Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Predictors of advanced fibrosis in elderly patients with biopsy-confirmed nonalcoholic fatty liver disease: the GOASIA study

BMC Gastroenterology volume 20, Article number: 88 (2020) Cite this article

Abstract

Background

The Gut and Obesity in Asia (GOASIA) Workgroup was formed to study obesity and gastrointestinal diseases in the Asia Pacific region. We aimed to 1) compare the characteristics of elderly (i.e. age ≥ 60) vs. non-elderly patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD); 2) identify predictors of advanced fibrosis in elderly patients with NAFLD; and 3) assess the performance of non-invasive fibrosis scores in the prediction of advance fibrosis in the elderly population.

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 < 0.001). By multivariable analysis, factors associated with advanced fibrosis in elderly patients included female sex [odds ratio (OR) 3.21; 95% confidence interval (CI) 1.37–7.54] and hypertension (OR 3.68; 95%CI 1.11–12.23). The area under receiver-operating characteristics curve (95% CI) of aspartate aminotransferase-to-platelet ratio index, NAFLD fibrosis score and Fibrosis-4 index for predicting advanced fibrosis in elderly patients were 0.62 (0.52–0.72), 0.65 (0.55–0.75) and 0.64 (0.54–0.74) respectively.

Conclusions

Elderly patients with NAFLD had a higher prevalence of advanced fibrosis than non-elderly patients. Female and hypertension were predicting factors for advanced fibrosis in the elderly. Non-invasive fibrosis scores had a lower specificity in elderly.

Peer Review reports

Background

Nowadays, nonalcoholic fatty liver disease (NAFLD) is a growing problem and is becoming a major cause of chronic liver disease worldwide. NAFLD broadly encompasses two conditions with different prognosis: nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH). The prevalence of NASH has consistently been reported to increase with age besides being associated with obesity, diabetes mellitus and the metabolic syndrome [1,2,3]. Due to population aging, NAFLD is projected to increase globally.

Recently, Ballestri and colleagues conducted a comprehensive review of NAFLD studies and found age, sex and the metabolic syndrome to be major factors influencing NAFLD onset and progression. The incidence of NAFLD is higher in men [4, 5]. In men, the prevalence of NAFLD increases during young adulthood to middle age and decline after the age of 50–60 years [6, 7]. In contrast, NAFLD is more common among elderly women with metabolic comorbidities [8]. In premenopausal women, the incidence of NAFLD is low but increases rapidly after menopause [9, 10]. The striking gender difference has long been reported in NAFLD.

The global prevalence of NAFLD is about 25% [11], while in Asia the disease has been reported to affect up to 30% of the general population in some studies [12,13,14]. However, data in the elderly population are limited. Currently, the proportion of older population is growing dramatically due to increased life expectancy and declining birth rates. Accordingly, the number of NAFLD patients would also inevitably increase. Predicting advanced fibrosis is necessary because of the higher risk of complications from chronic liver disease such as cirrhosis and hepatocellular carcinoma. In order to evaluate the liver disease severity, liver biopsy is gold standard. However, it is an invasive procedure and may be limited by sampling variability. So far there is no specific recommendation for elderly NAFLD in terms of diagnostic and fibrosis assessment [15, 16]. Previous studies have shown that non-invasive fibrosis scores, including fibrosis-4 (FIB-4) and NAFLD fibrosis score (NFS) have low specificity in elderly NAFLD patients [17].

The Gut and Obesity in Asia (GO ASIA) Workgroup was formed in November 2014 with the aim of studying relationship between obesity and gastrointestinal and liver diseases in the Asia Pacific region through multi-national collaborative studies [18, 19]. A database consisting of biopsy-proven NAFLD patients was formed through contribution from participating members of the GO ASIA Workgroup. We aimed to investigate factors associated with liver fibrosis in elderly (i.e. age ≥ 60) vs. non-elderly patients with biopsy-proven NAFLD, and to identify predictors of advanced fibrosis in elderly patients. In addition, we evaluated the performance of non-invasive fibrosis scores in elderly NAFLD patients.

Methods

Participating centers and cases

This is a cross-sectional study of 1008 patients with biopsy-proven NAFLD in nine centers across eight countries in the GO ASIA Workgroup [19]. The centers that participated in this study and the duration of data collection were listed as follows: The Chinese University of Hong Kong, Hong Kong collected data from September 2006 to October 2015; University of Malaya, Malaysia collected data from November 2012 to October 2015; Chulalongkorn University, Thailand collected data from January 2007 to February 2014; Yotsuya Medical Cube / Gunma University Graduate School of Medicine, and Yokohama City University Graduate School of Medicine, Japan collected data from October 2009 to February 2016; Shanghai Jiaotong University School of Medicine, China collected data from June 2012 to December 2013; The Catholic University of Korea, Korea collected data from January 2009 to February 2016; National University of Singapore, Singapore collected data from October 2002 to October 2015; and Digestive Disease and Oncology GI Centre, Medistra Hospital, Indonesia collected data from May 2011 to September 2015. Ethical approval was obtained from each center prior to the commencement of the study. Verbal informed consent was obtained from all patients for being included in the study and the institutional review board approved the use of verbal consent.

NAFLD was diagnosed based on ultrasonography findings of fatty liver with exclusion of viral hepatitis B and C infection, significant alcohol intake, and the use of medications that can cause hepatic steatosis. Persistent elevated serum aminotransferase levels were the main indication for liver biopsy. Patients with other causes of chronic liver disease, incomplete histological data and without significant hepatic steatosis were excluded from the analyses. Demographic, anthropometric, clinical and laboratory data were collected using a standard protocol.

Definitions

Elderly patients were defined as age ≥ 60 years. Obesity was defined as body mass index (BMI) ≥ 25.0 kg/m2 [20]. Central obesity was defined as waist circumference (WC) > 90 cm for men and > 80 cm for women [21]. A patient was considered to have diabetes mellitus if there was a self-reported history of diabetes mellitus, or if fasting blood sugar was ≥ 7.0 mmol/L. A patient was considered to have dyslipidemia if there was a self-reported history of dyslipidemia, if the serum total cholesterol (TC) was ≥ 5.2 mmol/L, if the serum triglyceride (TG) was ≥ 1.7 mmol/L, if the serum high-density lipoprotein (HDL) was < 1.0 mmol/L for men or < 1.3 mmol/L for women, or if the serum low-density lipoprotein (LDL) was ≥ 3.4 mmol/L. All laboratory parameters included in the study were within 3 months before or after liver biopsy obtained. Hypertension was based on self-reported history. If they were using any drugs as evidence of the corresponding metabolic disorders also considered as having diabetes mellitus, dyslipidemia or hypertension.

Non-invasive assessment of advanced fibrosis in patients with NAFLD

The performance of the NAFLD fibrosis score (NFS), fibrosis 4 (FIB-4) score, and aspartate aminotransferase (AST) to platelet ratio index (APRI) in prediction of advanced fibrosis in the elderly and non-elderly NAFLD patients were assessed.

Histological data

Histopathological findings were reported according to the Non-Alcoholic Steatohepatitis Clinical Research Network Scoring System [22]. NAFLD Activity Score (NAS) was defined as the un-weighted sum of the scores for steatosis which was the presence of significant hepatic steatosis (> 5% of hepatocytes) (0–3), lobular inflammation (0–3), and ballooning (0–2); thus ranging from 0 to 8. NASH was defined as steatosis with hepatocyte ballooning and inflammation with/without fibrosis [23].

The slides were review by pathologist in each center. Fibrosis stages 3 and 4 were considered as advanced fibrosis (F3–4).

Statistical analysis

We performed 1:3 matching by sex for elderly and non-elderly NAFLD patients. Continuous variables were reported as mean, standard deviation and analyzed using t-test. For non-normal distribution data were reported as median, interquartile range and analyzed using Mann-Whitney U test. Categorical variables were reported as percentages and analyzed using chi-square test. Factors associated with advanced fibrosis in elderly group were identified using binary logistic regression analysis. Multivariable analysis was performed by including all variables that had p-values < 0.1 from univariable analysis. Area under receiver-operating characteristics curve (AUROC) and its 95% confidence intervals were generated to determine performance of fibrosis prediction scores. A two-tailed P-value < 0.05 was considered statistically significant. Analyses were performed using SPSS 22.0 (SPSS Inc., Chicago, Illinois, U.S.).

Results

Characteristics of elderly and non-elderly NAFLD patients

Of 1008 patients with biopsy-proven NAFLD, 175 patients were elderly, who were matched with 525 non-elderly patients. The percentages of elderly NAFLD patients from each country included in the study are shown in supplemental table 1. The median (IQR) age of elderly NAFLD and non-elderly NAFLD patients were 64 (62–67) and 46 (36–54) years. In the elderly group, 102 (58.3%) patients were female. Characteristics of elderly and non-elderly NAFLD patients in different centers are shown in supplemental table 2.

The elderly NAFLD patients were more likely to have diabetes mellitus, hypertension and dyslipidemia than non-elderly patients. Elderly NAFLD patients had significantly lower BMI [27.19 (24.73–30.34) vs 29.62 (26.45–35) kg/m2, p < 0.001] and hip circumference [97 (87.75–104) vs 100 (88–108) cm, p = 0.037]. Elderly NAFLD patients had lower alanine aminotransferase [55 (38–94) vs 61 (37–90) U/L, p = 0.002], platelet count [227.5 (177.5–280.75) vs 251 (202–297) × 109/L, p < 0.001], white blood count [6.57 (5.6–8) vs 7.3 (5.9–8.8) × 103/mm3, p = 0.015], total cholesterol [4.4 (3.5–5.33) vs 5 (4.3–5.7) mmol/L, p < 0.001] and LDL cholesterol [2.3 (1.79–3.25) vs 3 (2.43–3.7) mmol/L, p < 0.001] than non-elderly NAFLD patients. Elderly patients had significantly higher hemoglobin A1c than non-elderly patients [6.65 (5.9–7.33) vs 6.1 (5.6–7.2) %, p < 0.001] (Table 1).

Table 1 Characteristics of elderly and non-elderly NAFLD patients were compared using1:3 sex-matched analysis
Full size table

For the pathology findings, NASH was not difference between elderly and non-elderly NAFLD patients (67.4% vs.63.8%, p = 0.386). Elderly NAFLD patients were more likely to have advanced fibrosis (F3–4; 35.4% vs. 13.3%, p < 0.001) and cirrhosis (15.4% vs. 4.8%, p < 0.001) than non-elderly NAFLD patients (Fig. 1). Elderly patients also had higher fibrosis scores: APRI (1.18 ± 2.02 vs. 0.74 ± 1.55, p = 0.02), NFS (− 0.75 ± 1.49 vs. -1.91 ± 1.88, p < 0.001), and FIB-4 index (3.88 ± 6.72 vs. 1.58 ± 3.935, p < 0.001) (Table 1).

Fig. 1
figure 1

The percentages of fibrosis stages compared between elderly and non-elderly NAFLD patients: elderly NAFLD patients had significantly more patients with advanced fibrosis (F3–4; 35.4% vs. 13.4%; P < 0.01)

Full size image

Characteristics of elderly NAFLD patients with and without advanced fibrosis

Focusing on the elderly NAFLD patients, over one-third of them had advanced fibrosis (35.4%) including stage 3 fibrosis (F3; 20%) and stage 4 fibrosis (F4; 15.4%). Elderly NAFLD patients with advanced fibrosis were more likely to be female (72.6% vs. 50.4%; p = 0.005), obesity (83.9% vs 65.5%; p = 0.01), central obesity (94.7% vs. 79.1%; p = 0.009), diabetes (79% vs 64.6%; p = 0.047) and hypertension (88.3% vs. 67%; p = 0.002) (Table 2).

Table 2 Characteristics of elderly groups with advanced fibrosis (F3–4) vs. non-advanced fibrosis (F0–2)
Full size table

By univariate analysis, female sex, obesity, central obesity, diabetes and hypertension were associated with advanced fibrosis among the elderly NAFLD patients. By multivariable analysis, factors associated with advanced fibrosis in elderly patients included female sex (OR 3.21; 95%CI 1.37–7.54) and hypertension (OR 3.68; 95%CI 1.11–12.23). In contrast, diabetes (OR 3.38; 95%CI 1.70–6.73) and platelet count less than 140 × 109/L (OR 4.18; 95%CI 1.32–13.25) were factors associated with advanced fibrosis in non-elderly patients (Table 3).

Table 3 Univariate analysis and multivariate analysis for predictors of advanced fibrosis in the elderly and non-elderly patients with NAFLD
Full size table

The performance of non-invasive fibrosis scores in elderly NAFLD patients

Box plot of non-invasive fibrosis scores in each liver biopsy-proven fibrosis stage is shown in Fig. 2.The AUROCs of APRI, NFS and FIB-4 to predict advanced fibrosis in the elderly NAFLD patients were as follows: 0.62 (0.52–0.72) p = 0.03, 0.65 (0.55–0.75) p = 0.01, and 0.64 (0.54–0.74) p = 0.01, respectively (Table 4). Comparison of the AUROCs among APRI, NFS, and FIB-4 showed no significant difference within elderly NAFLD patients (APRI vs NFS, p = 0.551, APRI vs FIB-4, p = 0.308 and NFS vs FIB-4, p = 0.828). The flow diagram evaluating the performance of non-invasive fibrosis scores in elderly NAFLD patients is shown in supplemental fig. 1. Comparison between percentage of advanced fibrosis in elderly NAFLD patients and non-elderly NAFLD patients from each non-invasive fibrosis score is shown in supplemental table 3. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of APRI, NFS and FIB-4 in both elderly and non-elderly NAFLD are shown in supplemental table 4.

Fig. 2
figure 2

Box plot of non-invasive fibrosis scores in each liver biopsy-proven fibrosis stage

Full size image
Table 4 The performance of AST to Platelet Ratio Index (APRI), NAFLD fibrosis score (NFS) and fibrosis 4 (FIB-4) in prediction of advanced fibrosis in elderly NAFLD patients and non-elderly NAFLD patients
Full size table

Discussion

This multicenter study on 700 biopsy-proven NAFLD patients revealed that a significant proportion of elderly patients had advanced fibrosis (35.4%). Liver is an organ with age and sex-related changes [24], and the complications from chronic liver disease increase with age, contributing significantly to health care burden. Besides, we demonstrated that the non-invasive scores were higher in elderly NAFLD patients than non-elderly patients. To better understand how to hinder disease progression, reliable baseline data are needed to identify predictors for early intervention and close monitoring. In this study, we found that elderly NAFLD patients with advanced fibrosis were more likely to be female and were more likely to have hypertension.

An earlier study from Noureddin et al. compared between elderly and non-elderly patients with NAFLD showed the predominance of NAFLD in elderly female patients. Their elderly NAFLD patients were more likely to be hypertensive, had lower mean BMI and smaller waist circumference. Moreover, They had a higher mean AST/ALT ratio, lower mean platelet count, and higher mean APRI score that were suggested as indices of more advanced liver disease [3]. Similar to the previous study, our elderly NAFLD patients had lesser mean BMI and hip circumference. This group of patients was more likely to have hypertension, diabetes mellitus, and dyslipidemia. It is worth noting that we must be aware that the elderly group may have NAFLD even if they have low BMI.

To identify patients who have advanced fibrosis, liver biopsy is the gold standard, but this procedure has some limitations due to its invasive nature and the potential complications. Non-invasive fibrosis scores, for example, APRI, NFS and FIB-4 score were developed to predict liver fibrosis. However, the validation of these scores were included only in the minority of elderly group [25] or some studies did not include any subjects with ages ≥65 years [26, 27]. Meta-analysis in 2016, most of patients aged less than 60, showed FIB-4 score had better diagnostic accuracy than NFS and BARD score. In non-elderly NAFLD, our study also supported that FIB-4 had better diagnostic accuracy than NFS and APRI [28].

Recently, McPherson et al. reported that the NAFLD fibrosis score and FIB-4 had low specificity for advanced fibrosis in patients aged ≥65 years leading to a high false positive rate. New cutoffs have been proposed to improve the accuracy of the NFS and FIB-4 score in patients ages ≥65 years [17]. From our data, we found that the NFS and FIB-4 had a lower specificity when using lower cutoffs. When validating by using the new cutoffs by McPherson et al., specificity was increased in elderly, however, sensitivity was low (supplemental table 5).

Aging promotes metabolic disturbances causing an increase in lipid accumulation in non-adipose tissues, including the liver. With reduced physical activity in aging, insulin resistance and hyperinsulinemia promote obesity and the onset of the metabolic syndrome. NASH is considered to be a manifestation of metabolic syndrome [29, 30]. In the present study, the prevalence of advanced liver fibrosis was high in elderly patients, particularly in women with central obesity. The gender difference of the metabolic disturbance is most evident in postmenopausal women. Although the mechanisms of menopause-induced metabolic dysfunction are largely unknown, estrogen depletion is thought to responsible for the underlying pathological mechanism [31]. This observation requires further study to confirm.

The strength of this study includes the use of a well-characterized cohort of biopsy-proven NAFLD patients from multiple centers in Asia. The proportion of elderly patients in the present study is greater than those reported in previous studies [3, 4]. One of the limitations may arise from the liver biopsy results and its assessment which was reported by the local pathologists of each center and they were not reviewed centrally by a panel of pathologists. However, interobserver agreement for advanced fibrosis tends to be better, and our study focused on advanced fibrosis. Secondly, the sampling errors of liver biopsy and observer variability may affect the pathological results interpretation [22]. Lastly, the study could be affected by selection bias as the sample came from tertiary centers and specialist liver clinics, thus the findings may not be applicable to general clinic setting.

Conclusions

Elderly patients with NAFLD had a higher prevalence of advanced fibrosis than non-elderly patients. Female sex and hypertension were predictive factors for the presence of advanced fibrosis in elderly. We should be aware of this in our aging society. Performance of fibrosis prediction by using non-invasive scoring system including APRI, NFS and FIB-4 were not good enough to predict the presence of advanced fibrosis stage in the elderly.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

APRI:

Aspartate aminotransferase-to-platelet ratio index

AUROC:

Area under receiver-operating characteristics curve

FIB-4:

Fibrosis 4 score

NAFLD:

Nonalcoholic fatty liver disease

NAS:

NAFLD activity score

NFS:

NAFLD fibrosis score

NPV:

Negative predictive value

PPV:

Positive predictive value

References

  1. Benedict M, Zhang X. Non-alcoholic fatty liver disease: an expanded review. World J Hepatol. 2017;9(16):715–32.

    Article  Google Scholar 

  2. Sayiner M, Koenig A, Henry L, Younossi ZM. Epidemiology of nonalcoholic fatty liver disease and nonalcoholic Steatohepatitis in the United States and the rest of the world. Clin Liver Dis. 2016;20(2):205–14.

    Article  Google Scholar 

  3. Noureddin M, Yates KP, Vaughn IA, Neuschwander-Tetri BA, Sanyal AJ, McCullough A, et al. Clinical and histological determinants of nonalcoholic steatohepatitis and advanced fibrosis in elderly patients. Hepatology. 2013;58(5):1644–54.

    Article  CAS  Google Scholar 

  4. Ballestri S, Nascimbeni F, Baldelli E, Marrazzo A, Romagnoli D, Lonardo A. NAFLD as a sexual dimorphic disease: role of gender and reproductive status in the development and progression of nonalcoholic fatty liver disease and inherent cardiovascular risk. Adv Ther. 2017;34(6):1291–326.

    Article  Google Scholar 

  5. Xu C, Yu C, Ma H, Xu L, Miao M, Li Y. Prevalence and risk factors for the development of nonalcoholic fatty liver disease in a nonobese Chinese population: the Zhejiang Zhenhai study. Am J Gastroenterol. 2013;108(8):1299–304.

    Article  Google Scholar 

  6. Eguchi Y, Hyogo H, Ono M, Mizuta T, Ono N, Fujimoto K, et al. Prevalence and associated metabolic factors of nonalcoholic fatty liver disease in the general population from 2009 to 2010 in Japan: a multicenter large retrospective study. J Gastroenterol. 2012;47(5):586–95.

    Article  CAS  Google Scholar 

  7. Kojima S, Watanabe N, Numata M, Ogawa T, Matsuzaki S. Increase in the prevalence of fatty liver in Japan over the past 12 years: analysis of clinical background. J Gastroenterol. 2003;38(10):954–61.

    Article  Google Scholar 

  8. Ludwig J, Viggiano TR, McGill DB, Oh BJ. Nonalcoholic steatohepatitis: Mayo Clinic experiences with a hitherto unnamed disease. Mayo Clin Proc. 1980;55(7):434–8.

    CAS  PubMed  Google Scholar 

  9. Florentino GS, Cotrim HP, Vilar CP, Florentino AV, Guimaraes GM, Barreto VS. Nonalcoholic fatty liver disease in menopausal women. Arq Gastroenterol. 2013;50(3):180–5.

    Article  Google Scholar 

  10. Hamaguchi M, Takeda N, Kojima T, Ohbora A, Kato T, Sarui H, et al. Identification of individuals with non-alcoholic fatty liver disease by the diagnostic criteria for the metabolic syndrome. World J Gastroenterol. 2012;18(13):1508–16.

    Article  CAS  Google Scholar 

  11. Bertolotti M, Lonardo A, Mussi C, Baldelli E, Pellegrini E, Ballestri S, et al. Nonalcoholic fatty liver disease and aging: epidemiology to management. World J Gastroenterol. 2014;20(39):14185–204.

    Article  Google Scholar 

  12. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64(1):73–84.

    Article  Google Scholar 

  13. Fan JG, Kim SU, Wong VW. New trends on obesity and NAFLD in Asia. J Hepatol. 2017;67(4):862–73.

    Article  Google Scholar 

  14. Chitturi S, Wong VW, Farrell G. Nonalcoholic fatty liver in Asia: firmly entrenched and rapidly gaining ground. J Gastroenterol Hepatol. 2011;26(Suppl 1):163–72.

    Article  Google Scholar 

  15. Nascimbeni F, Pais R, Bellentani S, Day CP, Ratziu V, Loria P, et al. From NAFLD in clinical practice to answers from guidelines. J Hepatol. 2013;59(4):859–71.

    Article  Google Scholar 

  16. Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018;67(1):328–57.

    Article  Google Scholar 

  17. McPherson S, Hardy T, Dufour JF, Petta S, Romero-Gomez M, Allison M, et al. Age as a confounding factor for the accurate non-invasive diagnosis of advanced NAFLD fibrosis. Am J Gastroenterol. 2017;112(5):740–51.

    Article  Google Scholar 

  18. Koh JC, Loo WM, Goh KL, Sugano K, Chan WK, Chiu WY, et al. Asian consensus on the relationship between obesity and gastrointestinal and liver diseases. J Gastroenterol Hepatol. 2016;31(8):1405–13.

    Article  Google Scholar 

  19. Chan WK, Treeprasertsuk S, Imajo K, Nakajima A, Seki Y, Kasama K, et al. Clinical features and treatment of nonalcoholic fatty liver disease across the Asia Pacific region-the GO ASIA initiative. Aliment Pharmacol Ther. 2018;47(6):816–25.

    Article  CAS  Google Scholar 

  20. Anuurad E, Shiwaku K, Nogi A, Kitajima K, Enkhmaa B, Shimono K, et al. The new BMI criteria for asians by the regional office for the western pacific region of WHO are suitable for screening of overweight to prevent metabolic syndrome in elder Japanese workers. J Occup Health. 2003;45(6):335–43.

    Article  Google Scholar 

  21. Alberti KG, Zimmet P, Shaw J, Group IDFETFC. The metabolic syndrome--a new worldwide definition. Lancet. 2005;366(9491):1059–62.

    Article  Google Scholar 

  22. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313–21.

    Article  Google Scholar 

  23. Yeh MM, Brunt EM. Pathological features of fatty liver disease. Gastroenterology. 2014;147(4):754–64.

    Article  CAS  Google Scholar 

  24. Cvitanovic Tomas T, Moskon M, Mraz M, Rozman D. Computational Modelling of liver metabolism and its applications in research and the clinics. Acta Chim Slov. 2018;65(2):253–65.

    Article  Google Scholar 

  25. Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology. 2007;45(4):846–54.

    Article  CAS  Google Scholar 

  26. Kruger FC, Daniels CR, Kidd M, Swart G, Brundyn K, van Rensburg C, et al. APRI: a simple bedside marker for advanced fibrosis that can avoid liver biopsy in patients with NAFLD/NASH. S Afr Med J. 2011;101(7):477–80.

    CAS  PubMed  Google Scholar 

  27. Shah AG, Lydecker A, Murray K, Tetri BN, Contos MJ, Sanyal AJ, et al. Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2009;7(10):1104–12.

    Article  CAS  Google Scholar 

  28. Sun W, Cui H, Li N, Wei Y, Lai S, Yang Y, et al. Comparison of FIB-4 index, NAFLD fibrosis score and BARD score for prediction of advanced fibrosis in adult patients with non-alcoholic fatty liver disease: a meta-analysis study. Hepatol Res. 2016;46(9):862–70.

    Article  CAS  Google Scholar 

  29. Amarapurkar D, Kamani P, Patel N, Gupte P, Kumar P, Agal S, et al. Prevalence of non-alcoholic fatty liver disease: population based study. Ann Hepatol. 2007;6(3):161–3.

    Article  Google Scholar 

  30. Park SH, Jeon WK, Kim SH, Kim HJ, Park DI, Cho YK, et al. Prevalence and risk factors of non-alcoholic fatty liver disease among Korean adults. J Gastroenterol Hepatol. 2006;21(1 Pt 1):138–43.

    Article  Google Scholar 

  31. Quinn MA, Xu X, Ronfani M, Cidlowski JA. Estrogen deficiency promotes hepatic Steatosis via a glucocorticoid receptor-dependent mechanism in mice. Cell Rep. 2018;22(10):2690–701.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We would like to thank the supporting team of the Gut and Obesity in Asia (GOASIA) Workgroup for database. Additionally, we would like to thank the GI research coordinator and statistician, GI Division, King Chulalongkorn Memorial hospital, Miss Kanokwan Sornsiri and Miss Chonlada Phathong.

Funding

The grant support organization including the Liver Research Unit of the Faculty of Medicine, Chulalongkorn University, as well as the funding from Fatty Liver Research Unit, Division of Gastroenterology, Chulalongkorn University. The funders had no role in study design, decision to publish and preparation of the manuscript.

Author information

Authors and Affiliations

  1. Department of Medicine, Chulalongkorn University, Bangkok, Thailand

    Panyavee Pitisuttithum, Panida Piyachaturawat & Sombat Treeprasertsuk

  2. Department of Medicine, University of Malaya, Kuala Lumpur, Malaysia

    Wah Kheong Chan & Khean Lee Goh

  3. Department of Gastroenterology and Hepatology, Yokohama City University Graduate School of Medicine, Yokohama, Japan

    Kento Imajo & Atsushi Nakajima

  4. Weight Loss and Metabolic Surgery Centre, Yotsuya Medical Cube, Tokyo, Japan

    Yosuke Seki & Kazunori Kasama

  5. Department of Gastroenterology and Hepatology, Gunma University Graduate School of Medicine, Gunma, Japan

    Satoru Kakizaki

  6. Department of Gastroenterology, Shanghai Jiaotong University School of Medicine, Shanghai, China

    Jian Gao Fan

  7. Department of Internal Medicine, The Catholic University of Korea, Seoul, Korea

    Myeong Jun Song & Seung Kew Yoon

  8. Department of Medicine, National University of Singapore, Singapore, Singapore

    Yock Young Dan & Khek Yu Ho

  9. Digestive Disease and Oncology GI Centre, Medistra Hospital, Jakarta, Indonesia

    Laurentius Lesmana

  10. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China

    Vincent Wai Sun Wong

Authors
  1. Panyavee Pitisuttithum
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wah Kheong Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Panida Piyachaturawat
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kento Imajo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Atsushi Nakajima
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yosuke Seki
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kazunori Kasama
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Satoru Kakizaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jian Gao Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Myeong Jun Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Seung Kew Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yock Young Dan
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Laurentius Lesmana
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Khek Yu Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Khean Lee Goh
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Vincent Wai Sun Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Sombat Treeprasertsuk
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ST and PP1 designed the study. PP1, WC, PP2, KI, AN, YS, KK, SK, JF, MS, SY, YD, LL, KH, KG, VW, ST contributed to data acquisition. ST and PP1 analyzed and interpreted the data. PP1, PP2 and ST drafted the manuscript. ST, WC and VW revised the manuscript critically for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sombat Treeprasertsuk.

Ethics declarations

Ethics approval and consent to participate

Ethics approval was obtained from each center prior to the commencement of the study. The Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee, China; Medical Ethics Committee of University Malaya Medical Center, Malaysia; the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Thailand; the Institutional Review Boards of Yotsuya Medical Cube and Gunma University, Japan; the Ethics Committee of Yokohama City University, Japan; Ethics Committees of Xinhua Hospital affiliated with the Shanghai Jiao Tong University School of Medicine, China; the Ethics Review Board of the Catholic University of Korea, Korea; the National Healthcare Group Domain Specific Review, Singapore; the Medistra hospital’s local ethics committee, Indonesia approved this study. This study was conducted in accordance with the Declaration of Helsinki. As retrospective study, our center recommended to use verbal consent, verbal informed consent was obtained from all patients for being included in the study and the institutional review board approved the use of verbal consent.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Part of the information has been submitted to the Digestive Disease Week® 2017, held on May 6 - 9, 2017 at McCormick Place - Chicago, Illinois, United States of America.

Supplementary information

Additional file 1: Supplemental fig. 1.

The flow diagram evaluating the performance of non-invasive fibrosis scores in elderly and non-elderly NAFLD patients. Supplemental table 1. The percentages of elderly NAFLD patients (n = 175) and non-elderly NAFLD patients from each country included in the study (total = 1008). Supplemental table 2. Characteristics of elderly and non-elderly NAFLD patients in different centers. Supplemental table 3. Comparison between percentages of advanced fibrosis in elderly and non-elderly NAFLD patients. Supplemental table 4. Thesensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of APRI, NFS and FIB-4 in both elderly and non-elderly NAFLD patients. Supplemental table 5. AUROC, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of APRI, NFS and FIB-4 in elderly NAFLD patients when elderly defined as ≥ 65 according to McPherson et al.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pitisuttithum, P., Chan, W.K., Piyachaturawat, P. et al. Predictors of advanced fibrosis in elderly patients with biopsy-confirmed nonalcoholic fatty liver disease: the GOASIA study. BMC Gastroenterol 20, 88 (2020). https://0-doi-org.brum.beds.ac.uk/10.1186/s12876-020-01240-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12876-020-01240-z

Keywords

BMC Gastroenterology

ISSN: 1471-230X

Contact us