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 Vol 14: Predicting the Outcomes of Combination Therapy in Patients With Chronic Hepatitis C Using Artificial Neural Network.


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This article is from Hepatitis Monthly, volume 14.AbstractBackground:: Treatment with Peginterferon Alpha-2b plus Ribavirin is the current standard therapy for chronic hepatitis C CHC. However, many host related and viral parameters are associated with different outcomes of combination therapy. Objectives:: The aim of this study was to develop an artificial neural network ANN model to predetermine individual responses to therapy based on patient’s demographics and laboratory data. Patients and Methods:: This case-control study was conducted in Tehran, Iran, on 139 patients divided into sustained virologic response SVR n = 50, relapse n = 50 and non-response n = 39 groups according to their response to combination therapy for 48 weeks. The ANN was trained 300 times epochs using clinical data. To test the ANN performance, the part of data that was selected randomly and not used in training process was entered to the ANN and the outputs were compared with real data. Results:: Hemoglobin P 0.001, cholesterol P = 0.001 and IL-28b genotype P = 0.002 values had significant differences between the three groups. Significant predictive factors for each group were hemoglobin for SVR OR: 1.517; 95% CI: 1.233-1.868; P 0.001, IL-28b genotype for relapse OR: 0.577; 95% CI: 0.339-0.981; P = 0.041 and hemoglobin OR: 0.824; 95% CI: 0.693-0.980; P = 0.017 and IL-28b genotype OR: 2.584; 95% CI: 1.430-4.668;P = 0.001 for non-response. The accuracy of ANN to predict SVR, relapse and non-response were 93%, 90%, and 90%, respectively. Conclusions:: Using baseline laboratory data and host characteristics, ANN has been shown as an accurate model to predict treatment outcome, which can lead to appropriate decision making and decrease the frequency of ineffective treatment in patients with chronic hepatitis C virus HCV infection.



Autor: Sargolzaee Aval, Forough; Behnaz, Nazanin; Raoufy, Mohamad Reza; Alavian, Seyed Moayed

Fuente: https://archive.org/







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