Prognostic models and autoimmune liver diseases

BEST PRACTICE & RESEARCH CLINICAL GASTROENTEROLOGY(2023)

引用 0|浏览3
暂无评分
摘要
Autoimmune liver diseases (AILDs) are complex diseases with unknown causes and immune-mediated pathophysiology. In primary biliary cholangitis (PBC) and autoimmune hepatitis (AIH) disease modifying drugs are available which improve patient quality and quantity of life. In primary sclerosing cholangitis (PSC) no medical therapy is available and the only accepted treatment is liver transplantation (LT). PBC, PSC and AIH possess features that describe the archetype of patients within each disorder. On the other hand, the classical disorders are not homogeneous, and patients within each diagnosis may present with a range of clinical, biochemical, serological, and histological findings.Singularly, they are considered rare diseases, but together, they account for approximately 20% of LTs in Europe and USA. Management of these patients is complex, as AILDs are relatively uncommon in clinical practice with challenges in developing expertise, disease presentation can be sneaky, clinical phenotypes and disease course are heterogeneous. Prognostic models are key tools for clinicians to assess patients' risk and to provide personalized care to patients. Aim of this review is to discuss challenges of the management of AILDs and how the available prognostic models can help. We will discuss the prognostic models developed in AILDs, with a special focus on the prognostic models that can support the clinical management of patients with AILDs: in PBC models based on ursodeoxycholic acid (UDCA) response and markers of liver fibrosis; in PSC several markers including biochemistry, disease stage and radiological semiquantitative markers; and finally in AIH, markers of disease stage and disease activity.
更多
查看译文
关键词
Primary biliary cholangitis PBC,Primary sclerosing cholangitis PSC,Autoimmune hepatitis AIH,Autoimmune liver diseases AILDs,Risk stratification,Prognostic models
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要