Journal of Gastrointestinal & Digestive System
Open Access

Review Article

Low Serum Alpha-fetoprotein Level an Important Predictor for Therapeutic Outcome in Egyptian Patients with Chronic Hepatitis C: A Data-Mining Analysis

Naglaa Zayed^1*, AbuBakr Awad², Wafaa El-Akel¹, Wahid Doss^1,3, Maissa El-Raziky¹ and Mahasen Mabrouk¹

¹Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Egypt

²Computer Science Department, Faculty of Computers and Information, Cairo University, Egypt

³National Hepatology and Tropical Medicine Institute, Ministry of Health and Population, Cairo, Egypt

*Corresponding Author:

Naglaa Zayed
Kasr Al-Aini Street, Faculty of Medicine
Cairo University, Cairo, Egypt
Tel: +201001460366
E-mail: naglaazayed@yahoo.com

Received date: October 09, 2014; Accepted date: November 12, 2014; Published date: November 18, 2014

Citation: Zayed N, Awad A, El-Akel W, Doss W, El-Raziky M, et al. (2014) Low Serum Alpha-fetoprotein Level an Important Predictor for Therapeutic Outcome in Egyptian Patients with Chronic Hepatitis C: A Data-Mining Analysis . J Gastrointest Dig Syst 4:240. doi:10.4172/2161-069X.1000240

Copyright: ©2014 Zayed N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Background Data mining can build predictive models for the response to antiviral therapy in chronic HCV patients. Objective To develop a prediction model for therapeutic outcome in chronic HCV genotype-4 patients using different decision-trees learning algorithms. Study Design Data of 3719 chronic HCV patients who had received PEG-IFN/RBV therapy at Cairo-Fatemia Hospital, Egypt was retrieved. Factors predictive of SVR were explored using data mining analysis. Weka implementations C4.5, classification and Reduced Error Pruning tree were constructed using 22 attributes from initial patients’ data. Results End of treatment response and estimated SVR were 61.6%, 52.5% respectively. Low median AFP; 2.9 ng/ml was significantly associated with SVR; compared to relapse group 5.06 ng/ml; p value<0.01. AFP was identified as the most decisive variable of initial split by both decision-tree models. Various cutoff levels were related to different probability of SVR. Baseline AFP ≤2.48 ng/ml was associated with 72%SVR while levels ≥ 7.8 ng/ml demonstrated 32%. Other attributes such as age, BMI, ALT, hepatic fibrosis and activity were less decisive in prediction of response. This was further confirmed by univariate logistic regression analysis; p value<0.01. Conclusion Low AFP Levels were significantly related to SVR in an HCV population presumably genotype-4 as demonstrated by data mining.

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