A cohort study found that having two or more metabolic risk factors was associated with greater odds of developing steatosis and fibrosis.
Among the more than 4,000 participants, those with at least two metabolic factors based on the criteria for metabolic fatty liver disease (MAFLD) were more likely to have steatosis (adjusted odds ratio) [aOR] 5.79, 95% CI 3.98-8.43) and fibrosis (aOR 2.5, 95% CI 1.3-4.81), regardless of high BMI and diabetes status, report Chirag Patel, PhD, of Harvard Medical School in Boston, and colleagues in Clinical gastroenterology and hepatology.
The two most important metabolic factors for steatosis and fibrosis are:
- Insulin resistance: aORs of 3.96 for steatosis (95% CI 2.9-5.4) and 2.8 for fibrosis (95% CI 1.63-4.9)
- Greater central obesity: AORs of 5.98 (95% CI 4.54-7.87) and 4.43 (95% CI 2.9-6.7), respectively
“Given that fatty liver disease is still underdiagnosed in real-world settings and the challenge of spreading heuristics requires laboratory testing, our findings highlight the potential for simplification of the MAFLD criteria/definition to identify the highest-throughput groups for screening and risk grading,” the authors wrote. .
They added, “This study highlights factors that dominate the association (eg, visceral obesity, insulin resistance) with steatosis and fibrosis, demonstrating that high prevalence factors in the United States are also the most likely to develop liver disease.”
“We were surprised that waist circumference and insulin resistance played a large, independent role even after considering BMI and diabetes risk for steatosis and fibrosis,” Patel said. MedPage today. “A new definition has been proposed to screen the population for potential risk of liver disease…but it is unclear which risk factors are currently in the definition that play a larger or smaller role in the general US population.”
Patel’s group noted that the MAFLD criteria are intended to improve patient stratification and management, but that the clinical factors used to define it are complex. This study was the first to examine the contribution of different metabolic factors in a nationally representative cohort, using 2017-2018 data from the National Health and Nutrition Examination Survey (NHANES) on 4,369 participants.
Of these, 2732 were healthy adults, 1234 had hepatic steatosis, and 403 had fibrosis. The median age was 44-52, and it was 44-62% of men. Nearly two-thirds of them were white. Most had at least two metabolic factors (55-92%), and 7-40% had diabetes. Exclusion criteria included pregnancy and a history of viral hepatitis, among others.
Patel and his team assessed the relative prognostic significance of seven major metabolic factors—waist circumference, insulin resistance, inflammation, blood pressure, plasma triglycerides, prediabetes, and high-density lipoprotein cholesterol—defined by the MAFLD criteria for steatosis and fibrosis outcomes, using separate models. , which were adjusted for demographics, diabetes mellitus, and overweight status.
Steatosis was defined by an attenuation coefficient set at a higher sensitivity cut-off point (≥290 dB/m), and fibrosis was defined by liver stiffness ≥8.2 kPa. Insulin resistance was measured by the homeostatic model of insulin resistance (HOMA-IR ≥2.5), and greater waist circumference was defined as 102 cm and 90 cm for non-Asian and Asian men and 88 cm and 80 cm for non-Asian and Asian women.
When insulin resistance and greater waist circumference were added to the ‘diabetes and overweight’ model, it improved accuracy in grading steatosis, with an overall NRI improvement of 77% (45% for cases and 31% for non-cases). , with an area under the curve (AUC) of 0.81.
Meanwhile, in the MAFLD model, the presence of at least two metabolic factors, diabetes, and overweight status improved the overall classification accuracy for hepatic steatosis with a total continuous NRI of 65%–82% for cases, but a lower NRI of -17 %, with an AUC of 0.79.
Patel and colleagues acknowledge that long-term data is necessary to confirm their findings.
This study was supported by the National Institutes of Allergy and Infectious Diseases and the National Institutes of Environmental Health Sciences and Optical Health.
Patel did not disclose any conflict of interest.
Co-author reported with support from Boston University School of Medicine, Division of Career Investment, Boston University Institute of Applied Sciences, Doris Duke Charitable Foundation, Gilead Sciences, and the National Institute of Diabetes and Digestive and Kidney Diseases.