Non-alcoholic fatty liver disease (NAFLD), a result of excess fat buildup in the liver, is one of the most common causes of liver disease in the US. NAFLD, commonly referred to as a “silent” disease, can be difficult to diagnose early as patients rarely experience any symptoms in the earlier stages. If left untreated, the scarring (fibrosis) becomes more severe, leading to a more advanced liver disease known as non-alcoholic steatohepatitis (NASH). As such, most diagnostic tests, such as liver biopsy and the Fibrosis-4 (FIB-4) Index for Liver Fibrosis, that are available for the diagnosis of NAFLD consider liver fibrosis to be a key criterion and are therefore more useful for the diagnosis of the more advanced cases of NAFLD/NASH. However, since NAFLD/NASH is easier to treat/reverse in the earlier stages of disease progression, efforts to improve early diagnosis and treatment in the primary care population are highly necessary. One potential solution that can aid in the quest for improving early diagnosis of liver disease is the steatosis-associated fibrosis estimator (SAFE) algorithm, which was developed by researchers from Stanford University School of Medicine to detect clinically significant fibrosis in patients with NAFLD.  

As most patients with NAFLD are typically found in the primary care setting, the SAFE algorithm was developed with the intention of improving primary care decision-making and triaging. A score of <0 signifies that a patient is at low risk for liver fibrosis, whereas a score between zero and 99 denotes an intermediate risk of fibrosis, and a score >100 signifies a high risk of fibrosis. The SAFE score is calculated using multivariable logistic regression and machine-learning methods using data such as age, body mass index (BMI), diabetes as a binary variable, aspartate and alanine aminotransferases, total globulin, and platelets from the NASH Clinical Research Network (CRN) observational study. Upon validation, researchers found that the receiver operating characteristic (ROC) curve for the SAFE score model to correctly define the presence of significant fibrosis was 0.79 in the training data set compared to 0.80 in an external validation data set, consisting of participants in the farnesoid X receptor ligand obeticholic acid in the NASH treatment (FLINT) trial. Further validation was performed in a separate cohort of patients with MRE-defined fibrosis.  

Next, the prognostic performance of the SAFE algorithm was investigated using data from the National Health and Nutrition Examination Survey (NHANES) for 2017–2020. In high-risk groups (SAFE >100), researchers observed several abnormalities, including steatosis (68.0%), viral hepatitis (7.0%), and abnormal ferritin levels (12.9%), with FibroScan data showing fibrosis consistent with stage two or higher. Additionally, very few patients with SAFE <0 had liver fibrosis. Overall, when SAFE scores were compared to those of established diagnostic models (FIB-4 and NAFLD fibrosis scores), researchers found that the SAFE scores outperformed the latter set of scores in both the derivation and validation cohorts. Despite the positive performance of the SAFE scores, it should be noted that the model is not yet ready to be applied to the wider primary care population. As a diagnostic or prediction model should be developed in cohorts where it would be applied, it appears further revision of the SAFE score model should be considered as the current model was developed and validated using data from secondary care populations (NASH CRN observational study and FLINT study data).  

With the increasing prevalence and public health impact of NAFLD, there is an urgent need for systematic approaches to lessen its consequences on the healthcare system. Given that most patients with NAFLD/NASH are typically diagnosed in the later stages of the disease, they are also commonly burdened with several comorbidities, including type 2 diabetes (T2D), obesity, cardiovascular disease (CVD), and chronic kidney disease (CKD). Therefore, these patients see a wide variety of healthcare specialists, such as endocrinologists, cardiologists, pharmacists, nutritionists/dietitians, hepatologists, and gastroenterologists, in addition to their primary care physician (PCP). Although such a large multidisciplinary team is required to effectively treat patients with NAFLD/NASH in the later stages of the disease, it is not practical to assume that hepatologists and gastroenterologists can keep up with the increasing volume of NAFLD/NASH patients. Certainly, patients who are diagnosed with severe liver disease should be referred to specialised care to decelerate or halt disease progression, prevent end-stage liver disease (ESLD), or handle complications. However, if the SAFE algorithm can be successfully integrated into primary care, it can not only help improve the identification of at-risk patients and implement proactive measures to enhance liver health but also potentially aid in the reduction of the burden faced by specialists in healthcare systems.  

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