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Universal Index for Cirrhosis (UIC index): The development and validation of a novel index to predict advanced liver disease

Authors Ahmed Z, Ren J, Gonzalez A, Ahmed U, Walayat S, Martin DK, Moole H, Yong S, Koppe S, Dhillon S

Received 22 December 2017

Accepted for publication 30 May 2018

Published 24 October 2018 Volume 2018:10 Pages 133—138

DOI https://doi.org/10.2147/HMER.S160616

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Andrew Yee

Peer reviewer comments 3

Editor who approved publication: Dr Gerry Lake-Bakaar


Zohair Ahmed,1 Jinma Ren,2 Adam Gonzalez,3 Umair Ahmed,4 Saqib Walayat,4 Daniel K Martin,5 Harsha Moole,4 Sherri Yong,6 Sean Koppe,7 Sonu Dhillon5

1Department of Gastroenterology and Hepatology, University of Illinois at Chicago, IL, USA; 2Department of Center for Outcomes Research, University of Illinois College of Medicine, Peoria, IL, USA; 3University of Illinois College of Medicine, Peoria, IL, USA; 4Department of Internal Medicine, University of Illinois College of Medicine, Peoria, IL, USA; 5Department of Gastroenterology and Hepatology, University of Illinois College of Medicine, Peoria, IL, USA; 6Department of Pathology, University of Illinois College of Medicine, Peoria, IL, USA; 7Department of Hepatology, University of Illinois at Chicago, IL, USA

Aim: The purpose of this study was to create and validate a novel serological diagnostic index to predict cirrhosis of all etiologies.
Methods: This was a retrospective observational study of 771 patients, age >18 years, who underwent a liver biopsy. The stage of fibrosis and routine laboratory values were recorded. The data were randomly separated into 2 datasets (training 50% and testing 50%). A stepwise logistic regression model was used to develop the novel index. The area under the curve of receiver operating characteristic (AUROC) was applied to compare the new index to existing ones (Fibro-Q, FIB4, APRI, AAR), which was also validated in the testing dataset.
Results: Variables associated with the presence of cirrhosis were first assessed by univariate analysis then by multivariable analysis, which indicated serum glutamic-oxaloacetic acid transaminase, serum glutamic-pyruvic transaminase, international normalized ratio, albumin, blood urea nitrogen, glucose, platelet count, total protein, age, and race were the independent predictors of cirrhosis (P<0.05). Regression formula for prediction of cirrhosis was generated and a novel index was subsequently created. The diagnostic performance of the novel index for predicting cirrhosis was assessed using the receiver operating characteristic curve. The new index had significantly higher AUROC (0.83, 95% CI: 0.79–0.87) than Fibro-Q (0.80, 95% CI: 0.76–0.85), FIB4 (0.79, 95% CI: 0.74–0.83), APRI (0.74, 95% CI: 0.69–0.78), and AAR (0.72, 95% CI: 0.67–0.78).
Conclusion: The novel index had the highest AUROC curve when compared with current indices and can be applied to all etiologies of chronic liver disease.

Keywords: cirrhosis, liver, fibrosis, diagnosis, screening, NAFLD, HCV, alcohol

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