Reducing NAFLD-Screening Time: A Comparative Study of Eight Diagnostic Methods Offering an Alternative to Ultrasound Scans

Filippo Procino; Giovanni Misciagna; Nicola Veronese; Maria G. Caruso; Marisa Chiloiro; Anna M. Cisternino; Maria Notarnicola; Caterina Bonfiglio; Irene Bruno; Claudia Buongiorno; Angelo Campanella; Valentina Deflorio; Isabella Franco; Rocco Guerra; Carla M. Leone; Antonella Mirizzi; Alessandro Nitti; Alberto R. Osella; MICOL GROUP

Disclosures

Liver International. 2019;39(1):187-196. 

In This Article

Materials and Methods

Details on the study population have been published elsewhere. Briefly, the study cohort (2970 subjects) included two different groups of subjects randomly sampled from the electoral rolls of the population of Castellana Grotte (18 728 inhabitants in 2005), a town in southern Italy (Apulia region) and enrolled or followed up between 2005 and 2006. A group of 1697 men and women who participated in the Multicenter Italian Study on Cholelithiasis III (MICOL III) in 1985 and a group of 1273 young participants (30–49 years old) added as panel group of the MICOL III study in 2005.[24,25]

The MICOL study was approved by the Institutional Review Board (Ethics Committee) of the IRCCS De Bellis and written informed consent was obtained from each participant.

A PubMed search was performed for non-invasive NAFLD markers that did not require additional tests beyond those we had already performed as part of routine clinical examinations.

We selected, two scores, FLI and Hepatic Steatosis Index (HIS), that were specifically created and validated to predict the presence of NAFLD and six anthro-m, namely body mass index (BMI), waist circumference (WC), Abdominal Volume Index (AVI), waist-to-height ratio (WHtR), waist/height0.5 (WHT.5R) and Body Roundness Index (BRI), that have been associated with different conditions that can indicate metabolic disorders related to NAFLD.[18,26–32]

Table 1 shows the specific formulas used to predict the NAFLD condition. All the models were constructed retrospectively from the necessary clinical information that had been collected at the time of the US evaluation. All the tests utilized are non-proprietary and can be constructed from routinely collected clinical data.

Anthropometric values were measured by an expert dietitian. WC and Hip circumferences (HC) were measured using a tape meter with 0.1 cm precision. The height (Ht) and weight (W) were collected using a wall stadiometer with 0.1 cm precision and a clinical scale (SECA) with 0.1 kg precision respectively. Blood samples were taken after at least 12 hours of fasting to assess routine biochemical assays according to the standard laboratory methods. NAFLD was detected using an ultrasound scanner Hitachi H21 Vision (Hitachi Medical Corporation, Tokyo, Japan). People affected by active chronic hepatitis (hepatitis B (HBV) or hepatitis C (HCV), acute forms, autoimmune hepatitis, cirrhosis, hemochromatosis or alcoholic liver disease (AFLD) were excluded from this work. Liver steatosis was counted as NAFLD or AFLD, using the standard cut-offs for alcoholic liver disease (>30 g/day for men, and >20 g/day for women).[33] Examination of the visible liver parenchyma was performed with a 3.5 MHz transducer.

All statistical analyses were performed using Stata version 15.1 (StataCorp, 4905 Lakeway Drive College Station, TX). Normally distributed continuous variables were expressed as the mean and standard deviation (SD). Student's t test for unpaired data was used to compare groups when variables were normally distributed. Chi-square test was used to compare differences among categorical variables; a P-value ≤ 0.05 was taken as significant.

To assess the capability of each formula selected to predict liver steatosis, we used the receiver operating characteristic curve (ROC). We also adjusted data for age and sex. Sensitivity and specificity were calculated for each model after identifying the optimal cut-off point for each ROC curve using Youden's index.

To compare the performance of the eight alternative hybrid methods in identifying NAFLD in a large population, we calculated the positive predictive value (PPV) and the negative predictive value (NPV) of each formula, taking into account the real prevalence. By varying the prevalence rates in the formulas to calculate PPV and NPV, we have drawn the graphs about the trend of PPV and NPV vs prevalence, to verify the applicability of the predictive formulas to different prevalence rates.

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