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Histologic Scores for Fat and Fibrosis Associate With Development of Type 2 Diabetes in Patients With Nonalcoholic Fatty Liver Disease
Accepted Manuscript Histologic Scores for Fat and Fibrosis Associate With Development of Type 2 Diabetes in Patients With Non-alcoholic Fatty Liver Disease Karl Björkström, Per Stål, Rolf Hultcrantz, Hannes Hagström
PII: DOI: Reference:
S1542-3565(17)30534-7 10.1016/j.cgh.2017.04.040 YJCGH 55225
To appear in: Clinical Gastroenterology and Hepatology Accepted Date: 17 April 2017 Please cite this article as: Björkström K, Stål P, Hultcrantz R, Hagström H, Histologic Scores for Fat and Fibrosis Associate With Development of Type 2 Diabetes in Patients With Non-alcoholic Fatty Liver Disease, Clinical Gastroenterology and Hepatology (2017), doi: 10.1016/j.cgh.2017.04.040. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Title: Histologic Scores for Fat and Fibrosis Associate With Development of Type 2 Diabetes in Patients With Non-alcoholic Fatty Liver Disease
Short title: Diabetes development in NAFLD
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Authors: Karl Björkström1, Per Stål1,2, Rolf Hultcrantz1,2, Hannes Hagström1,2 Department of Medicine, Huddinge, Karolinska Institutet
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Centre for Digestive Diseases, Unit of Hepatology, Karolinska University Hospital
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Grant Support (Funding):
HH was supported by grants from the Stockholm County Council (ALF projects 20140329 and 20150403) and the Royal Swedish Academy of Sciences (Grant no ME2015-0011). Per Stål was supported by grants from Ruth and Richard Julins Foundation and the Swedish
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Society of Medicine (Gastroenterology Fund)
Independence (role of the sponsors): None of the grant providers had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and
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preparation, review, or approval of the manuscript.
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Abbreviations: ALT, alanine aminotransferase. AST, aspartate aminotransferase. BMI, body mass index. ɣGT, gamma glutamyltransferase. Hb, haemoglobin. HCC, hepatocellular carcinoma. HR, hazard ratio. NAFLD, non-alcoholic fatty liver disease. NASH, non-alcoholic steatohepatitis. NAS, NAFLD activity score. NFS, non-alcoholic fatty liver disease fibrosis score. SD, standard deviation. WBC, white blood cell count.
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ACCEPTED MANUSCRIPT Correspondence and reprint requests: Karl Björkström, Department of Medicine, Huddinge, Karolinska Institutet, 141 86 Stockholm, Sweden
E-mail: [email protected]
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Disclosure / Conflict of interest declaration: None
Study concept and design: HH
Statistical analysis: HH
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Acquisition of data: KB, HH, RH
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Writing Assistance: None. Author contributions:
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Phone: +46 (0) 73 703 41 67 Fax: +46 (0) 8 5858 2335
Interpretation of data: KB, PS, RH, HH
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Drafting of manuscript: KB, HH
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Critical revision: KB, PS, RH, HH Author statement:
Guarantor of article: Hannes Hagström All authors approved the final version of the article, including the authorship list. Total word count: 3274. Abstract: 246. Tables: 3. Figures: 3. Character count for title: 90
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ACCEPTED MANUSCRIPT Abstract: Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a strong risk factor for development of type 2 diabetes, but little is known about how long-term NAFLD or its histologic features affect risk. We aimed to investigate the cumulative incidence of type 2 diabetes in patients with NAFLD, and to identify histologic factors that affect risk of diabetes.
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Methods: We performed a retrospective study of 396 patients in Sweden diagnosed with NAFLD by biopsy analysis from 1971 through 2009 who did not have type 2 diabetes at baseline. Data on development of type 2 diabetes were collected from patient charts and national registers. Patients were categorized into groups with fibrosis stages 0–2 (n=357) or stages 3–4 (n=39). Hazard ratios of histologic parameters for type 2 diabetes development were calculated separately in a multivariate Cox regression model adjusted for sex, age, body mass index, and serum levels of triglycerides above 150 mg/dL.
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Results: During a mean follow-up period of 18.4 years (range 0–41 years), 132 individuals (33%) developed type 2 diabetes. A significantly higher proportion of patients with fibrosis stages 3–4 (51.2%) developed type 2 diabetes than patients with fibrosis stages 0–2 (31.3%) (P=.02). For patients with fibrosis stages 0–2, fat score associated independently with development of type 2 diabetes (adjusted hazard ratio, 1.34; 95% CI, 1.03–1.74; P=.03). No histologic factors associated with development of diabetes in patients with fibrosis stage 3–4. Presence of non-alcoholic steatohepatitis was not associated with development of type 2 diabetes.
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Conclusion: In a retrospective study, we found a higher proportion of patients with fibrosis stages 3–4 to develop type 2 diabetes than patients with fibrosis stages 0–2. In patients with fibrosis stages 0–2, fat score associates with risk of type 2 diabetes.
Introduction
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KEY WORDS: NASH, type 2 diabetes mellitus, cirrhosis, risk factor
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Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide, with a global prevalence estimated to approximately 25%.1 A large number of studies have found that patients with NAFLD have an increased risk for development of type 2 diabetes mellitus (T2DM) compared to matched controls without NAFLD, with risk ratios ranging from 1.097.63.2-18 The severity of NAFLD is also associated with T2DM, as previous studies have shown that up to 66% of patients with T2DM suffer from non-alcoholic steatohepatitis (NASH), the more severe form of NAFLD, which is characterized by lobular inflammation and ballooning. 19, 20 In addition to this, T2DM is an established risk factor for development of 3
ACCEPTED MANUSCRIPT hepatocellular carcinoma (HCC), cardiovascular disease and overall mortality.21-23 Thus, the development of T2DM in patients with NAFLD is associated with several potential adverse outcomes. Finding T2DM early in the disease process could allow for more intense treatment and life-style modifications, which could reduce future morbidity and mortality. With the vast
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number of patients with NAFLD, it is vital to identify relevant risk factors associated with the development of T2DM to be able to focus resources on high-risk patient groups for T2DM
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screening.
Since the prevalence of T2DM increases with increasing age, studies investigating the risk of
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T2DM development require a long follow-up to ascertain outcomes. Previous cohort studies investigating the development of T2DM in patients with NAFLD have had relatively short follow-up periods, with only four studies having a follow up period longer than 10 years.9, 17, 24, 25
Also, only one study has used gold standard diagnosis of NAFLD, i.e. liver biopsy,9
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while other studies have relied mostly on ultrasound, which lacks sensitivity for lower degrees of steatosis.26, 27 Previous data from others and us has shown that the only relevant histological marker for mortality is fibrosis stage.28-30 However, the extent to which different
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histological features of NAFLD are useful in predicting other outcomes, including development of T2DM, is still largely unknown. Increased understanding of how the different
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histopathological parameters of NAFLD are associated with development of T2DM could facilitate identification of patients with NAFLD that have a high risk of developing T2DM.
The aim of this study was to examine the cumulative incidence of T2DM and to evaluate the predictive value of histological parameters for the risk of developing T2DM in a large cohort of patients with biopsy confirmed NAFLD during an extended follow-up period.
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Methods and material Study population This was a retrospective cohort study including patients diagnosed with NAFLD using liver biopsy, at the Karolinska University Hospital, Huddinge, during the period 1971 – 2009. All
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biopsies were categorized by a pathologist at the time of biopsy using the systemized nomenclature of medicine (SNOMED).31 The code for hepatic steatosis (M50080) has not changed since the start of the study period and was used to identify all biopsies with hepatic
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steatosis between 1971 and the end of 2009 at the Karolinska University Hospital, Huddinge. These patients were identified and the biopsies were collected from the archive for re-
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examination. Causes for steatosis other than NAFLD were excluded through an extensive review of the patient’s medical charts, which were examined in detail using electronic medical charts (in place since year 2000, covering the majority of the Stockholm residential area) and by reading older paper copies of medical charts. In patients who had moved from
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the Stockholm region or where electronic or paper charts were unavailable, the National Patient Register (NPR) was used to ascertain T2DM diagnosis. The NPR was established in 1964, and includes information on dates of hospital admissions, discharges, and diagnoses
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classified according to the International Classification of Diseases (ICD) codes, 7–10. The register also includes information on hospital-based outpatient visits since 2001. The coverage
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of the register is approximately 99% of all somatic discharge diagnoses, and the validity of hospital discharge diagnoses is between 85–95% depending on diagnosis.32 Patients that reported consuming more than 30 g of alcohol per day for men or 20 g per day for women at baseline or during follow-up was categorized as alcoholic fatty liver disease and were excluded. Patients that reported binge drinking defined as five or more units of alcohol on the same occasion, were also excluded. To minimize the risk of misclassifying patients with fatty liver caused by alcoholic fatty liver disease, patients with no information regarding
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ACCEPTED MANUSCRIPT alcohol intake were excluded. Other liver diseases, including viral hepatitis, were excluded at baseline or through manual chart review during the follow-up. Patients on treatment with drugs associated with hepatic steatosis at the time of biopsy, such as glucocorticoids or
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methotrexate, were also excluded.
Variables
T2DM was defined as having a diagnosis of T2DM in the medical charts or in the NPR, or
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being prescribed any anti-diabetic medication or insulin. The ICD-code used for extraction from the NPR was E11. Follow-up was defined as time from the baseline biopsy to the first
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time of diagnosis of T2DM, prescription of anti-diabetic medication or insulin, death, emigration or the end of the study period (2016-02-20), whichever came first. Baseline information included biomarkers such as liver enzymes, lipids and fasting glucose. Hypertension was defined as a blood pressure of more than 140/90 mmHg after a 5 minute
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resting period in the supine position, or having a formal hypertension diagnosis, or being prescribed any anti-hypertensive medication. Smoking was defined as ever or never being a smoker, and BMI was defined as weight (kg) divided by height (m) squared, allowing for
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light clothing.
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Liver biopsy assessment
All liver biopsies were stored in archives after the initial assessment and all were available for re-analysis. In general, biopsy quality was good despite the sometime long storage time. Biopsies of insufficient quality were excluded from the cohort. One expert liver pathologist (R.H) reviewed all biopsies, which were scored according to the Steatosis Activity Fibrosis score (SAF) using the FLIP algorithm to ascertain presence of NASH.33, 34 Fibrosis was scored according to Kleiner on a 0-4 scale35 and was analysed as a binary variable categorized as stage 0-2 or 3-4. The NAFLD activity score (NAS) was also determined.35 6
ACCEPTED MANUSCRIPT Statistical analysis Differences in baseline variables between patients with or without T2DM development were examined using Fischer’s exact test for categorical variables, and the Wilcoxon ranksum test for continuous variables. A Cox regression model was used with diagnosis of T2DM
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diagnosis as the dependent variable. As patients with significant fibrosis (F3-4) are known to have a higher risk of death than patients with stage 0-2,28, 29 the cohort was stratified on
presence of F3-4, and the two groups were analysed separately. Histological scores for fat (0-
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3), ballooning (0-2), lobular inflammation (0-3), presence of NASH, as well as the NAS as a continuous variable were all tested separately in univariate analysis (model 1). Two
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multivariate models were then created (model 2 and 3). Model 2 was constructed using sex, age and BMI as a priori defined covariates. We then used a stepwise-forward approach to select other potential covariates into model 3, using a p-value of <0.05 as significant. Model 3 was finally adjusted for sex, age, BMI and triglycerides>150mg/dL. Patients who died during
(StataCorp, US).
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Sensitivity analyses
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follow-up were censored. All statistical tests were performed using STATA v. 12.1
First, we tested the risk of T2DM development using an alternate categorization of patients
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Here, patients were categorized into four groups: F0 without NASH (reference group), F0 with NASH, F1-2 or F3-4 irrespective of NASH. Second, to examine if the outcome data obtained from the NPR introduced a bias into the final results, these patients were excluded.
Ethical considerations The regional ethics committee at Karolinska Institutet approved the study. (Dnr 2011/90531/2 and 2015/1591-32).
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Results In total, 2176 patients were found to have biopsy-confirmed fatty liver. The most common indication for liver biopsy was persistently elevated liver transaminases, or the finding of steatosis on liver imaging. Of these, 1666 patients were excluded due to alternate diagnoses
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than NAFLD, including 86 cases with alcoholic liver disease. Of the 510 patients that were classified as NAFLD, 81 (15.9%) had a diagnosis of T2DM at baseline and were excluded. 15 (3.6%) patients had no information on outcome in either medical charts or in the NPR and
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were excluded. Eleven patients were classified as NAFLD, but with biopsies in too bad state for detailed analysis, and an additional seven patients had less than 5% fat content on
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histological examination, and were thus excluded. This study is based on the remaining 396 patients. A flow chart for patient inclusion is presented in figure 1.
Of the patients included in the final analysis, 322 had information on their outcome in medical
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charts. 74 patients (18.7%) had moved from the Stockholm residential area during follow-up, and information on their outcomes were obtained through the NPR. At baseline, patients had a mean age of 45.8 years (SD ±13.7). There were 257 men (64.9%), and patients were in
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general overweight with a mean BMI of 27.5 (SD ±3.9). Patients were followed for a mean period of 18.4 years (SD 9.0, range 0-41 years), or 7276 person-years. During this period, 132
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patients developed T2DM (33.3%), corresponding to an incidence rate of 18 cases per 1000 person-years. The unadjusted cumulative incidence for patients in the cohort to develop T2DM after 5, 10 and 15 years was 5.1%, 10.3% and 16.9% respectively. Baseline characteristics of patients who developed T2DM and patients who did not are presented in table 1.
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ACCEPTED MANUSCRIPT Patients with fibrosis stage 3-4 (N=39) were significantly more likely to develop T2DM than patients with fibrosis stage 0-2 (51.2% vs. 31.3%, p=0.02). Hazard ratios for development of T2DM are presented in table 2 for patients with F0-2, and in table 3 for patients with F3-4 at
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baseline.
In the group with fibrosis stage 0-2, statistically significant univariate hazard ratios were
found for age, triglycerides>150mg/dL, fat score, lobular inflammation score and NAS. Fat
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score was independently associated with development of T2DM in both model 2 (aHR 1.34 for one increase in fat score, 95% CI 1.07-1.66, p=0.01) and model 3 (aHR 1.36, 95% CI
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1.03-1.79, p=0.03).
None of the other histological features, including presence of NASH or the NAS, were associated with development of T2DM (table 2 and 3).
In the group with fibrosis stage 3-4, statistically significant univariate hazard ratios were
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found for BMI and cholesterol>240mmol/L. None of the tested variables were statistically significant in the multivariate analysis (model 3). Figure 2 presents a Kaplan-Meier curve for risk of development of T2DM, stratified on fibrosis stage 0-2 or 3-4. Figure 3 presents a
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score 1 vs. 2-3.
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Kaplan-Meier curve for risk of development of T2DM in the F0-2 group, stratified on fat
During follow-up, there were 87 deaths in the 357 patients with F0-2 (25.6%), compared to 19 deaths (55.9%) in the 39 patients with F3-4 (p<0.001). Development of T2DM was not associated with an increased risk of death, with 40 deaths (30.8%) in patients who developed T2DM compared to 66 deaths (27.1%) in patients who did not (p=0.45).
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ACCEPTED MANUSCRIPT Sensitivity analyses Using a different categorization of patients, and comparing to patients with simple steatosis and F0 (N=48), no increased risk was seen in patients with NASH and F0 (N=29, aHR 0.73, 95% CI 0.17-2.98, p=0.66). For patients with F1-2, the risk was increased (N= 280, aHR 2.51,
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95% CI 1.07-5.88, p= 0.04). In patients with F3-4, no clear increase in risk could be identified using model 3 (N=39, aHR 2.45, 95% CI 0.78 - 7.66, p=0.12). However, data on triglycerides used for model 3 was missing to a large extent in the F34 group (51.2%). Using model 2,
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(aHR 3.07, 95% CI 1.35-6.96, p=0.007).
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without triglycerides, indicated that patients with F34 did have an increased risk for T2DM
Excluding patients where T2DM status was classified using the NPR (N=74) yielded very similar results as the main analysis. Fat score was independently associated with an increased risk of T2DM (aHR 1.40 for one increase in fat score, 95% CI 1.05-1.87, p=0.02) in the group
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with F0-2.
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Discussion This study, with the hitherto longest follow-up ever documented in a large cohort of patients with biopsy-confirmed NAFLD, corroborates that patients with NAFLD have a high risk of T2DM development. One third of the patients included in the present study developed T2DM
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during a follow-up of up to 41 years (mean 18.4 years). Patients with advanced fibrosis were more likely to develop T2DM than patients with lower stages of fibrosis (0-2). Among patients with fibrosis stage 0-2, higher histological scores for fat were independently
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associated with development of T2DM, with a 36% increased hazard per increase in fat score. Fat on liver biopsy is generally seen as benign, as it does not impact mortality.29 Our results
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partly challenge this, as patients with a high fat score seem to be more prone to develop T2DM, although this was not associated with an increased mortality per se.
The incidence rate of T2DM among patients with NAFLD was 18 cases per 1000 person-
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years. This is around five times higher than the incidence rate in the general population of the Stockholm county during the year 2010, where an incidence rate of 3.6 cases per 1000 person-
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years was found.36
In a study of 129 patients with NAFLD diagnosed using liver biopsy, published in 2006,
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Ekstedt and colleagues reported that patients with NASH had a significantly higher risk of having T2DM compared to patients with steatosis with or without unspecific inflammation.9 It has also been previously reported that fibrosis assessed non-invasively through the NAFLD fibrosis score (NFS) is associated with an increased risk of T2DM.37 In a study from 2013, Chang and colleagues followed a cohort of 38.291 patients for five years and concluded that compared to patients without NAFLD, patients with NAFLD and high NFS had a greater risk of developing T2DM than patients with low NFS (aHR 4.74 and 2.00, respectively).37 This
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ACCEPTED MANUSCRIPT finding is confirmed by our study using gold standard liver biopsy, where more than 50% of patients with F3-4 developed T2DM.
Two previous studies, both using ultrasonography to assess the level of steatosis, have
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reported that severity of steatosis in NAFLD is associated with an increased risk of
developing T2DM.4, 10 In 2013, Sung and colleagues reported that patients who maintained or increased their level of steatosis over a period of five years had a significantly elevated risk of
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T2DM compared to patients who had a reduction in the amount of steatosis.38
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As the cohort in our study was diagnosed with NAFLD using liver biopsy, it was possible to assess the importance of the level of steatosis in subgroups of patients with low and high levels of fibrosis. While fat, as reported in the previously mentioned studies, was associated with a higher risk of T2DM in patients with lower levels of fibrosis, this association was not
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found in patients with advanced fibrosis. Given that our study is the first to perform this type of analysis, these findings should be interpreted with caution. Despite this, these results pose interesting questions regarding the pathophysiological interplay between NAFLD and T2DM,
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and indicates that the level of steatosis only is relevant for predicting T2DM in patients where
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fibrosis has not yet progressed to higher stages.
The majority of previous studies performed on cohorts of patients with NAFLD to elucidate the risk of developing T2DM have had short follow-up times and have studied predominantly Asian cohorts. Since our cohort was recruited from the population in Stockholm, Sweden, it is likely that the results in our study are more representative for the populations in Europe and the US. Few studies have had follow-up times over 10 years.9, 17, 24, 25, 39, 40 Hence, our study provides a more comprehensive follow-up than previous studies regarding T2DM
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ACCEPTED MANUSCRIPT development. In the previously mentioned article published in 2006 by Ekstedt et al, the follow-up time was 13.7 years and 58% of the patients in the cohort developed T2DM, as compared to 33% in our study.9 In that study, however, all patients were re-examined at the end of the follow-up, where T2DM was diagnosed de novo in 16% of the cohort.
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Furthermore, patients with T2DM at baseline (8.5%) were not excluded from the cohort, and the patients were on average older (51.0 vs 45.8) and had a higher BMI (mean BMI 28.3 vs 27.6) than the patients in our study, which could account for some of the difference in risk.
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Surprisingly, no increase in mortality was observed in patients who developed T2DM. This
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could be due to the follow-up not being long enough for a difference in mortality to be observed. It might also be explained by the fact that patients with diet-treated T2DM were included in the study. Since diet-treated T2DM is associated with lower mortality than pharmacological treatment, this might dilute the effect of T2DM on mortality. 74 patients (18.7%) moved from the Stockholm residential area during the follow-up, and therefore could
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not be assessed through manual chart review. This presents a methodological limitation since the information obtained through the NPR is not as accurate as information obtained through
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manual chart review. For the majority (81.3%) of the cohort, however, medical charts were available, improving capture of data. Also, a separate sensitivity analysis excluding patient
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data obtained from the NPR yielded similar results as the main analysis, indicating that no bias was introduced by including cases from the NPR.
Further, limitations include the sample size of the cohort, which might have been too small to detect smaller differences in risk. Also, possible misclassification could occur as some patients with T2DM might not have been properly diagnosed yet.
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ACCEPTED MANUSCRIPT Since the individuals included in this study were not chosen from the general population, but from a cohort of patients that were being examined at hospital mostly due to elevated liver transaminases, the examined cohort is not representative for the general population. This problem is somewhat mitigated by the fact that the patients were not included in the cohort
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because they had a specifically high probability for the outcome, but rather because they had some sort of liver pathology, usually elevated transaminases or steatosis on liver imaging. Also, as previously stated, patients were relatively healthy at baseline, without many
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established risk factors for T2DM development. Lastly, information on triglycerides were missing to a large extent (36.7%), especially in the F34-group (51.2%). However, the
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prognostic value of triglycerides as a marker for future risk of T2DM in early NAFLD should be further explored as it was associated with an increased risk in patients with F0-2 when analysed separately (HR 1.78, 95% CI 1.09-2.92 p=0.02). Applications
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Around 25% of the adult population globally suffer from NAFLD.1 Since such a large part of the population carry an increased risk, it is likely that the economic, social and individual
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burden of patients with NAFLD and T2DM will be problematic for health care systems and society in general in the coming decades. This study provides information that might be
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useful for clinicians when identifying patients with NAFLD that are at the highest risk of developing T2DM, which in turn is a strong risk factor for development of cardiovascular disease as well as liver disease and overall mortality.21-23 Once high-risk patients are identified, they can be targeted with more intense treatment and monitoring. Conclusions Patients with NAFLD are at high risk for T2DM development. One third of patients in this cohort developed T2DM after up to 41 years of follow-up. Patients with higher stages of fibrosis are at an increased risk for T2DM development. Among patients with lower stages of 14
ACCEPTED MANUSCRIPT fibrosis, higher histological scores for fat are independently associated with an increased risk of T2DM development. Acknowledgements: Anna Andreasson and Peter Norris for critical revision of the
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manuscript. Ulf Hammar for statistical input.
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17. Goessling W, Massaro JM, Vasan RS, et al. Aminotransferase levels and 20-year risk of metabolic syndrome, diabetes, and cardiovascular disease. Gastroenterology. 2008;135(6):1935-44, 44.e1. Epub 2008/11/18. 18. Nannipieri M, Gonzales C, Baldi S, et al. Liver enzymes, the metabolic syndrome, and incident diabetes: the Mexico City diabetes study. Diabetes Care. 2005;28(7):1757-62. Epub 2005/06/29. 19. Angulo P, Keach JC, Batts KP, et al. Independent predictors of liver fibrosis in patients with nonalcoholic steatohepatitis. Hepatology. 1999;30(6):1356-62. Epub 1999/11/26. 20. Ratziu V, Giral P, Charlotte F, et al. Liver fibrosis in overweight patients. Gastroenterology. 2000;118(6):1117-23. Epub 2000/06/02. 21. El-Serag HB, Tran T, Everhart JE. Diabetes increases the risk of chronic liver disease and hepatocellular carcinoma. Gastroenterology. 2004;126(2):460-8. 22. Emerging Risk Factors C, Sarwar N, Gao P, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215-22. Epub 2010/07/09. 23. Emerging Risk Factors C, Seshasai SR, Kaptoge S, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829-41. Epub 2011/03/04. 24. Fukuda T, Hamaguchi M, Kojima T, et al. The impact of non-alcoholic fatty liver disease on incident type 2 diabetes mellitus in non-overweight individuals. Liver Int. 2016;36(2):27583. Epub 2015/07/16. 25. Yamazaki H, Tsuboya T, Tsuji K, et al. Independent Association Between Improvement of Nonalcoholic Fatty Liver Disease and Reduced Incidence of Type 2 Diabetes. Diabetes Care. 2015;38(9):1673-9. Epub 2015/07/15. 26. Lonardo A, Ballestri S, Marchesini G, et al. Nonalcoholic fatty liver disease: a precursor of the metabolic syndrome. Dig Liver Dis. 2015;47(3):181-90. Epub 2015/03/06. 27. Rinella ME. Nonalcoholic fatty liver disease: a systematic review. Jama. 2015;313(22):2263-73. Epub 2015/06/10. 28. Ekstedt M, Hagstrom H, Nasr P, et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology. 2015;61(5):1547-54. Epub 2014/08/16. 29. Angulo P, Kleiner DE, Dam-Larsen S, et al. Liver Fibrosis, but No Other Histologic Features, Associates With Long-Term Outcomes of Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology. 2015. 30. Stepanova M, Rafiq N, Makhlouf H, et al. Predictors of all-cause mortality and liverrelated mortality in patients with non-alcoholic fatty liver disease (NAFLD). Digestive diseases and sciences. 2013;58(10):3017-23. Epub 2013/06/19. 31. Cote RA, Robboy S. Progress in medical information management. Systematized nomenclature of medicine (SNOMED). Jama. 1980;243(8):756-62. Epub 1980/02/22. 32. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC public health. 2011;11:450. Epub 2011/06/11. 33. Bedossa P, Poitou C, Veyrie N, et al. Histopathological algorithm and scoring system for evaluation of liver lesions in morbidly obese patients. Hepatology. 2012;56(5):1751-9. Epub 2012/06/19. 34. Bedossa P. Utility and appropriateness of the fatty liver inhibition of progression (FLIP) algorithm and steatosis, activity, and fibrosis (SAF) score in the evaluation of biopsies of nonalcoholic fatty liver disease. Hepatology. 2014;60(2):565-75. Epub 2014/04/23. 35. Kleiner DE, Brunt EM, Van Natta M, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313-21.
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36. Andersson T, Ahlbom A, Magnusson C, et al. Prevalence and incidence of diabetes in Stockholm County 1990-2010. PLoS One. 2014;9(8):e104033. Epub 2014/08/15. 37. Chang Y, Jung HS, Yun KE, et al. Cohort study of non-alcoholic fatty liver disease, NAFLD fibrosis score, and the risk of incident diabetes in a Korean population. Am J Gastroenterol. 2013;108(12):1861-8. Epub 2013/10/09. 38. Sung KC, Wild SH, Byrne CD. Resolution of fatty liver and risk of incident diabetes. J Clin Endocrinol Metab. 2013;98(9):3637-43. Epub 2013/07/23. 39. Adams LA, Waters OR, Knuiman MW, et al. NAFLD as a risk factor for the development of diabetes and the metabolic syndrome: an eleven-year follow-up study. The American journal of gastroenterology. 2009;104(4):861-7. Epub 2009/03/19. 40. Kotronen A, Laaksonen MA, Heliovaara M, et al. Fatty liver score and 15-year incidence of type 2 diabetes. Hepatology international. 2013;7(2):610-21. Epub 2013/06/01.
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Table 1. Comparison of baseline variables between outcome groups Free of T2DM (N=264)
Mean/N
Mean/N
SD
SD
Complete data, N
0.44
396
0.11
396
0.92
352
<0.001
395
<0.001
381
Sex, N male (%)
82 (62.0)
Age (years)
47.4
Smoking, ever N (%)
49 (37)
Follow-up time (years)
15.2
Hypertension, N (%)
46 (34.8)
BMI (kg/m2)
28.1
3.8
27.3
4.2
0.03
379
Thrombocytes (109/L)
247.4
64.7
260.7
82.2
0.23
323
Hemoglobin (g/dL)
14.9
1.2
14.8
1.2
0.39
377
WBC (109/L)
6.8
1.8
6.7
2.1
0.46
324
Ferritin (µg/L)
248.8
167.7
235.2
218.5
0.18
187
ALT (U/L)
131.1
523.1
114.3
400.3
0.87
392
AST (U/L)
73.3
249.2
63.6
170.4
0.68
389
ɣGT (U/L)
109.7
143.7
110.8
124.5
0.53
332
0.7
0.5
0.7
0.5
0.48
367
45.0 91 (34)
8.2
20.0
8.9
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56 (20.8)
14.4
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12.0
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Bilirubin (µmol/L)
175 (66.2)
Pvalue
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Developed T2DM (N=132)
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Variable
Albumin (g/dL)
4.3
0.5
4.2
0.4
0.02
344
Cholesterol (mmol/L)
234.3
54.9
223.5
45.8
0.21
275
Triglycerides > 150mg/dL
60 (45.5)
0.03
251
Glucose (mg/dL)
96.2
0.37
307
NASH, N (%)
95 (72)
0.22
396
NAS (0-8)
4.7
0.10
396
Fibrosis (stage 3-4, %)
20 (15.2)
<0.001
396
60 (33)
17.5
94.5
17.9
176 (67) 1.85
4.4 19 (7.2)
2.0
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Table 1. Baseline characteristics. P-values were calculated using Fischer’s exact test for categorical variables and Wilcoxon ranksum test for continuous and ordinal variables. Data is presented as mean values with standard deviations for continuous variables and as total numbers and percentages for categorical variables. Abbreviations: T2DM=type 2 diabetes mellitus; SD=standard deviation; BMI=body mass index; WBC=white blood cells; ALT=alanine aminotransferase; AST=aspartate aminotransferase; ɣGT=gamma glutamyltransferase; NASH=non-alcoholic steatohepatitis. NASH was defined as per the FLIP algorithm.
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Model 2
0.75 0.51 - 1.12
0.16
Age (years)
1.02 1.01 - 1.04
<0.01
BMI (kg/m2)
1.04 0.99 - 1.08
0.09
Cholesterol > 240 (mmol/L)
1.00 1.00 - 1.01
0.48
Triglycerides > 150 (mg/dL) 1.78 1.01 – 2.92
0.02
Glucose > 126 (mg/dL)
1.01 1.00 - 1.02
0.25
Hypertension NASH
1.76 1.19 - 2.62 1.32 0.89 - 1.97
0.005 0.17
Fat (0-4)
1.34 1.09 - 1.66
<0.01
Ballooning (0-4)
1.13 0.89 - 1.43
0.30
Inflammation (0-4)
1.30 1.02 - 1.66
0.03
NAS (0-8)
1.13 1.02 - 1.25 0.01
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Sex, male
P-value aHR 95% CI
P-value
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P-value aHR 95% CI
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95% CI
1.48 1.15
0.97 - 2.27 0.07 0.75 - 1.75 0.52
1.17 1.09
0.71 - 1.93 0.54 0.66 - 1.80 0.75
1.34
1.07 - 1.66 0.01
1.36
1.03 - 1.79 0.03
1.03
0.80 - 1.32 0.83
0.94
0.68 - 1.29 0.70
1.22
0.95 - 1.59 0.13
1.26
0.92 - 1.73 0.15
1.11
1.00 - 1.23 0.06
1.10
0.97 - 1.26 0.14
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HR
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Variable
Model 3
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Model 1
Table 2. Hazard ratios for development of T2DM in patients with fibrosis stage 0-2. Abbreviations: HR=hazard ratio; BMI=body mass index; T2DM=type 2 diabetes mellitus; NASH=non-alcoholic steatohepatitis. NASH was defined as per the FLIP algorithm. Model 1, unadjusted estimates. Model 2 adjusted for age, BMI and sex. Model 3 further adjusted for triglycerides above 150mg/dL.
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Model 2
95% CI
P-value aHR 95% CI
Sex, male
0.92 0.36 - 2.35 0.87
Age (years)
1.00 0.97 - 1.03 0.99
BMI (kg/m2)
1.14 1.01 - 1.29 0.03
Cholesterol > 240 (mmol/L)
1.02 1.00 - 1.04 0.04
Triglycerides > 150 (mg/dL) 1.30 0.32 - 5.27 0.71
Hypertension NASH*
1.04 0.40 - 2.71 0.94 -
Fat (0-4)
1.56 0.86 - 2.84 0.14
Ballooning (0-4)
2.56 0.90 - 7.25 0.08
Inflammation (0-4)
0.73 0.38 - 1.40 0.35
NAS (1-8)
1.22 0.86 - 1.71 0.27
-
-
P-value
-
-
-
1.56
0.74 - 3.31 0.24
1.24
0.41 - 3.74
0.71
1.60
0.53 - 4.79 0.40
8.59
0.37 - 199.2 0.18
0.51
0.24 - 1.11 0.09
0.23
0.03 - 1.89
0.17
1.01
0.70 - 1.47 0.95
1.03
0.56 - 1.83
0.97
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1.02 1.00 - 1.04 0.11
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Glucose > 126 (mg/dL)
P-value aHR 95% CI
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HR
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Variable
Model 3
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Model 1
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Table 3. Hazard ratios for development of T2DM in patients with fibrosis stage 3-4. Model 1, unadjusted estimates. Model 2 adjusted for age, BMI and sex. Model 3 further adjusted for triglycerides above 150mg/dL. Abbreviations: HR=hazard ratio; BMI=body mass index; T2DM=type 2 diabetes mellitus; NASH=non-alcoholic steatohepatitis. NASH was defined as per the FLIP algorithm. *38 of 39 patients in the F3-4group had NASH at baseline, which is why no analysis was possible.
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Figure 1. Flowchart for patients included in cohort. Figure 2. Kaplan-Meier curve for risk of development of T2DM, stratified on fibrosis stage 0-2 or 3-4. Logrank <0.001.
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Figure 3. Kaplan-Meier curve for risk of development of T2DM in patients with fibrosis stage 0-2, stratified on histological fat score of 1 vs 2-3. Logrank <0.001.
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PII: DOI: Reference:
S1542-3565(17)30534-7 10.1016/j.cgh.2017.04.040 YJCGH 55225
To appear in: Clinical Gastroenterology and Hepatology Accepted Date: 17 April 2017 Please cite this article as: Björkström K, Stål P, Hultcrantz R, Hagström H, Histologic Scores for Fat and Fibrosis Associate With Development of Type 2 Diabetes in Patients With Non-alcoholic Fatty Liver Disease, Clinical Gastroenterology and Hepatology (2017), doi: 10.1016/j.cgh.2017.04.040. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Title: Histologic Scores for Fat and Fibrosis Associate With Development of Type 2 Diabetes in Patients With Non-alcoholic Fatty Liver Disease
Short title: Diabetes development in NAFLD
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Authors: Karl Björkström1, Per Stål1,2, Rolf Hultcrantz1,2, Hannes Hagström1,2 Department of Medicine, Huddinge, Karolinska Institutet
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Centre for Digestive Diseases, Unit of Hepatology, Karolinska University Hospital
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Grant Support (Funding):
HH was supported by grants from the Stockholm County Council (ALF projects 20140329 and 20150403) and the Royal Swedish Academy of Sciences (Grant no ME2015-0011). Per Stål was supported by grants from Ruth and Richard Julins Foundation and the Swedish
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Society of Medicine (Gastroenterology Fund)
Independence (role of the sponsors): None of the grant providers had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and
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preparation, review, or approval of the manuscript.
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Abbreviations: ALT, alanine aminotransferase. AST, aspartate aminotransferase. BMI, body mass index. ɣGT, gamma glutamyltransferase. Hb, haemoglobin. HCC, hepatocellular carcinoma. HR, hazard ratio. NAFLD, non-alcoholic fatty liver disease. NASH, non-alcoholic steatohepatitis. NAS, NAFLD activity score. NFS, non-alcoholic fatty liver disease fibrosis score. SD, standard deviation. WBC, white blood cell count.
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ACCEPTED MANUSCRIPT Correspondence and reprint requests: Karl Björkström, Department of Medicine, Huddinge, Karolinska Institutet, 141 86 Stockholm, Sweden
E-mail: [email protected]
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Disclosure / Conflict of interest declaration: None
Study concept and design: HH
Statistical analysis: HH
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Acquisition of data: KB, HH, RH
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Writing Assistance: None. Author contributions:
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Phone: +46 (0) 73 703 41 67 Fax: +46 (0) 8 5858 2335
Interpretation of data: KB, PS, RH, HH
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Drafting of manuscript: KB, HH
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Critical revision: KB, PS, RH, HH Author statement:
Guarantor of article: Hannes Hagström All authors approved the final version of the article, including the authorship list. Total word count: 3274. Abstract: 246. Tables: 3. Figures: 3. Character count for title: 90
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ACCEPTED MANUSCRIPT Abstract: Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a strong risk factor for development of type 2 diabetes, but little is known about how long-term NAFLD or its histologic features affect risk. We aimed to investigate the cumulative incidence of type 2 diabetes in patients with NAFLD, and to identify histologic factors that affect risk of diabetes.
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Methods: We performed a retrospective study of 396 patients in Sweden diagnosed with NAFLD by biopsy analysis from 1971 through 2009 who did not have type 2 diabetes at baseline. Data on development of type 2 diabetes were collected from patient charts and national registers. Patients were categorized into groups with fibrosis stages 0–2 (n=357) or stages 3–4 (n=39). Hazard ratios of histologic parameters for type 2 diabetes development were calculated separately in a multivariate Cox regression model adjusted for sex, age, body mass index, and serum levels of triglycerides above 150 mg/dL.
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Results: During a mean follow-up period of 18.4 years (range 0–41 years), 132 individuals (33%) developed type 2 diabetes. A significantly higher proportion of patients with fibrosis stages 3–4 (51.2%) developed type 2 diabetes than patients with fibrosis stages 0–2 (31.3%) (P=.02). For patients with fibrosis stages 0–2, fat score associated independently with development of type 2 diabetes (adjusted hazard ratio, 1.34; 95% CI, 1.03–1.74; P=.03). No histologic factors associated with development of diabetes in patients with fibrosis stage 3–4. Presence of non-alcoholic steatohepatitis was not associated with development of type 2 diabetes.
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Conclusion: In a retrospective study, we found a higher proportion of patients with fibrosis stages 3–4 to develop type 2 diabetes than patients with fibrosis stages 0–2. In patients with fibrosis stages 0–2, fat score associates with risk of type 2 diabetes.
Introduction
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KEY WORDS: NASH, type 2 diabetes mellitus, cirrhosis, risk factor
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Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide, with a global prevalence estimated to approximately 25%.1 A large number of studies have found that patients with NAFLD have an increased risk for development of type 2 diabetes mellitus (T2DM) compared to matched controls without NAFLD, with risk ratios ranging from 1.097.63.2-18 The severity of NAFLD is also associated with T2DM, as previous studies have shown that up to 66% of patients with T2DM suffer from non-alcoholic steatohepatitis (NASH), the more severe form of NAFLD, which is characterized by lobular inflammation and ballooning. 19, 20 In addition to this, T2DM is an established risk factor for development of 3
ACCEPTED MANUSCRIPT hepatocellular carcinoma (HCC), cardiovascular disease and overall mortality.21-23 Thus, the development of T2DM in patients with NAFLD is associated with several potential adverse outcomes. Finding T2DM early in the disease process could allow for more intense treatment and life-style modifications, which could reduce future morbidity and mortality. With the vast
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number of patients with NAFLD, it is vital to identify relevant risk factors associated with the development of T2DM to be able to focus resources on high-risk patient groups for T2DM
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screening.
Since the prevalence of T2DM increases with increasing age, studies investigating the risk of
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T2DM development require a long follow-up to ascertain outcomes. Previous cohort studies investigating the development of T2DM in patients with NAFLD have had relatively short follow-up periods, with only four studies having a follow up period longer than 10 years.9, 17, 24, 25
Also, only one study has used gold standard diagnosis of NAFLD, i.e. liver biopsy,9
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while other studies have relied mostly on ultrasound, which lacks sensitivity for lower degrees of steatosis.26, 27 Previous data from others and us has shown that the only relevant histological marker for mortality is fibrosis stage.28-30 However, the extent to which different
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histological features of NAFLD are useful in predicting other outcomes, including development of T2DM, is still largely unknown. Increased understanding of how the different
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histopathological parameters of NAFLD are associated with development of T2DM could facilitate identification of patients with NAFLD that have a high risk of developing T2DM.
The aim of this study was to examine the cumulative incidence of T2DM and to evaluate the predictive value of histological parameters for the risk of developing T2DM in a large cohort of patients with biopsy confirmed NAFLD during an extended follow-up period.
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Methods and material Study population This was a retrospective cohort study including patients diagnosed with NAFLD using liver biopsy, at the Karolinska University Hospital, Huddinge, during the period 1971 – 2009. All
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biopsies were categorized by a pathologist at the time of biopsy using the systemized nomenclature of medicine (SNOMED).31 The code for hepatic steatosis (M50080) has not changed since the start of the study period and was used to identify all biopsies with hepatic
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steatosis between 1971 and the end of 2009 at the Karolinska University Hospital, Huddinge. These patients were identified and the biopsies were collected from the archive for re-
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examination. Causes for steatosis other than NAFLD were excluded through an extensive review of the patient’s medical charts, which were examined in detail using electronic medical charts (in place since year 2000, covering the majority of the Stockholm residential area) and by reading older paper copies of medical charts. In patients who had moved from
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the Stockholm region or where electronic or paper charts were unavailable, the National Patient Register (NPR) was used to ascertain T2DM diagnosis. The NPR was established in 1964, and includes information on dates of hospital admissions, discharges, and diagnoses
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classified according to the International Classification of Diseases (ICD) codes, 7–10. The register also includes information on hospital-based outpatient visits since 2001. The coverage
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of the register is approximately 99% of all somatic discharge diagnoses, and the validity of hospital discharge diagnoses is between 85–95% depending on diagnosis.32 Patients that reported consuming more than 30 g of alcohol per day for men or 20 g per day for women at baseline or during follow-up was categorized as alcoholic fatty liver disease and were excluded. Patients that reported binge drinking defined as five or more units of alcohol on the same occasion, were also excluded. To minimize the risk of misclassifying patients with fatty liver caused by alcoholic fatty liver disease, patients with no information regarding
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methotrexate, were also excluded.
Variables
T2DM was defined as having a diagnosis of T2DM in the medical charts or in the NPR, or
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being prescribed any anti-diabetic medication or insulin. The ICD-code used for extraction from the NPR was E11. Follow-up was defined as time from the baseline biopsy to the first
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time of diagnosis of T2DM, prescription of anti-diabetic medication or insulin, death, emigration or the end of the study period (2016-02-20), whichever came first. Baseline information included biomarkers such as liver enzymes, lipids and fasting glucose. Hypertension was defined as a blood pressure of more than 140/90 mmHg after a 5 minute
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resting period in the supine position, or having a formal hypertension diagnosis, or being prescribed any anti-hypertensive medication. Smoking was defined as ever or never being a smoker, and BMI was defined as weight (kg) divided by height (m) squared, allowing for
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light clothing.
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Liver biopsy assessment
All liver biopsies were stored in archives after the initial assessment and all were available for re-analysis. In general, biopsy quality was good despite the sometime long storage time. Biopsies of insufficient quality were excluded from the cohort. One expert liver pathologist (R.H) reviewed all biopsies, which were scored according to the Steatosis Activity Fibrosis score (SAF) using the FLIP algorithm to ascertain presence of NASH.33, 34 Fibrosis was scored according to Kleiner on a 0-4 scale35 and was analysed as a binary variable categorized as stage 0-2 or 3-4. The NAFLD activity score (NAS) was also determined.35 6
ACCEPTED MANUSCRIPT Statistical analysis Differences in baseline variables between patients with or without T2DM development were examined using Fischer’s exact test for categorical variables, and the Wilcoxon ranksum test for continuous variables. A Cox regression model was used with diagnosis of T2DM
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diagnosis as the dependent variable. As patients with significant fibrosis (F3-4) are known to have a higher risk of death than patients with stage 0-2,28, 29 the cohort was stratified on
presence of F3-4, and the two groups were analysed separately. Histological scores for fat (0-
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3), ballooning (0-2), lobular inflammation (0-3), presence of NASH, as well as the NAS as a continuous variable were all tested separately in univariate analysis (model 1). Two
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multivariate models were then created (model 2 and 3). Model 2 was constructed using sex, age and BMI as a priori defined covariates. We then used a stepwise-forward approach to select other potential covariates into model 3, using a p-value of <0.05 as significant. Model 3 was finally adjusted for sex, age, BMI and triglycerides>150mg/dL. Patients who died during
(StataCorp, US).
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Sensitivity analyses
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follow-up were censored. All statistical tests were performed using STATA v. 12.1
First, we tested the risk of T2DM development using an alternate categorization of patients
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Here, patients were categorized into four groups: F0 without NASH (reference group), F0 with NASH, F1-2 or F3-4 irrespective of NASH. Second, to examine if the outcome data obtained from the NPR introduced a bias into the final results, these patients were excluded.
Ethical considerations The regional ethics committee at Karolinska Institutet approved the study. (Dnr 2011/90531/2 and 2015/1591-32).
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Results In total, 2176 patients were found to have biopsy-confirmed fatty liver. The most common indication for liver biopsy was persistently elevated liver transaminases, or the finding of steatosis on liver imaging. Of these, 1666 patients were excluded due to alternate diagnoses
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than NAFLD, including 86 cases with alcoholic liver disease. Of the 510 patients that were classified as NAFLD, 81 (15.9%) had a diagnosis of T2DM at baseline and were excluded. 15 (3.6%) patients had no information on outcome in either medical charts or in the NPR and
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were excluded. Eleven patients were classified as NAFLD, but with biopsies in too bad state for detailed analysis, and an additional seven patients had less than 5% fat content on
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histological examination, and were thus excluded. This study is based on the remaining 396 patients. A flow chart for patient inclusion is presented in figure 1.
Of the patients included in the final analysis, 322 had information on their outcome in medical
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charts. 74 patients (18.7%) had moved from the Stockholm residential area during follow-up, and information on their outcomes were obtained through the NPR. At baseline, patients had a mean age of 45.8 years (SD ±13.7). There were 257 men (64.9%), and patients were in
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general overweight with a mean BMI of 27.5 (SD ±3.9). Patients were followed for a mean period of 18.4 years (SD 9.0, range 0-41 years), or 7276 person-years. During this period, 132
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patients developed T2DM (33.3%), corresponding to an incidence rate of 18 cases per 1000 person-years. The unadjusted cumulative incidence for patients in the cohort to develop T2DM after 5, 10 and 15 years was 5.1%, 10.3% and 16.9% respectively. Baseline characteristics of patients who developed T2DM and patients who did not are presented in table 1.
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ACCEPTED MANUSCRIPT Patients with fibrosis stage 3-4 (N=39) were significantly more likely to develop T2DM than patients with fibrosis stage 0-2 (51.2% vs. 31.3%, p=0.02). Hazard ratios for development of T2DM are presented in table 2 for patients with F0-2, and in table 3 for patients with F3-4 at
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baseline.
In the group with fibrosis stage 0-2, statistically significant univariate hazard ratios were
found for age, triglycerides>150mg/dL, fat score, lobular inflammation score and NAS. Fat
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score was independently associated with development of T2DM in both model 2 (aHR 1.34 for one increase in fat score, 95% CI 1.07-1.66, p=0.01) and model 3 (aHR 1.36, 95% CI
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1.03-1.79, p=0.03).
None of the other histological features, including presence of NASH or the NAS, were associated with development of T2DM (table 2 and 3).
In the group with fibrosis stage 3-4, statistically significant univariate hazard ratios were
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found for BMI and cholesterol>240mmol/L. None of the tested variables were statistically significant in the multivariate analysis (model 3). Figure 2 presents a Kaplan-Meier curve for risk of development of T2DM, stratified on fibrosis stage 0-2 or 3-4. Figure 3 presents a
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score 1 vs. 2-3.
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Kaplan-Meier curve for risk of development of T2DM in the F0-2 group, stratified on fat
During follow-up, there were 87 deaths in the 357 patients with F0-2 (25.6%), compared to 19 deaths (55.9%) in the 39 patients with F3-4 (p<0.001). Development of T2DM was not associated with an increased risk of death, with 40 deaths (30.8%) in patients who developed T2DM compared to 66 deaths (27.1%) in patients who did not (p=0.45).
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ACCEPTED MANUSCRIPT Sensitivity analyses Using a different categorization of patients, and comparing to patients with simple steatosis and F0 (N=48), no increased risk was seen in patients with NASH and F0 (N=29, aHR 0.73, 95% CI 0.17-2.98, p=0.66). For patients with F1-2, the risk was increased (N= 280, aHR 2.51,
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95% CI 1.07-5.88, p= 0.04). In patients with F3-4, no clear increase in risk could be identified using model 3 (N=39, aHR 2.45, 95% CI 0.78 - 7.66, p=0.12). However, data on triglycerides used for model 3 was missing to a large extent in the F34 group (51.2%). Using model 2,
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(aHR 3.07, 95% CI 1.35-6.96, p=0.007).
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without triglycerides, indicated that patients with F34 did have an increased risk for T2DM
Excluding patients where T2DM status was classified using the NPR (N=74) yielded very similar results as the main analysis. Fat score was independently associated with an increased risk of T2DM (aHR 1.40 for one increase in fat score, 95% CI 1.05-1.87, p=0.02) in the group
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with F0-2.
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Discussion This study, with the hitherto longest follow-up ever documented in a large cohort of patients with biopsy-confirmed NAFLD, corroborates that patients with NAFLD have a high risk of T2DM development. One third of the patients included in the present study developed T2DM
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during a follow-up of up to 41 years (mean 18.4 years). Patients with advanced fibrosis were more likely to develop T2DM than patients with lower stages of fibrosis (0-2). Among patients with fibrosis stage 0-2, higher histological scores for fat were independently
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associated with development of T2DM, with a 36% increased hazard per increase in fat score. Fat on liver biopsy is generally seen as benign, as it does not impact mortality.29 Our results
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partly challenge this, as patients with a high fat score seem to be more prone to develop T2DM, although this was not associated with an increased mortality per se.
The incidence rate of T2DM among patients with NAFLD was 18 cases per 1000 person-
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years. This is around five times higher than the incidence rate in the general population of the Stockholm county during the year 2010, where an incidence rate of 3.6 cases per 1000 person-
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years was found.36
In a study of 129 patients with NAFLD diagnosed using liver biopsy, published in 2006,
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Ekstedt and colleagues reported that patients with NASH had a significantly higher risk of having T2DM compared to patients with steatosis with or without unspecific inflammation.9 It has also been previously reported that fibrosis assessed non-invasively through the NAFLD fibrosis score (NFS) is associated with an increased risk of T2DM.37 In a study from 2013, Chang and colleagues followed a cohort of 38.291 patients for five years and concluded that compared to patients without NAFLD, patients with NAFLD and high NFS had a greater risk of developing T2DM than patients with low NFS (aHR 4.74 and 2.00, respectively).37 This
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Two previous studies, both using ultrasonography to assess the level of steatosis, have
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reported that severity of steatosis in NAFLD is associated with an increased risk of
developing T2DM.4, 10 In 2013, Sung and colleagues reported that patients who maintained or increased their level of steatosis over a period of five years had a significantly elevated risk of
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T2DM compared to patients who had a reduction in the amount of steatosis.38
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As the cohort in our study was diagnosed with NAFLD using liver biopsy, it was possible to assess the importance of the level of steatosis in subgroups of patients with low and high levels of fibrosis. While fat, as reported in the previously mentioned studies, was associated with a higher risk of T2DM in patients with lower levels of fibrosis, this association was not
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found in patients with advanced fibrosis. Given that our study is the first to perform this type of analysis, these findings should be interpreted with caution. Despite this, these results pose interesting questions regarding the pathophysiological interplay between NAFLD and T2DM,
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and indicates that the level of steatosis only is relevant for predicting T2DM in patients where
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fibrosis has not yet progressed to higher stages.
The majority of previous studies performed on cohorts of patients with NAFLD to elucidate the risk of developing T2DM have had short follow-up times and have studied predominantly Asian cohorts. Since our cohort was recruited from the population in Stockholm, Sweden, it is likely that the results in our study are more representative for the populations in Europe and the US. Few studies have had follow-up times over 10 years.9, 17, 24, 25, 39, 40 Hence, our study provides a more comprehensive follow-up than previous studies regarding T2DM
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Furthermore, patients with T2DM at baseline (8.5%) were not excluded from the cohort, and the patients were on average older (51.0 vs 45.8) and had a higher BMI (mean BMI 28.3 vs 27.6) than the patients in our study, which could account for some of the difference in risk.
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Surprisingly, no increase in mortality was observed in patients who developed T2DM. This
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could be due to the follow-up not being long enough for a difference in mortality to be observed. It might also be explained by the fact that patients with diet-treated T2DM were included in the study. Since diet-treated T2DM is associated with lower mortality than pharmacological treatment, this might dilute the effect of T2DM on mortality. 74 patients (18.7%) moved from the Stockholm residential area during the follow-up, and therefore could
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not be assessed through manual chart review. This presents a methodological limitation since the information obtained through the NPR is not as accurate as information obtained through
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manual chart review. For the majority (81.3%) of the cohort, however, medical charts were available, improving capture of data. Also, a separate sensitivity analysis excluding patient
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data obtained from the NPR yielded similar results as the main analysis, indicating that no bias was introduced by including cases from the NPR.
Further, limitations include the sample size of the cohort, which might have been too small to detect smaller differences in risk. Also, possible misclassification could occur as some patients with T2DM might not have been properly diagnosed yet.
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ACCEPTED MANUSCRIPT Since the individuals included in this study were not chosen from the general population, but from a cohort of patients that were being examined at hospital mostly due to elevated liver transaminases, the examined cohort is not representative for the general population. This problem is somewhat mitigated by the fact that the patients were not included in the cohort
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because they had a specifically high probability for the outcome, but rather because they had some sort of liver pathology, usually elevated transaminases or steatosis on liver imaging. Also, as previously stated, patients were relatively healthy at baseline, without many
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established risk factors for T2DM development. Lastly, information on triglycerides were missing to a large extent (36.7%), especially in the F34-group (51.2%). However, the
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prognostic value of triglycerides as a marker for future risk of T2DM in early NAFLD should be further explored as it was associated with an increased risk in patients with F0-2 when analysed separately (HR 1.78, 95% CI 1.09-2.92 p=0.02). Applications
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Around 25% of the adult population globally suffer from NAFLD.1 Since such a large part of the population carry an increased risk, it is likely that the economic, social and individual
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burden of patients with NAFLD and T2DM will be problematic for health care systems and society in general in the coming decades. This study provides information that might be
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useful for clinicians when identifying patients with NAFLD that are at the highest risk of developing T2DM, which in turn is a strong risk factor for development of cardiovascular disease as well as liver disease and overall mortality.21-23 Once high-risk patients are identified, they can be targeted with more intense treatment and monitoring. Conclusions Patients with NAFLD are at high risk for T2DM development. One third of patients in this cohort developed T2DM after up to 41 years of follow-up. Patients with higher stages of fibrosis are at an increased risk for T2DM development. Among patients with lower stages of 14
ACCEPTED MANUSCRIPT fibrosis, higher histological scores for fat are independently associated with an increased risk of T2DM development. Acknowledgements: Anna Andreasson and Peter Norris for critical revision of the
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manuscript. Ulf Hammar for statistical input.
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References
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17. Goessling W, Massaro JM, Vasan RS, et al. Aminotransferase levels and 20-year risk of metabolic syndrome, diabetes, and cardiovascular disease. Gastroenterology. 2008;135(6):1935-44, 44.e1. Epub 2008/11/18. 18. Nannipieri M, Gonzales C, Baldi S, et al. Liver enzymes, the metabolic syndrome, and incident diabetes: the Mexico City diabetes study. Diabetes Care. 2005;28(7):1757-62. Epub 2005/06/29. 19. Angulo P, Keach JC, Batts KP, et al. Independent predictors of liver fibrosis in patients with nonalcoholic steatohepatitis. Hepatology. 1999;30(6):1356-62. Epub 1999/11/26. 20. Ratziu V, Giral P, Charlotte F, et al. Liver fibrosis in overweight patients. Gastroenterology. 2000;118(6):1117-23. Epub 2000/06/02. 21. El-Serag HB, Tran T, Everhart JE. Diabetes increases the risk of chronic liver disease and hepatocellular carcinoma. Gastroenterology. 2004;126(2):460-8. 22. Emerging Risk Factors C, Sarwar N, Gao P, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215-22. Epub 2010/07/09. 23. Emerging Risk Factors C, Seshasai SR, Kaptoge S, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829-41. Epub 2011/03/04. 24. Fukuda T, Hamaguchi M, Kojima T, et al. The impact of non-alcoholic fatty liver disease on incident type 2 diabetes mellitus in non-overweight individuals. Liver Int. 2016;36(2):27583. Epub 2015/07/16. 25. Yamazaki H, Tsuboya T, Tsuji K, et al. Independent Association Between Improvement of Nonalcoholic Fatty Liver Disease and Reduced Incidence of Type 2 Diabetes. Diabetes Care. 2015;38(9):1673-9. Epub 2015/07/15. 26. Lonardo A, Ballestri S, Marchesini G, et al. Nonalcoholic fatty liver disease: a precursor of the metabolic syndrome. Dig Liver Dis. 2015;47(3):181-90. Epub 2015/03/06. 27. Rinella ME. Nonalcoholic fatty liver disease: a systematic review. Jama. 2015;313(22):2263-73. Epub 2015/06/10. 28. Ekstedt M, Hagstrom H, Nasr P, et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology. 2015;61(5):1547-54. Epub 2014/08/16. 29. Angulo P, Kleiner DE, Dam-Larsen S, et al. Liver Fibrosis, but No Other Histologic Features, Associates With Long-Term Outcomes of Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology. 2015. 30. Stepanova M, Rafiq N, Makhlouf H, et al. Predictors of all-cause mortality and liverrelated mortality in patients with non-alcoholic fatty liver disease (NAFLD). Digestive diseases and sciences. 2013;58(10):3017-23. Epub 2013/06/19. 31. Cote RA, Robboy S. Progress in medical information management. Systematized nomenclature of medicine (SNOMED). Jama. 1980;243(8):756-62. Epub 1980/02/22. 32. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the Swedish national inpatient register. BMC public health. 2011;11:450. Epub 2011/06/11. 33. Bedossa P, Poitou C, Veyrie N, et al. Histopathological algorithm and scoring system for evaluation of liver lesions in morbidly obese patients. Hepatology. 2012;56(5):1751-9. Epub 2012/06/19. 34. Bedossa P. Utility and appropriateness of the fatty liver inhibition of progression (FLIP) algorithm and steatosis, activity, and fibrosis (SAF) score in the evaluation of biopsies of nonalcoholic fatty liver disease. Hepatology. 2014;60(2):565-75. Epub 2014/04/23. 35. Kleiner DE, Brunt EM, Van Natta M, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313-21.
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36. Andersson T, Ahlbom A, Magnusson C, et al. Prevalence and incidence of diabetes in Stockholm County 1990-2010. PLoS One. 2014;9(8):e104033. Epub 2014/08/15. 37. Chang Y, Jung HS, Yun KE, et al. Cohort study of non-alcoholic fatty liver disease, NAFLD fibrosis score, and the risk of incident diabetes in a Korean population. Am J Gastroenterol. 2013;108(12):1861-8. Epub 2013/10/09. 38. Sung KC, Wild SH, Byrne CD. Resolution of fatty liver and risk of incident diabetes. J Clin Endocrinol Metab. 2013;98(9):3637-43. Epub 2013/07/23. 39. Adams LA, Waters OR, Knuiman MW, et al. NAFLD as a risk factor for the development of diabetes and the metabolic syndrome: an eleven-year follow-up study. The American journal of gastroenterology. 2009;104(4):861-7. Epub 2009/03/19. 40. Kotronen A, Laaksonen MA, Heliovaara M, et al. Fatty liver score and 15-year incidence of type 2 diabetes. Hepatology international. 2013;7(2):610-21. Epub 2013/06/01.
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Table 1. Comparison of baseline variables between outcome groups Free of T2DM (N=264)
Mean/N
Mean/N
SD
SD
Complete data, N
0.44
396
0.11
396
0.92
352
<0.001
395
<0.001
381
Sex, N male (%)
82 (62.0)
Age (years)
47.4
Smoking, ever N (%)
49 (37)
Follow-up time (years)
15.2
Hypertension, N (%)
46 (34.8)
BMI (kg/m2)
28.1
3.8
27.3
4.2
0.03
379
Thrombocytes (109/L)
247.4
64.7
260.7
82.2
0.23
323
Hemoglobin (g/dL)
14.9
1.2
14.8
1.2
0.39
377
WBC (109/L)
6.8
1.8
6.7
2.1
0.46
324
Ferritin (µg/L)
248.8
167.7
235.2
218.5
0.18
187
ALT (U/L)
131.1
523.1
114.3
400.3
0.87
392
AST (U/L)
73.3
249.2
63.6
170.4
0.68
389
ɣGT (U/L)
109.7
143.7
110.8
124.5
0.53
332
0.7
0.5
0.7
0.5
0.48
367
45.0 91 (34)
8.2
20.0
8.9
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56 (20.8)
14.4
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12.0
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Bilirubin (µmol/L)
175 (66.2)
Pvalue
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Developed T2DM (N=132)
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Variable
Albumin (g/dL)
4.3
0.5
4.2
0.4
0.02
344
Cholesterol (mmol/L)
234.3
54.9
223.5
45.8
0.21
275
Triglycerides > 150mg/dL
60 (45.5)
0.03
251
Glucose (mg/dL)
96.2
0.37
307
NASH, N (%)
95 (72)
0.22
396
NAS (0-8)
4.7
0.10
396
Fibrosis (stage 3-4, %)
20 (15.2)
<0.001
396
60 (33)
17.5
94.5
17.9
176 (67) 1.85
4.4 19 (7.2)
2.0
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Table 1. Baseline characteristics. P-values were calculated using Fischer’s exact test for categorical variables and Wilcoxon ranksum test for continuous and ordinal variables. Data is presented as mean values with standard deviations for continuous variables and as total numbers and percentages for categorical variables. Abbreviations: T2DM=type 2 diabetes mellitus; SD=standard deviation; BMI=body mass index; WBC=white blood cells; ALT=alanine aminotransferase; AST=aspartate aminotransferase; ɣGT=gamma glutamyltransferase; NASH=non-alcoholic steatohepatitis. NASH was defined as per the FLIP algorithm.
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Model 2
0.75 0.51 - 1.12
0.16
Age (years)
1.02 1.01 - 1.04
<0.01
BMI (kg/m2)
1.04 0.99 - 1.08
0.09
Cholesterol > 240 (mmol/L)
1.00 1.00 - 1.01
0.48
Triglycerides > 150 (mg/dL) 1.78 1.01 – 2.92
0.02
Glucose > 126 (mg/dL)
1.01 1.00 - 1.02
0.25
Hypertension NASH
1.76 1.19 - 2.62 1.32 0.89 - 1.97
0.005 0.17
Fat (0-4)
1.34 1.09 - 1.66
<0.01
Ballooning (0-4)
1.13 0.89 - 1.43
0.30
Inflammation (0-4)
1.30 1.02 - 1.66
0.03
NAS (0-8)
1.13 1.02 - 1.25 0.01
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Sex, male
P-value aHR 95% CI
P-value
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P-value aHR 95% CI
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95% CI
1.48 1.15
0.97 - 2.27 0.07 0.75 - 1.75 0.52
1.17 1.09
0.71 - 1.93 0.54 0.66 - 1.80 0.75
1.34
1.07 - 1.66 0.01
1.36
1.03 - 1.79 0.03
1.03
0.80 - 1.32 0.83
0.94
0.68 - 1.29 0.70
1.22
0.95 - 1.59 0.13
1.26
0.92 - 1.73 0.15
1.11
1.00 - 1.23 0.06
1.10
0.97 - 1.26 0.14
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Model 3
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Model 1
Table 2. Hazard ratios for development of T2DM in patients with fibrosis stage 0-2. Abbreviations: HR=hazard ratio; BMI=body mass index; T2DM=type 2 diabetes mellitus; NASH=non-alcoholic steatohepatitis. NASH was defined as per the FLIP algorithm. Model 1, unadjusted estimates. Model 2 adjusted for age, BMI and sex. Model 3 further adjusted for triglycerides above 150mg/dL.
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Model 2
95% CI
P-value aHR 95% CI
Sex, male
0.92 0.36 - 2.35 0.87
Age (years)
1.00 0.97 - 1.03 0.99
BMI (kg/m2)
1.14 1.01 - 1.29 0.03
Cholesterol > 240 (mmol/L)
1.02 1.00 - 1.04 0.04
Triglycerides > 150 (mg/dL) 1.30 0.32 - 5.27 0.71
Hypertension NASH*
1.04 0.40 - 2.71 0.94 -
Fat (0-4)
1.56 0.86 - 2.84 0.14
Ballooning (0-4)
2.56 0.90 - 7.25 0.08
Inflammation (0-4)
0.73 0.38 - 1.40 0.35
NAS (1-8)
1.22 0.86 - 1.71 0.27
-
-
P-value
-
-
-
1.56
0.74 - 3.31 0.24
1.24
0.41 - 3.74
0.71
1.60
0.53 - 4.79 0.40
8.59
0.37 - 199.2 0.18
0.51
0.24 - 1.11 0.09
0.23
0.03 - 1.89
0.17
1.01
0.70 - 1.47 0.95
1.03
0.56 - 1.83
0.97
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1.02 1.00 - 1.04 0.11
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Glucose > 126 (mg/dL)
P-value aHR 95% CI
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HR
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Model 3
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Model 1
-
Table 3. Hazard ratios for development of T2DM in patients with fibrosis stage 3-4. Model 1, unadjusted estimates. Model 2 adjusted for age, BMI and sex. Model 3 further adjusted for triglycerides above 150mg/dL. Abbreviations: HR=hazard ratio; BMI=body mass index; T2DM=type 2 diabetes mellitus; NASH=non-alcoholic steatohepatitis. NASH was defined as per the FLIP algorithm. *38 of 39 patients in the F3-4group had NASH at baseline, which is why no analysis was possible.
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Figure 1. Flowchart for patients included in cohort. Figure 2. Kaplan-Meier curve for risk of development of T2DM, stratified on fibrosis stage 0-2 or 3-4. Logrank <0.001.
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Figure 3. Kaplan-Meier curve for risk of development of T2DM in patients with fibrosis stage 0-2, stratified on histological fat score of 1 vs 2-3. Logrank <0.001.
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