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A Stepwise Algorithmic Approach and External Validation Study for Noninvasive Prediction of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease.

Publication ,  Journal Article
Kosick, HM-K; Keyrouz, A; Adeyi, O; Sebastiani, G; Patel, K
Published in: Dig Dis Sci
November 2021

BACKGROUND AND AIMS: Advanced F3-4 fibrosis predicts liver-related mortality in nonalcoholic fatty liver disease (NAFLD). Noninvasive tests, designed to rule in/out advanced fibrosis, are limited by indeterminates, necessitating biopsy. We aimed to determine whether stepwise combinations of noninvasive serum-based tests and elastography (VCTE) could predict F3-4, reduce indeterminates, and decrease liver biopsies. METHODS AND RESULTS: Five hundred forty-one biopsy-proven NAFLD cases were identified between 2010 and 2018 from two Canadian centers. Characteristics of training (n = 407)/validation (n = 134) cohorts included: males 54%/59%; mean age 48.5/52.5 years; mean body mass index 32.3/33.6 kg/m2; diabetes mellitus 30%/34%; and F3-4 48%/43%. For training/validation cohorts, area under the receiver operating curve (AUROC) for FIB-4, AST-platelet ratio index (APRI), NAFLD fibrosis score (NFS), BARD score, and AST/ALT ratio ranged from 0.70 to 0.83/0.68 to 0.81, with indeterminates 25-39%/34-45%, for F3-4. In the training cohort, parallel FIB-4 + NFS had good accuracy (AUROC = 0.81) but was limited by 38% indeterminates and 16% misclassified. Sequential FIB-4 → NFS reduced indeterminates to 10%, and FIB-4 → VCTE to 0%, misclassified 20-22%, while maintaining high specificity (0.88-0.92) and accuracy (AUROC 0.75-0.78) for combined cohorts. Liver biopsy could have been avoided in 27-29% of patients using sequential algorithms. CONCLUSIONS: Sequential FIB-4 ➔ NFS/VCTE predicts F3-4 with high specificity and good accuracy, while reducing indeterminates and need for biopsy. Parallel algorithms are limited by high indeterminates. Sequential FIB-4 ➔ NFS had similar accuracy to VCTE-containing algorithms. Validation in low-prevalence cohorts may allow for potential use in community or resource-limited areas for risk stratification.

Duke Scholars

Published In

Dig Dis Sci

DOI

EISSN

1573-2568

Publication Date

November 2021

Volume

66

Issue

11

Start / End Page

4046 / 4057

Location

United States

Related Subject Headings

  • Risk Factors
  • Retrospective Studies
  • Reproducibility of Results
  • Polydactyly
  • Non-alcoholic Fatty Liver Disease
  • Middle Aged
  • Male
  • Liver Diseases
  • Humans
  • Gastroenterology & Hepatology
 

Citation

APA
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ICMJE
MLA
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Kosick, H.-K., Keyrouz, A., Adeyi, O., Sebastiani, G., & Patel, K. (2021). A Stepwise Algorithmic Approach and External Validation Study for Noninvasive Prediction of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease. Dig Dis Sci, 66(11), 4046–4057. https://doi.org/10.1007/s10620-020-06748-8
Kosick, Heather Mary-Kathleen, Aline Keyrouz, Oyedele Adeyi, Giada Sebastiani, and Keyur Patel. “A Stepwise Algorithmic Approach and External Validation Study for Noninvasive Prediction of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease.Dig Dis Sci 66, no. 11 (November 2021): 4046–57. https://doi.org/10.1007/s10620-020-06748-8.
Kosick, Heather Mary-Kathleen, et al. “A Stepwise Algorithmic Approach and External Validation Study for Noninvasive Prediction of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease.Dig Dis Sci, vol. 66, no. 11, Nov. 2021, pp. 4046–57. Pubmed, doi:10.1007/s10620-020-06748-8.
Kosick HM-K, Keyrouz A, Adeyi O, Sebastiani G, Patel K. A Stepwise Algorithmic Approach and External Validation Study for Noninvasive Prediction of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease. Dig Dis Sci. 2021 Nov;66(11):4046–4057.
Journal cover image

Published In

Dig Dis Sci

DOI

EISSN

1573-2568

Publication Date

November 2021

Volume

66

Issue

11

Start / End Page

4046 / 4057

Location

United States

Related Subject Headings

  • Risk Factors
  • Retrospective Studies
  • Reproducibility of Results
  • Polydactyly
  • Non-alcoholic Fatty Liver Disease
  • Middle Aged
  • Male
  • Liver Diseases
  • Humans
  • Gastroenterology & Hepatology