DESIGN: We prospectively recruited 496 patients with non-alcoholic fatty liver disease who underwent VCTE by both M and XL probes within 1 week before liver biopsy.
RESULTS: 391 (78.8%) and 433 (87.3%) patients had reliable liver stiffness measurement (LSM) (10 successful acquisitions and IQR:median ratio ≤0.30) by M and XL probes, respectively (p<0.001). The area under the receiver operating characteristic curves was similar between the two probes (0.75-0.88 for F2-4, 0.83-0.91 for F4). When used in the same patient, LSM by XL probe was lower than that by M probe (mean difference 2.3 kPa). In contrast, patients with BMI ≥30 kg/m2 had higher LSM regardless of the probe used. When M and XL probes were used in patients with BMI <30 and ≥30 kg/m2, respectively, they yielded nearly identical median LSM at each fibrosis stage and similar diagnostic performance. Severe steatosis did not increase LSM or the rate of false-positive diagnosis by XL probe.
CONCLUSION: High BMI but not severe steatosis increases LSM. The same LSM cut-offs can be used without further adjustment for steatosis when M and XL probes are used according to the appropriate BMI.
METHODS: Six hundred and thirty-six adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from two independent Asian cohorts were enrolled in our study. Liver stiffness measurement (LSM) was assessed by vibration-controlled transient elastography (Fibroscan). Fibrotic NASH was defined as NASH with a NAFLD activity score (NAS) ≥ 4 and F ≥ 2 fibrosis.
RESULTS: Metabolic syndrome (MetS), platelet count and MACK-3 were independent predictors of fibrotic NASH. On the basis of their regression coefficients, we developed a novel nomogram showing a good discriminatory ability (area under receiver operating characteristic curve [AUROC]: 0.79, 95% confidence interval [CI 0.75-0.83]) and a high negative predictive value (NPV: 94.7%) to rule out fibrotic NASH. In the validation set, this nomogram had a higher AUROC (0.81, 95%CI 0.74-0.87) than that of MACK-3 (AUROC: 0.75, 95%CI 0.68-0.82; P liver biopsy in 56.9% of patients.
CONCLUSIONS: Our novel nomogram (combining MACK-3, platelet count and MetS) shows promising utility for diagnosing fibrotic NASH. The sequential combination of this nomogram and vibration-controlled transient elastography limits indeterminate results and reduces the number of unnecessary liver biopsies.
METHODS AND RESULTS: A multidisciplinary panel of fifty-two international experts comprising Hepatologists, Endocrinologists, Diabetologists, Cardiologists and Family Physicians from six continents (Asia, Europe, North America, South America, Africa and Oceania) participated in a formal Delphi survey and developed consensus statements on the association between MAFLD and the risk of CVD. Statements were developed on different aspects of CVD risk, ranging from epidemiology to mechanisms, screening, and management.
CONCULSIONS: The expert panel identified important clinical associations between MAFLD and the risk of CVD that could serve to increase awareness of the adverse metabolic and cardiovascular outcomes of MAFLD. Finally, the expert panel also suggests potential areas for future research.
METHODS: We performed a retrospective analysis of data from 759 patients with biopsy-proven NAFLD (24% with advanced fibrosis), seen at 10 centers in 9 countries in Asia, from 2006 through 2018. By using liver biopsies as the reference standard, we calculated percentages of misclassifications and indeterminate or discordant results from assessments made based on fibrosis scores (NAFLD fibrosis score [NFS] or Fibrosis-4 score) and liver stiffness measurements (LSMs), alone or in combination. The analysis was repeated using randomly selected subgroups with a different prevalence of advanced fibrosis (histologic fibrosis stage ≥F3).
RESULTS: In groups in which 3.7% and 10% of patients had advanced fibrosis, a 2-step approach (using the NFS followed by LSM only for patients with indeterminate or high NFS) and using a gray zone of 10 to 15 kPa for LSM, produced indeterminate or discordant results for 6.9% of patients and misclassified 2.7% of patients; only 25.6% of patients required LSM. In the group in which 10% of patients had advanced fibrosis, the same approach produced indeterminate or discordant results for 7.9% of patients and misclassified 6.6% of patients; only 27.4% of patients required LSM. In groups in which 24% and 50% of patients had advanced fibrosis, using LSM ≥10 kPa alone for the diagnosis of advanced fibrosis had the highest accuracy and misclassified 18.1% and 18.3% of patients, respectively. These results were similar when the Fibrosis-4 score was used in place of NFS.
CONCLUSIONS: In a retrospective analysis, we found that a 2-step approach using fibrosis scores followed by LSM most accurately detects advanced fibrosis in populations with a low prevalence of advanced fibrosis. However, LSM ≥10 kPa identifies patients with advanced fibrosis with the highest level of accuracy in populations with a high prevalence of advanced fibrosis.
METHODS: This was a multicenter study of 489 patients with biopsy-proven NAFLD and 69 patients with NAFLD-related or cryptogenic HCC. Antihepatitis B core antibody (anti-HBc) was used to detect the previous HBV infection.
RESULTS: In the biopsy cohort, positive anti-HBc was associated with lower steatosis grade but higher fibrosis stage. 18.8% and 7.5% of patients with positive and negative anti-HBc had cirrhosis, respectively (P < 0.001). The association between anti-HBc and cirrhosis remained significant after adjusting for age and metabolic factors (adjusted odds ratio 2.232; 95% confidence interval, 1.202-4.147). At a mean follow-up of 6.2 years, patients with positive anti-HBc had a higher incidence of HCC or cirrhotic complications (6.5% vs 2.2%; P = 0.039). Among patients with NAFLD-related or cryptogenic HCC, 73.9% had positive anti-HBc. None of the patients had positive serum HBV DNA. By contrast, antihepatitis B surface antibody did not correlate with histological severity.
DISCUSSION: Positive anti-HBc is associated with cirrhosis and possibly HCC and cirrhotic complications in patients with NAFLD. Because a significant proportion of NAFLD-related HCC may develop in noncirrhotic patients, future studies should define the role of anti-HBc in selecting noncirrhotic patients with NAFLD for HCC surveillance.
AIM: To study factors associated with nonalcoholic steatohepatitis (NASH) and advanced fibrosis, and medical treatment of biopsy-proven nonalcoholic fatty liver disease (NAFLD) patients.
METHODS: Retrospective study of biopsy-proven NAFLD patients from centres in the GO ASIA Workgroup. Independent factors associated with NASH and with advanced fibrosis on binary logistic regression analyses in a training cohort were used for the development of their corresponding risk score, which were validated in a validation cohort.
RESULTS: We included 1008 patients from nine centres across eight countries (NASH 62.9%, advanced fibrosis 17.2%). Independent predictors of NASH were body mass index ≥30 kg/m2 , diabetes mellitus, dyslipidaemia, alanine aminotransferase ≥88 U/L and aspartate aminotransferase ≥38 U/L, constituting the Asia Pacific NASH risk score. A high score has a positive predictive value of 80%-83% for NASH. Independent predictors of advanced fibrosis were age ≥55 years, diabetes mellitus and platelet count <150 × 109 /L, constituting the Asia-Pacific NAFLD advanced fibrosis risk score. A low score has a negative predictive value of 95%-96% for advanced fibrosis. Only 1.7% of patients were referred for structured lifestyle program, 4.2% were on vitamin E, and 2.4% were on pioglitazone.
CONCLUSIONS: More severe liver disease can be suspected or ruled out based on factors identified in this study. Utilisation of structured lifestyle program, vitamin E and pioglitazone was limited despite this being a cohort of biopsy-proven NAFLD patients with majority of patients having NASH.
METHODS: Adult patients with chronic liver disease who had a liver biopsy and examination with both the M and XL probes were included. Previously defined optimal cut-offs for CAP using the M probe were used for the diagnosis of steatosis grades ≥S1, ≥S2, and S3 (248, 268, and 280 dB/m, respectively).
RESULTS: Data for 180 patients were analyzed (mean age 53.7 ± 10.8 years; central obesity 84.5%; non-alcoholic fatty liver disease 86.7%). The distribution of steatosis grades was S0, 9.4%; S1, 28.3%; S2, 43.9%, and S3, 18.3%. The sensitivity, specificity, positive predictive value, and negative predictive value of CAP using the M/XL probe for the diagnosis of steatosis grade ≥S1 was 93.9%/93.3%, 58.8%/58.8%, 95.6%/95.6%, and 50.0%/47.6%, respectively. These values were 94.6%/94.6%, 41.2%/44.1%, 72.6%/73.6%, and 82.4%/83.3%, respectively, for ≥S2, and 87.9%/87.9%, 27.2%/27.9%, 21.3%/21.5%, and 90.9%/91.1%, respectively, for S3.
CONCLUSION: The same cut-off values for CAP may be used for the M and XL probes for the diagnosis of hepatic steatosis grade.
METHODS: A review of the literature identified studies containing histology verified CAP data (M probe, vibration controlled transient elastography with FibroScan®) for grading of steatosis (S0-S3). Receiver operating characteristic analysis after correcting for center effects was used as well as mixed models to test the impact of covariates on CAP. The primary outcome was establishing CAP cut-offs for distinguishing steatosis grades.
RESULTS: Data from 19/21 eligible papers were provided, comprising 3830/3968 (97%) of patients. Considering data overlap and exclusion criteria, 2735 patients were included in the final analysis (37% hepatitis B, 36% hepatitis C, 20% NAFLD/NASH, 7% other). Steatosis distribution was 51%/27%/16%/6% for S0/S1/S2/S3. CAP values in dB/m (95% CI) were influenced by several covariates with an estimated shift of 10 (4.5-17) for NAFLD/NASH patients, 10 (3.5-16) for diabetics and 4.4 (3.8-5.0) per BMI unit. Areas under the curves were 0.823 (0.809-0.837) and 0.865 (0.850-0.880) respectively. Optimal cut-offs were 248 (237-261) and 268 (257-284) for those above S0 and S1 respectively.
CONCLUSIONS: CAP provides a standardized non-invasive measure of hepatic steatosis. Prevalence, etiology, diabetes, and BMI deserve consideration when interpreting CAP. Longitudinal data are needed to demonstrate how CAP relates to clinical outcomes.
LAY SUMMARY: There is an increase in fatty liver for patients with chronic liver disease, linked to the epidemic of the obesity. Invasive liver biopsies are considered the best means of diagnosing fatty liver. The ultrasound based controlled attenuation parameter (CAP) can be used instead, but factors such as the underlying disease, BMI and diabetes must be taken into account. Registration: Prospero CRD42015027238.
AIM: To determine how to use CAP in interpreting liver stiffness measurements.
METHODS: This is a secondary analysis of data from an individual patient data meta-analysis on CAP. The main exclusion criteria for the current analysis were unknown aetiology, unreliable elastography measurement and data already used for the same research question. Aetiology-specific liver stiffness measurement cut-offs were determined and used to estimate positive and negative predictive values (PPV/NPV) with logistic regression as functions of CAP.
RESULTS: Two thousand and fifty eight patients fulfilled the inclusion criteria (37% women, 18% NAFLD/NASH, 42% HBV, 40% HCV, 51% significant fibrosis ≥ F2). Youden optimised cut-offs were only sufficient for ruling out cirrhosis (NPV of 98%). With sensitivity and specificity-optimised cut-offs, NPV for ruling out significant fibrosis was moderate (70%) and could be improved slightly through consideration of CAP. PPV for significant fibrosis and cirrhosis were 68% and 55% respectively, despite specificity-optimised cut-offs for cirrhosis.
CONCLUSIONS: Liver stiffness measurement values below aetiology-specific cut-offs are very useful for ruling out cirrhosis, and to a lesser extent for ruling out significant fibrosis. In the case of the latter, Controlled Attenuation Parameter can improve interpretation slightly. Even if cut-offs are very high, liver stiffness measurements are not very reliable for ruling in fibrosis or cirrhosis.
METHODS: We abstracted the data of 1008 patients with NAFLD from nine centers across eight countries. Characteristics of elderly and non-elderly patients with NAFLD were compared using 1:3 sex-matched analysis.
RESULTS: Of the 1008 patients, 175 were elderly [age 64 (62-67) years], who were matched with 525 non-elderly patients [46 (36-54) years]. Elderly patients were more likely to have advanced fibrosis (35.4% vs. 13.3%; p
AIM: To identify the association of baseline GGT level and QRISK2 score among patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD).
METHODS: This was a retrospective study involving 1535 biopsy-proven NAFLD patients from 10 Asian centers in 8 countries using data collected by the Gut and Obesity in Asia (referred to as "GO ASIA") workgroup. All patients with available baseline GGT levels and all 16 variables for the QRISK2 calculation (QRISK2-2017; developed by researchers at the United Kingdom National Health Service; https://qrisk.org/2017/; 10-year cardiovascular risk estimation) were included and compared to healthy controls with the same age, sex, and ethnicity. Relative risk was reported. QRISK2 score > 10% was defined as the high-CVD-risk group. Fibrosis stages 3 and 4 (F3 and F4) were considered advanced fibrosis.
RESULTS: A total of 1122 patients (73%) had complete data and were included in the final analysis; 314 (28%) had advanced fibrosis. The median age (interquartile range [IQR]) of the study population was 53 (44-60) years, 532 (47.4%) were females, and 492 (43.9%) were of Chinese ethnicity. The median 10-year CVD risk (IQR) was 5.9% (2.6-10.9), and the median relative risk of CVD over 10 years (IQR) was 1.65 (1.13-2.2) compared to healthy individuals with the same age, sex, and ethnicity. The high-CVD-risk group was significantly older than the low-risk group (median [IQR]: 63 [59-67] vs 49 [41-55] years; P < 0.001). Higher fibrosis stages in biopsy-proven NAFLD patients brought a significantly higher CVD risk (P < 0.001). Median GGT level was not different between the two groups (GGT [U/L]: Median [IQR], high risk 60 [37-113] vs low risk 66 [38-103], P = 0.56). There was no correlation between baseline GGT level and 10-year CVD risk based on the QRISK2 score (r = 0.02).
CONCLUSION: The CVD risk of NAFLD patients is higher than that of healthy individuals. Baseline GGT level cannot predict CVD risk in NAFLD patients. However, advanced fibrosis is a predictor of a high CVD risk.