A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C.

A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C. Research Abstract Details 

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A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C. Abstract Text:

Mazen Alsatie,Paul Y Kwo,Joel R Gingerich,Rong Qi,George Eckert,Oscar W Cummings,Thomas F Imperiale,

BACKGROUND: A noninvasive method to identify advanced hepatic fibrosis (AHF) in chronic hepatitis C (CHC) could preclude the need for routine liver biopsy. Recent evidence suggests that obesity may contribute to hepatic fibrosis in hepatitis C virus infection. GOALS: To determine whether clinical variables, including body mass index (BMI), can predict risk of AHF. STUDY: Retrospective review of untreated CHC patients evaluated between 1993 and 2002 without clinical or physical evidence of end-stage liver disease. Liver biopsies were scored for fibrosis, steatosis, and inflammation. Multivariable analysis was used to derive and internally validate a prediction equation. A clinical index was created from the equation by assigning points for each variable. The risk of AHF was measured for each risk category. RESULTS: Two hundred eighty-six satisfied inclusion criteria, of which 86 (30%) had AHF. In the derivation subgroup (N=190), 5 factors were independently associated with AHF: diabetes mellitus, platelets count <150,000, aspartate aminotransferase > or =65 IU/mL, international normalized ratio > or =1.1, and bilirubin > or =0.85 mg/dL. The corresponding risk index contained 3 categories: low-risk (score of 0), intermediate risk (scores of 1 to 3), and high risk (scores of > or =4), in which the respective risks of AHF were 9%, 34%, and 92%. Inclusion of BMI did not improve model performance. CONCLUSIONS: A model for estimating AHF risk in CHC performed well in this population. BMI had no effect on the risk of AHF. If this model can be validated in other patient cohorts, it could preclude the need for liver biopsy in patients with scores of 0 or > or =4.

A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C. Publishing Authors By Initials

M Alsatie,PY Kwo,JR Gingerich,R Qi,G Eckert,OW Cummings,TF Imperiale,

For similar investigative techniques: epidemiologic methods: data collection: health surveys: health status indicators: severity of illness index research abstracts see: investigative techniques: epidemiologic methods: data collection: health surveys: health status indicators: severity of illness index research

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A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Journal of clinical gastroenterology

VOLUME: 41

Page Numbers: 416-21

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ISSN: 0192-0790

DAY: 3

MONTH: Apr

YEAR: 2007

A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C. Information

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LANGUAGE: eng

NlmUniqueID: 7910017

A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C. Keywords Mesh Terms:

KEYWORDS: Severity of Illness Index

MESH TERMS: complications

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Grant and Affiliation Information for A multivariable model of clinical variables predicts advanced fibrosis in chronic hepatitis C.

AFFILIATION: Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana 46202, USA.

Country: United States

AGENCY: United States NIDDK

GRANT: K24 DK002756-07

ACRONYM: DK

MEDLINETA: J Clin Gastroenterol

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