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Recruiting NCT05597709

Prevalence of MAFLD in Patients With Type 2 Diabetes in Jiangsu Province of China

— Observational Type 2 Diabetes Mellitus in Remission Metabolic Associated Fatty Liver Disease

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Ultrasound attenuation parameter measurement, fasting blood glucose and fasting insulin determination.
Who it may be relevant to
Registry conditions: Type 2 Diabetes Mellitus in Remission, Metabolic Associated Fatty Liver Disease. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

Prevalence of Metabolic Associated Fatty Liver Disease in Patients With Type 2 Diabetes in Jiangsu Province of China: a Prospective, Multicenter, Real-world Study

Overview

In 2019, the number of patients with diabetes was about 463 million in the world, accounting for 8.3% of the total population, and it is expected to rise to 578 million (9.2%) by 2030 and 700 million (9.6%) by 2045. According to the WHO diagnostic criteria, the prevalence of diabetes among adults in China from 2015 to 2017 was 11.2%, of which over 90% were type 2 diabetes mellitus (T2DM). The global prevalence of non-alcoholic fatty liver disease (NAFLD) is also very high, which was approximately 25% in 2016. The prevalence of NAFLD may continue to rise. NAFLD is often accompanied by clinical manifestations of metabolic syndrome, such as obesity, T2DM, hyperlipidemia and hypertension.

Detailed description

The presence of NAFLD not only increases the risk of T2DM, but also accelerates the process of various diabetes-related organ damage in patients with T2DM. Similarly, T2DM also increases the risk of NAFLD. However, in patients with T2DM, there are few reports on the correlation between ultrasound attenuation parameters for non-invasive assessment of liver fat content and insulin resistance. In addition, T2DM may be the most important predictor of adverse clinical outcomes in NAFLD patients. T2DM is an important predictor of NAFLD patients progressing to compensated advanced chronic liver disease (cACLD), and even cirrhotic portal hypertension and other end-stage liver diseases.

In February 2020, international experts suggested NAFLD to be renamed metabolic associated fatty liver disease (MAFLD). In April of the same year, the Journal of Hepatology released a new definition and diagnosis of MAFLD with the criteria based on histological (liver biopsy), imaging, or blood biomarker indicating the presence of hepatic fat accumulation (hepatocyte steatosis), in combination with one of the following 3 conditions: overweight/obesity, type 2 diabetes and metabolic dysfunction. The new diagnostic criteria are based on underlying metabolic abnormalities and recognize that MAFLD often coexists with other diseases.

Therefore, this study aims to investigate the prevalence and clinical characteristics of MAFLD in patients with T2DM, as well as the correlation between UAP and insulin resistance in T2DM. Patients will be followed up to 5 years for the clinical outcomes at 3months, 6 months, 12 months, 36 months, 48 months and 60 months respectively and the risk factors affecting the clinical outcomes of patients with T2DM will be analyzed.

Interventions

  • Procedure Ultrasound attenuation parameter measurement, fasting blood glucose and fasting insulin determination
    Eligible participants will receive ultrasound attenuation parameter with iLivTouch, fasting blood glucose and fasting insulin determination

Primary outcome measures

  • The proportion of patients with MAFLD in the T2DM population screened by UAP with iLivTouch [Time frame: 12 months]
  • Correlation between UAP and insulin resistance [Time frame: 12 months]
  • Analysis of risk factors for clinical outcomes in patients with T2DM [Time frame: 5 years]

Eligibility criteria

Inclusion criteria

  • Diagnosed as T2DM according to the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes
  • UAP were measured based on iLivTouch
  • Willing to attend this study and able to provide the written informed consent.

Exclusion criteria

  • Other types of diabetes
  • Patients unable to receive regular follow-up

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

China · 1 center
  • Zhongda Hospital, Medical School, Southeast University — Nanjing

Publications

  • Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, Colagiuri S, Guariguata L, Motala AA, Ogurtsova K, Shaw JE, Bright D, Williams R; IDF Diabetes Atlas Committee. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019 Nov;157:107843. do PMID 31518657
  • Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, Harrison SA, Brunt EM, Sanyal AJ. The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018 Jan;67(1):328-357. doi: 10.1002/hep.29367. Epub 2017 Sep 29. No abstract available. PMID 28714183
  • 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 Jul;64(1):73-84. doi: 10.1002/hep.28431. Epub 2016 Feb 22. PMID 26707365
  • Byrne CD, Targher G. NAFLD: a multisystem disease. J Hepatol. 2015 Apr;62(1 Suppl):S47-64. doi: 10.1016/j.jhep.2014.12.012. PMID 25920090
  • Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, George J, Bugianesi E. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018 Jan;15(1):11-20. doi: 10.1038/nrgastro.2017.109. Epub 2017 Sep 20. PMID 28930295
  • Lyu K, Zhang Y, Zhang D, Kahn M, Ter Horst KW, Rodrigues MRS, Gaspar RC, Hirabara SM, Luukkonen PK, Lee S, Bhanot S, Rinehart J, Blume N, Rasch MG, Serlie MJ, Bogan JS, Cline GW, Samuel VT, Shulman GI. A Membrane-Bound Diacylglycerol Species Induces PKCϵ-Mediated Hepatic Insulin Resistance. Cell Metab. 2020 Oct 6;32(4):654-664.e5. doi: 10.1016/j.cmet.2020.08.001. Epub 2020 Sep 2. PMID 32882164
  • Hossain N, Afendy A, Stepanova M, Nader F, Srishord M, Rafiq N, Goodman Z, Younossi Z. Independent predictors of fibrosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2009 Nov;7(11):1224-9, 1229.e1-2. doi: 10.1016/j.cgh.2009.06.007. Epub 2009 Jun 25. PMID 19559819
  • Stepanova M, Rafiq N, Makhlouf H, Agrawal R, Kaur I, Younoszai Z, McCullough A, Goodman Z, Younossi ZM. Predictors of all-cause mortality and liver-related mortality in patients with non-alcoholic fatty liver disease (NAFLD). Dig Dis Sci. 2013 Oct;58(10):3017-23. doi: 10.1007/s10620-013-2743-5. Epub 2013 Jun 18. PMID 23775317

Identifiers

NCT: NCT05597709 · MAFLD

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗