAFLD or NASH; who were referred between September 1, 2014, and June 1, 2018; and who had at least one TE result.
The inclusion criteria were as follows:
Liver disease compatible with NAFLD as evidenced by imaging or biopsy in the presence of at least one metabolic disease risk factor—hypertension (≥130/85 mmHg), high serum triglyceride levels (≥1.7 mmol/L), low serum high-density lipoprotein (≤0.9 mmol/L), glucose intolerance or diabetes (fasting plasma glucose >6.0 mmol/L, hemoglobin A1c (HbA1c) ≥6.0%, 2 hr oral glucose tolerance test >7.7mmol/L), truncal obesity (waist-to-hip ratio >0.9 cm or waist circumference >102 cm for men and >0.85 or >88 cm, respectively, for women), or ethnic risk factors (Asian or Latin American descent)
Aged ≥19 years at the time of the TE reading
BMI (kg/m2) available within 2 months before the TE reading
The exclusion criteria were as follows:
Primary causes of hepatic steatosis (genetic disorders of metabolism)
Other causes of liver disease, including hepatitis B, hepatitis C, Wilson’s disease, autoimmune hepatitis, primary biliary cholangitis, primary sclerosing cholangitis, drug-induced liver injury, or alpha-1-antitrypsin deficiency
Presence of ascites, HCC, intrahepatic cholangiocarcinoma, large (>5 cm) benign liver tumours, including hemangiomas, adenoma, or focal nodular hyperplasia
Presence of direct hyperbilirubinemia (total bilirubin >34 µmol/L with >50% of direct fraction)
Liver disease secondary to post-hepatic vascular flow obstruction (right heart failure, Budd-Chiari syndrome, concomitant diagnosis of sinusoidal obstruction or portosinusoidal disease)
Alcohol consumption of >15 units/week in men or >10 units/week in women (a unit of alcohol was defined as 1.5 oz of spirits, 5 oz of wine, or 12 oz of beer)
TE results were measured using FibroScan (Echosens, Paris, France). At least 10 readings were performed, and only results with an interquartile range <0.30 were considered valid. All patients were weighed using an electronic scale and measured on their clinic visit by the same investigator (VM). The fibrosis score was determined within 2 months of the most recent laboratory blood results.
Variables collected included age (years), gender (male or female), body mass index (BMI; kg/m2), presence of hypertension (treated with at least one anti-hypertensive agent), triglycerides (mmol/L), HbA1C (%), AST (IU/L), ALT(IU/L), platelet count (109/L), bilirubin (mmol/L), international normalized ratio (INR), albumin (g/L), ferritin (µg/L) , alcohol consumption (units/week), TE score (kPa), and liver biopsy results if available. Our clinic was not equipped with a probe to measure the controlled attenuation parameter score at the time the data were collected.
Statistical analysis
The FIB-4 score was calculated using the following equation:
The NFS was calculated using the following equation:
The results of the FIB-4 and NFS were compared with two different TE results (>8.0 kPa and >8.7 kPa). The cut-off of 8.7 was chosen on the basis of the study by Wong et al, showing that this cut-off had a 95% negative predictive value for F3 or greater fibrosis using these values (16). The value of 8.0 kPa was chosen to test whether it could increase the sensitivity of the lab base testing. We calculated diagnostic parameters for the FIB-4 and NFS using cut-offs of >1.30 and <–.455, respectively. These values were chosen on the basis of previous literature demonstrating a strong negative predictive value for ruling out biopsy-proven advanced fibrosis at these cut-offs (15,17). The diagnostic parameters included the sensitivity, specificity, positive and negative predictive value, receiver operating characteristic (ROC) area, and positive and negative likelihood ratios. We then combined both the FIB-4 and the NFS and determined the negative predictive value of having normal results for both in ruling out significant fibrosis (as determined by TE results).
We evaluate the number of referrals for TE that could potentially be avoided by using the NFS or the FIB-4 as a first step in the risk evaluation of detection of fibrosis score ≥8.7 kPa. Finally, we assessed whether features of metabolic syndrome (BMI >30 kg/m2, history of hypertension, or impaired fasting glucose) could predict the presence of high TE results in patients with low NFS or FIB-4 scores.
Continuous variables are presented as means or medians with their standard deviation or interquartile range, respectively. Categorical data are presented as proportions. All inferential analyses are presented with their 95% confidence interval. Analyses were performed using Stata version 15.1 (StataCorp, College Station, Texas, USA)
Results
Data were collected from 317 patients. After removing patients with insufficient data, 224 remained, and their data were used for the study. The average age was 51.1 years, and the gender distribution was 50%–50%. Almost half of the group had a history of glucose intolerance or diabetes. The mean values for patient characteristics are as follows: BMI, 28.9 kg/m2; triglycerides, 1.77 mmol/L; HbA1C, 6.01%; AST, 39.1 IU/L; ALT, 56.2 IU/L; platelets, 248.8; bilirubin, 10.9 mmol/L; INR, 1.00; albumin, 43.6 g/L; ferritin, 145 µg/L; and liver stiffness, 5.2 kPa. Eighty-three patients (37.1%) had a history of hypertension, 32 (14.3%) had liver stiffness >8.7 kPa, and 39 (17.4%) had liver stiffness >8.0 kPa (Table 1).
Table 1:
Patient characteristics (N = 224)
| Variable | Mean (SD)* |
|---|---|
| Age, y | 51.1 (12.3) |
| Gender, n (%) | |
| Male | 112 (50) |
| Female | 112 (50) |
| BMI | 28.9 (5.3) |
| Impaired fasting glucose, n (%) | 49 (21.9) |
| Hypertension, n (%) | 83 (37.1) |
| Triglycerides, mmol/L | 1.77 (1.09) |
| HbA1c, % | 6.01 (1.22) |
| AST, IU/L | 39.1 (39.2) |
| ALT, IU/L | 56.2 (49.7) |
| Platelets, ×109/L | 248.8 (66.1) |
| Bilirubin, mmol/L | 10.9 (6.5) |
| INR | 1.00 (0.09) |
| Albumin, g/L | 43.6 (3.69) |
| Ferritin, ug/L, median (IQR) | 145 (61–311) |
| Liver stiffness | |
| kPa, median (IQR) | 5.2 (4.4–6.8) |
| ≥8.7 kPa, n (%) | 32 (14.3) |
| ≥8.0 kPa, n (%) | 39 (17.4) |
Unless otherwise indicated
HbA1c = Hemoglobin A1c; AST = Aspartate aminotransferase; ALT = Alanine aminotransferase; INR = International normalized ratio; IQR = Interquartile range
When comparing NFS (cut-off –1.455) with a FibroScan score of ≥8.7kPa, the sensitivity and specificity were 71.9% and 75.0%, respectively, with a negative predictive value of 94.1%. When comparing NFS with a FibroScan score of ≥8.0 kPa, the sensitivity and specificity were 66.7% and 75.7%, respectively, with a negative predictive value of 91.5% (Table 2).
Table 2:
Performance of NFS (cut-off = –1.455) against FibroScan with cut-offs of ≥8.7 kPa and ≥8.0 kPa for significant fibrosis
| Variable | Fibrosis score | |
|---|---|---|
| ≥8.7 kPa | ≥8.0 kPa | |
| Disease prevalence, % | 14 | 17 |
| Sensitivity, % (range) | 71.9 (53.3 to 86.3) | 66.7 (49.8 to 80.9) |
| Specificity, % (range) | 75.0 (68.3 to 81) | 75.7 (68.8 to 81.7) |
| ROC area | 0.73 (0.65 to 0.82) | 0.71 (0.63 to 0.79) |
| Likelihood ratio | ||
| + | 2.88 (2.07 to 3.99) | 2.75 (1.96 to 3.84) |
| – | 0.38 (0.21 to 0.66) | 0.44 (0.28 to 0.69) |
| Positive predictive value, % (range) | 32.4 (21.8 to 44.5) | 36.6 (25.5 to 48.9) |
| Negative predictive value, % (range) | 94.1 (89.1 to 97.3) | 91.5 (85.9 to 97.3) |
NFS = Non-Alcoholic Fatty Liver Disease Fibrosis Score; ROC = Receiver operating characteristic
When comparing the FIB-4 score (cut-off 1.3) with a FibroScan score of ≥8.7 kPa, the sensitivity and specificity were 53.1% and 84.9%, respectively, with a negative predictive value of 91.6%. When comparing FIB-4 with a FibroScan score of ≥8.0 kPa, the sensitivity and specificity were 51.3% and 85.9%, respectively, with a negative predictive value of 89.3% (Table 3).
Table 3:
Performance of FIB-4 (cut-off >1.3) against FibroScan with cut-offs of ≥8.7kPa and ≥8.0 kPa for significant fibrosis
| Variable | Fibrosis score | |
|---|---|---|
| ≥8.7 kPa | ≥8.0 kPa | |
| Prevalence, % | 14 | 17 |
| Sensitivity, % (range) | 53.1 (34.7 to 70.9) | 51.3 (34.8 to 67.6) |
| Specificity, % (range) | 84.9 (79 to 89.6) | 85.9 (80.1 to 90.6) |
| ROC area | 0.69 (0.60 to 0.78) | 0.69 (0.60 to 0.77) |
| Likelihood ratio | ||
| + | 3.52 (2.2 to 5.6) | 3.65 (2.28 to 5.84) |
| – | 0.55 (0.38 to 0.80) | 0.57 (0.41 to 0.79) |
| Positive predictive value, % (range) | 37.0 (23.2 to 52.5) | 43.5 (28.9 to 58.9) |
| Negative predictive value, % (range) | 91.6 (86.5 to 95.2) | 89.3 (83.8 to 93.4) |
FIB-4 = Fibrosis–4; ROC = Receiver operating characteristic
The FIB-4 and NFS were then combined to test whether using the results of both tests simultaneously could improve diagnostic accuracy. We compared both tests being normal with either or both being abnormal in predicting a fibrosis score ≥8.7 kPa. The sensitivity of combined scores was 71.9% (IQR 53.3 to 86.3), and the specificity was 75% (IQR 68.3% to 81.0%) with an area under the ROC of 0.734 (0.65 to 0.82). The NPV was 94.1% (IQR 89.1 to 97.3). There was no statistical difference between the area under the ROC for NFS, FIB-4, or both scores combined in predicting a fibrosis score ≥8.7 kPa.
A two-step pathway was used. If a strategy of referral to TE using a FIB-4 cut-off of 1.3 was used, only 46 of the 224 patients (20.5%) would have been referred. Among the 178 patients who were not referred, we would have missed 15 (8.4%) with TE scores ≥8.7 kPa. If a strategy of referral to TE using an NFS cut-off of –1.455 was used, only 71 of the 224 patients (31.7%) would have been referred. Among the 153 patients who were not referred, we would have missed 9 (5.9%) with TE scores ≥8.7 kPa.
History of impaired fasting glucose was identified as an independent predictor of a high TE score (>8.7 kPa) in patients with FIB-4 ≥1.3 with an OR of 7.32 (95% CI 2.05 to 26.1). Hypertension was also an independent predictor of a high TE score (>8.7 kPa) in patients with FIB-4 ≥1.3 with an OR of 1.62 (95% CI 0.45 to 5.8) (Table 4). A history of high BMI and history of impaired fasting glucose are part of the NFS calculation, so we did not perform the same analysis because it could introduce bias.
Table 4:
Clinical predictors of fibrosis ≥8.7 kPa in patients with a FIB-4 ≥1.3
| Variable | OR (95% CI) | |
|---|---|---|
| Univariate | Multivariate | |
| BMI ≥ 30 kg/m2 | 1.18 (1.07 to 1.30) | 3.35 (0.94 to 12) |
| History of impaired fasting glucose | 12.2 (3.81 to 38.9) | 7.32 (2.05 to 26.1) |
| History of hypertension | 3.93(1.27 to 12.05) | 1.62 (0.45 to 5.8) |
OR = Odds ratio; CI = Confidence interval
Using a strategy of referral to TE of patients with FIB-4 >1.3 or with a history of glucose intolerance, only 79 patients (35.2%) would have been referred. Among the 145 patients who would have avoided referral, significant fibrosis would have been missed in only 5 (3.4%).
Discussion
With the prevalence of NAFLD on the rise, the ability to recognize patients who are at high risk of progression is becoming an ever more important challenge. Liver biopsy is the gold standard for identifying the degree of fibrosis, but the associated risks and limited access render this an impractical screening tool. Similarly, TE has been shown to effectively measure liver fibrosis, but it is offered in only a minority of centres, limiting access for patients in peripheral communities. This has led to the need for an inexpensive and easily accessible screening tool for fibrosis in NAFLD that can be performed by primary care physicians or physicians caring for patients at higher risk of NASH. Our study evaluated the performance of NFS and FIB-4 against TE scores for predicting fibrosis in NAFLD. Previous studies have evaluated the performance of NFS and FIB-4 against liver biopsy proven fibrosis and have demonstrated a strong correlation (14–17). Given that TE scores have been shown to accurately predict degree of fibrosis seen in liver biopsy (18), we expected that NFS and FIB-4 would similarly correlate well with TE scores. Our results suggest that both modalities have reasonably strong negative predictive values (89.1% and 86.5%, respectively, using a TE score cut-off of ≥8.7 kPa), and can be used in lieu of TE with selected patients. The low positive predictive values of NFS and FIB-4 (32.4% and 37.0%, respectively, using a TE score cut-off of ≥8.7 kPa) highlight that these tools cannot be used to diagnose fibrosis but rather should be used only as a screening tool to rule out fibrosis. These low positive predictive values are consistent with previous studies.
Two steps pathways have been evaluated in prior studies. Srivastava et al published a prospective study using an initial screening with FIB-4 followed by enhanced liver fibrosis test (ELF) in patients with an intermediate score (1.3–3.25) and referral to a hepatologist in those with a FIB-4 score >3.25 or ELF >9.5 (19). They found that, compared with the standard of care before this pathway introduction, the number of unnecessary referrals dropped by 88%. In a cost-comparison analysis, Srivastava et al compared five different scenarios of referral by primary care physicians. In scenario 1, a referral would be made on the basis of clinical judgement and routine blood tests; in scenario 2, all patients would have a FIB-4, followed by ELF for those with indeterminate results; in scenario 3, FIB-4 would be followed by a FibroScan; in scenario 4, ELF alone would be performed; and in scenario 5, FibroScan only would be done. The cost per case of advanced fibrosis (METAVIR ≥F3) was £24,543, £8,932, £9,083, £9,487, and £10,351 for scenarios 1–5, respectively. Their conclusion was that non-invasive liver testing in primary care can reduce unnecessary referrals and is cost-efficient (20). The results of our study suggest that the easily accessible FIB-4 and NFS testing can be used to decide whether patients can avoid a referral for TE. Using these tests, 70%–80% of referrals could have been avoided. This finding can have a significant impact on health care costs, as well as on travel time and expenses for patients. The proportion of patients with significant fibrosis that could have been missed was low (between 5.9% and 8.4%), but not negligible. However, we found that by taking into account a history of impaired glucose intolerance, we could reduce the proportion of cases missed to 3.4%.
The strength of our study is its sample size and the fact that all patients were from the same centre, which results in more standardized TE scores and measurements. Another strength is that our patient population had been screened for other concomitant liver diseases and excluded if there was any evidence of such. Moreover, we included only patients with at least one risk factor for NAFLD. As such, there is a high likelihood that our patients all truly had NAFLD as the underlying etiology of their liver disease.
A potential limitation of this study is that the parameters used in the NFS and FIB-4 were not necessarily obtained at the same time as the TE. We allowed for up to a 3-month difference in timing from when individual results were obtained, which therefore introduces the possibility of a misclassification. However, given that fibrosis in the context of NAFLD is typically a gradual process, this is unlikely to create a significant difference. Another limitation is that only a small minority of patients had liver biopsies performed. Therefore, NFS and FIB-4 scores were compared only with TE results, which can introduce bias from use of inappropriate reference standard. Our conclusions would have been strengthened if they had been supported by biopsy-proven fibrosis.
Our study supports the use of NFS and FIB-4 as effective screening tools that can be used in the primary care and community settings. These findings will, we hope, help to reduce the number of patients needing evaluation by TE or liver biopsies. Given the wide geographical distribution of the Canadian population and the fact that TE and liver biopsy are largely restricted to urban centres, we expect that the application of NFS and FIB-4 could significantly reduce the need for patient travel. This, combined with the fact that prevalence of NAFLD is continually increasing, means that these inexpensive screening tools could lead to major cost savings for the health care system if applied appropriately.
Conclusion
NFS and FIB-4 are inexpensive and readily available non-invasive scoring systems that can help to rule out fibrosis among patients with NAFLD and can be used in select patients to circumvent the need for TE or liver biopsy.
Ethics Approval:
The study was conducted at the Vancouver General Hospital hepatology clinic and was approved by the University of British Columbia Research Ethics Board.
Informed Consent:
Informed consent was obtained from the patients.
Registry and Registration No. of the Study/Trial:
N/A
Funding:
No funding was received for this article.
Disclosures:
The authors have nothing to disclose.
Peer Review:
This article has been peer reviewed.
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