Abstract and Introduction
Abstract
Background: Patients with nonalcoholic fatty liver disease (NAFLD) with type 2 diabetes (T2D) or other components of metabolic syndrome are at high risk for disease progression. We proposed an algorithm to identify high-risk NAFLD patients in clinical practice using noninvasive tests (NITs).
Methods: Evidence about risk stratification of NAFLD using validated NITs was reviewed by a panel of NASH Experts. Using the most recent evidence regarding the performance of NITs and their application in clinical practice were used to develop an easy-to-use algorithm for risk stratification of NAFLD patients seen in primary care, endocrinology and gastroenterology practices.
Results: The proposed algorithm uses a three-step process to identify NAFLD patients who are potentially at high risk for adverse outcomes. The first step is to use clinical data to identify most patients who are at risk for having potentially progressive NAFLD (e.g. having T2D or multiple components of metabolic syndrome). The second step is to calculate the FIB-4 score as a NIT that can further risk stratifying individuals who are at low risk for progressive liver disease and can be managed by their primary healthcare providers to manage their cardiometabolic comorbidities. The third step is to use second-line NITs (transient elastography or enhanced liver fibrosis tests) to identify those who at high risk for progressive liver disease and should be considered for specially care by providers with NASH expertise.
Conclusions: The use of this simple clinical algorithm can identify and assist in managing patients with NAFLD at high risk for adverse outcomes.
Introduction
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in the United States.[1–6] NAFLD is driven by metabolic abnormalities including insulin resistance.[7,8] The progressive form of NAFLD or nonalcoholic steatohepatitis (NASH) has the potential to cause significant hepatic fibrosis which is an important predictor of adverse outcomes.[8–16] Although, only about 15%–20% of patients with NASH will develop progressive liver disease, all patients with NAFLD and NASH remain at high risk for cardiovascular disease and other complications of metabolic syndrome requiring careful monitoring and management.[17] In addition to adverse clinical outcomes, NASH is also associated with impairment of patient-reported outcomes (PROs) such as health-related quality of life (HRQL). In this context, impairments of these PROs can worsen with more advanced liver disease as well as the presence of nonhepatic co-morbidities.[18–21] Finally, NASH is associated with a significant economic burden which worsens with more advanced liver disease.[22–27]
Although a very large proportion of the general population is affected by NAFLD, a smaller proportion are at risk for adverse outcomes. Identifying these individuals or so called 'high-risk NAFLD' from a very large pool of NAFLD patients in the general population can be challenging and screening the general population for just NAFLD is not plausible or cost-effective. However, identifying those 'high-risk NAFLD' patients is clinically relevant and potentially cost-effective[24] but the use of liver biopsy is not feasible in screening or a case-finding programme for NAFLD. To address this issue, several noninvasive tests (NITs) have been developed and validated which can primarily estimate the stage of liver disease as an important indicator of prognosis.[28] In this context, algorithms are being developed to use these NITs in real-world clinical practices to help identify patients not only with NAFLD but who are at high risk for adverse outcomes and link them to care.[17,29]
In order to explore this opportunity, a group of NASH experts came together to review the evidence regarding the disease burden of NAFLD, assess the performance of diagnostic/prognostic NITs and evaluate the use of current algorithms to risk stratify patients with NAFLD (Figure 1).[17,29–32] The primary goal was to incorporate validated NITs in a simple, easy to use algorithm to identify NAFLD patients at 'high risk' for having NAFLD and then risk stratifying those within this group who are at highest risk (those with significant fibrosis, F2 or greater) for adverse outcomes and linking these patients to a care pathway. A case scenario is presented to assist practitioners in their decision-making when working with patients who present with risk factors for NAFLD incorporating the utilisation of the algorithm. (Case Presentation Appendix A).
Figure 1.
Screening criteria for and stratification of patients with high risk NAFLD using non invasive tests.
Aliment Pharmacol Ther. 2023;57(3):304-312. © 2023 Blackwell Publishing
