Comparison of non-invasive fibrosis scores to predict increased liver stiffness in the general population with unknown liver disease: Searching for the primary physician's best friend

The association between liver fibrosis score and incident dementia: A nationwide retrospective cohort study

BACKGROUND

We assessed the relationship of liver fibrosis score with incident dementia in a large, national sample.

METHODS

For this retrospective cohort study, data of dementia-free individuals aged 40-69 years were derived from electronic records of the largest healthcare provider in Israel. The association between liver fibrosis score (FIB-4), assessed from routine laboratory measurements, and incident dementia was explored through multivariate cox regression models.

RESULTS

Of the total sample (N = 826,578, mean age 55 ± 8 years at baseline), 636,967 (77%) had no fibrosis, 180,114 (21.8%) had inconclusive fibrosis status and 9497 (1.2%) had high risk for advanced fibrosis. Over a median follow-up of 17 years, 41,089 dementia cases were recorded. Inconclusive liver fibrosis and advanced fibrosis were associated with increased dementia risk (HR = 1.09, 95%CI: 1.07-1.11 and HR = 1.18, 95%CI: 1.10-1.27, respectively). This association remained robust through seven sensitivity analyses.

CONCLUSIONS

Liver fibrosis assessed through a serum-based algorithm may serve as a risk factor for dementia in the general population.

HIGHLIGHTS

Liver fibrosis may predict dementia diagnosis in the general population. Inconclusive liver fibrosis was associated with 9% increased dementia risk. Advanced liver fibrosis was associated with 18% increased dementia risk. Findings remained robust in sensitivity analyses and after adjustments.

Algorithms for Early Detection of Silent Liver Fibrosis in the Primary Care Setting

More than one-third of the adult world population has steatotic liver disease (SLD), with a few percent of individuals developing cirrhosis after decades of silent liver fibrosis accumulation. Lack of systematic early detection causes most patients to be diagnosed late, after decompensation, when treatment has limited effect and survival is poor. Unfortunately, no isolated screening test in primary care can sufficiently predict advanced fibrosis from SLD. Recent efforts, therefore, combine several parameters into screening algorithms, to increase diagnostic accuracy. Besides patient selection, for example, by specific characteristics, algorithms include nonpatented or patented blood tests and liver stiffness measurements using elastography-based techniques. Algorithms can be composed as a set of sequential tests, as recommended by most guidelines on primary care pathways. Future use of algorithms that are easy to interpret, cheap, and semiautomatic will improve the management of patients with SLD, to the benefit of global health care systems.