Die Häufigkeit von diagnostizierten Fettlebererkrankungen (NAFLD) in der deutschen Bevölkerung – Eine Analyse auf der Basis von GKV-Routinedaten

Zusammenfassung

Hintergrund Die nichtalkoholische Fettlebererkrankung (NAFLD) zählt zu den häufigsten Lebererkrankungen in Deutschland. Langfristig besteht das Risiko einer Leberzirrhose und weiterer Folgeerkrankungen. Epidemiologische Studien zur NAFLD in Deutschland liegen kaum vor. Ziel der vorliegenden Arbeit ist eine dezidierte Analyse der administrativen Inzidenz und Prävalenz (der diagnostizierten Erkrankungen) im Zeitraum von 2008 bis 2018.

Methodik Die Grundlage der Analysen bilden GKV-Routinedaten. Es wurden Personen mit durchgängiger Versicherung im Analysejahr sowie im 3-jährigen Vorbeobachtungszeitraum eingeschlossen (1,7–2 Mio. Versicherte pro Analysejahr). Erkrankte Personen wurden über relevante ICD-10-Codes (K76.0 und K75.8) identifiziert.

Ergebnisse Im Jahr 2018 wurde bei 4,66 % der Versicherten eine NAFLD-Diagnose gestellt, eine erstmalige Diagnose lag bei 0,87 % vor. Diagnosen einer Fettleberentzündung (NASH) waren mit 0,09 % selten. Im Zeitverlauf zeigt sich eine steigende NAFLD-Prävalenz, wobei sich die Zahl der jährlich erstmals diagnostizierten Patienten kaum verändert hat. Bei Vorliegen von Erkrankungen des metabolischen Syndroms war die Wahrscheinlichkeit einer NAFLD signifikant erhöht.

Schlussfolgerungen Es zeigt sich, dass eine NAFLD im ärztlichen Alltag häufig diagnostiziert wird, auch wenn Daten aus populationsbasierten Untersuchungen eine noch höhere Prävalenz vermuten lassen.

Abstract

Background Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases in Germany. In the long term, there is an increased risk of developing liver cirrhosis and subsequent diseases. Epidemiologic studies on NAFLD prevalence in Germany are scarce. The aim of the study was to assess administrative incidence and prevalence or, more specifically, the number of patients diagnosed with NAFLD in the period from 2008 to 2018.

Methods Analyses are based on administrative data of a large statutory health insurance fund. All individuals who were insured in the year of analysis and in the three-year pre-observation period were included (between 1.7-2 million insured per analysis year). NAFLD-patients were identified using relevant ICD-10 codes (K76.0 und K75.8).

Results In 2018, 4.66 % of insured persons had a NAFLD diagnosis, 0.87 % were diagnosed first-time. Diagnoses of nonalcoholic steatohepatitis (NASH) were comparatively rare (0.09 %). Data show an uptake of NAFLD diagnoses over time. The number of incident cases per year has hardly changed. Patients with diseases of the metabolic syndrome had an increased chance of being diagnosed with NAFLD.

Conclusion It becomes evident that NAFLD is frequently diagnosed in everyday medical practice, although data from population-based studies suggest an even higher prevalence.

Schlüsselwörter

Epidemiologie - Diagnosehäufigkeit - Fettleber - Fettleberentzündung - Inzidenz - Prävalenz

Keywords

epidemiology - frequency of diagnosis - NAFLD - NASH - incidence - prevalence

Publication History

Received: 14 December 2020

Accepted: 24 February 2021

Article published online:
23 March 2021

• Literatur

• 1 Paik JM, Golabi P, Younossi Y. et al. Changes in the Global Burden of Chronic Liver Diseases From 2012 to 2017: The Growing Impact of NAFLD. Hepatol 2020; 72: 1605-1616
• 2 Younossi ZM, Koenig AB, Abdelatif D. et al. Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatol 2016; 64: 73-84
• 3 Weiß J, Rau M, Geier A. Non-alcoholic fatty liver disease: epidemiology, clinical course, investigation, and treatment. Dtsch Arzteblatt Int 2014; 111: 447-452
• 4 Chalasani N, Younossi Z, Lavine JE. et al. The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases. Hepatol 2018; 67: 328-357
• 5 Benedict M, Zhang X. Non-alcoholic fatty liver disease: An expanded review. World J Hepatol 2017; 9: 715-732
• 6 Haldar D, Kern B, Hodson J. et al. Outcomes of liver transplantation for non-alcoholic steatohepatitis: A European Liver Transplant Registry study. J Hepatol 2019; 71: 313-322
• 7 Estes C, Anstee QM, Arias-Loste MT. et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016-2030. J Hepatol 2018; 69: 896-904
• 8 Labenz C, Huber Y, Michel M. et al. Impact of NAFLD on the Incidence of Cardiovascular Diseases in a Primary Care Population in Germany. Dig Dis Sci 2020; 65: 2112-2119
• 9 Kaps L, Labenz C, Galle PR. et al. Non-alcoholic fatty liver disease increases the risk of incident chronic kidney disease. United Eur Gastroenterol J 2020; 8: 942-948
• 10 Huber Y, Labenz C, Michel M. et al. Tumor Incidence in Patients with Non-Alcoholic Fatty Liver Disease. Dtsch Aerzteblatt Int 2020; 117: 719-724
• 11 O’Hara J, Finnegan A, Dhillon H. et al. Cost of non-alcoholic steatohepatitis in Europe and the USA: The GAIN study. JHEP Rep l 2020; 2: 100142
• 12 Harries L, Schrem H, Stahmeyer JT. et al. High resource utilization in liver transplantation-how strongly differ costs between the care sectors and what are the main cost drivers?: a retrospective study. Transpl Int 2017; 30: 621-637
• 13 Ye Q, Zou B, Yeo YH. et al. Global prevalence, incidence, and outcomes of non-obese or lean non-alcoholic fatty liver disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol 2020; 5: 739-752
• 14 Blachier M, Leleu H, Peck-Radosavljevic M. et al. The burden of liver disease in Europe: a review of available epidemiological data. J Hepatol 2013; 58: 593-608
• 15 Volzke H, Robinson D-M, Kleine V. et al. Hepatic steatosis is associated with an increased risk of carotid atherosclerosis. World J Gastroenterol 2005; 11: 1848-1853
• 16 Kühn J-P, Meffert P, Heske C. et al. Prevalence of Fatty Liver Disease and Hepatic Iron Overload in a Northeastern German Population by Using Quantitative MR Imaging. Radiology 2017; 284: 706-716
• 17 Canbay A, Kachru N, Haas JS. et al. Patterns and predictors of mortality and disease progression among patients with non-alcoholic fatty liver disease. Aliment Pharmacol Ther 2020; 52: 1185-1194
• 18 Hammer GP, du Prel J-B, Blettner M. Avoiding bias in observational studies: part 8 in a series of articles on evaluation of scientific publications. Dtsch Arzteblatt Int 2009; 106: 664-668
• 19 Ohlmeier C, Frick J, Prütz F. et al. [Use of routine data from statutory health insurances for federal health monitoring purposes]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2014; 57: 464-472
• 20 Hofmann WP, Buggisch P, Schubert L. et al. The Fatty Liver Assessment in Germany (FLAG) cohort study identifies large heterogeneity in NAFLD care. JHEP Rep I 2020; 2: 100168
• 21 Labenz C, Huber Y, Kalliga E. et al. Predictors of advanced fibrosis in non-cirrhotic non-alcoholic fatty liver disease in Germany. Aliment Pharmacol Ther 2018; 48: 1109-1116
• 22 Labenz C, Prochaska JH, Huber Y. et al. Cardiovascular Risk Categories in Patients With Nonalcoholic Fatty Liver Disease and the Role of Low-Density Lipoprotein Cholesterol. Hepatol Commun 2019; 3: 1472-1481
• 23 Roeb E, Steffen HM, Bantel H. et al. [S2k Guideline non-alcoholic fatty liver disease]. Z Gastroenterol 2015; 53: 668-723
• 24 Pydyn N, Miękus K, Jura J. et al. New therapeutic strategies in nonalcoholic fatty liver disease: a focus on promising drugs for nonalcoholic steatohepatitis. Pharmacol Rep 2020; 72: 1-12
• 25 Tönnies T, Röckl S, Hoyer A. et al. Projected number of people with diagnosed Type 2 diabetes in Germany in 2040. Diabet Med 2019; 36: 1217-1225
• 26 Bauer S, Geiger L, Niggemann R. et al. Präventionsbericht. Berlin: 2020
• 27 Jordan S, von der Lippe E. [Participation in health behaviour change programmes: results of the German Health Interview and Examination Survey for Adults (DEGS1)]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2013; 56: 878-884
• 28 Neubauer S, Zeidler J, Lange A. et al. Prozessorientierter Leitfaden für die Analyse und Nutzung von Routinedaten der Gesetzlichen Krankenversicherung. 1. Auflage. Baden-Baden: Nomos; 2017
• 29 Zeidler J, Braun S. Sekundärdatenanalysen. In: Gesundheitsökonomische Evaluationen. Berlin Heidelberg: Springer; 2012: 243-274
• 30 Klein S, Krupka S, Behrendt S. et al. Weißbuch Adipositas – Versorgungssituation in Deutschland. Berlin: MWV Medizinisch Wissenschaftliche Verlagsgesellschaft; 2016
• 31 Jaunzeme J, Eberhard S, Geyer S. [How „representative“ are SHI (statutory health insurance) data? Demographic and social differences and similarities between an SHI-insured population, the population of Lower Saxony, and that of the Federal Republic of Germany using the example of the AOK in Lower Saxony]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2013; 56: 447-454