Data mining of routine laboratory tests can predict liver disease progression in Egyptian diabetic patients with hepatitis C virus (G4) infection: a cohort study of 71 806 patients

Eur J Gastroenterol Hepatol. 2018 Feb;30(2):201-206. doi: 10.1097/MEG.0000000000001008.

Abstract

Objectives: Hepatitis C virus (HCV) and diabetes mellitus (DM) are prevalent diseases worldwide, associated with significant morbidity, mortality, and mutual association. The aims of this study were as follows: (i) find the prevalence of DM among 71 806 Egyptian patients with chronic HCV infection and its effect on liver disease progression and (ii) using data mining of routine tests to predict hepatic fibrosis in diabetic patients with HCV infection.

Patients and methods: A retrospective multicentered study included laboratory and histopathological data of 71 806 patients with HCV infection collected by Egyptian National Committee for control of viral hepatitis. Using data mining analysis, we constructed decision tree algorithm to assess predictors of fibrosis progression in diabetic patients with HCV.

Results: Overall, 12 018 (16.8%) patients were diagnosed as having diabetes [6428: fasting blood glucose ≥126 mg/dl (9%) and 5590: fasting blood glucose ≥110-126 mg/dl (7.8%)]. DM was significantly associated with advanced age, high BMI and α-fetoprotein (AFP), and low platelets and serum albumin (P≤0.001). Advanced liver fibrosis (F3-F4) was significantly correlated with DM (P≤0.001) irrespective of age. Of 16 attributes, decision tree model for fibrosis showed AFP was most decisive with cutoff of 5.25 ng/ml as starting point of fibrosis. AFP level greater than cutoff in patients was the first important splitting attribute; age and platelet count were second important splitting attributes.

Conclusion: (i) Chronic HCV is significantly associated with DM (16.8%). (ii) Advanced age, high BMI and AFP, low platelets count and albumin show significant association with DM in HCV. (iii) AFP cutoff of 5.25 is a starting point of fibrosis development and integrated into mathematical model to predict development of liver fibrosis in diabetics with HCV (G4) infection.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Age Factors
  • Algorithms
  • Body Mass Index
  • Clinical Laboratory Techniques
  • Comorbidity
  • Data Mining*
  • Decision Trees
  • Diabetes Mellitus / blood
  • Diabetes Mellitus / epidemiology*
  • Disease Progression
  • Egypt / epidemiology
  • Female
  • Hepatitis C, Chronic / complications
  • Hepatitis C, Chronic / epidemiology*
  • Humans
  • Liver Cirrhosis / blood
  • Liver Cirrhosis / epidemiology*
  • Liver Cirrhosis / virology
  • Male
  • Middle Aged
  • Platelet Count
  • Retrospective Studies
  • Risk Factors
  • Serum Albumin / metabolism
  • alpha-Fetoproteins / metabolism*

Substances

  • AFP protein, human
  • Serum Albumin
  • alpha-Fetoproteins