Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART
American Journal of Theoretical and Applied Statistics
Volume 8, Issue 6, November 2019, Pages: 193-202
Received: May 3, 2019; Accepted: Oct. 24, 2019; Published: Oct. 31, 2019
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Author
Getnet Bogale Begashaw, Department of Statistics, College of Natural Science, Wollo University, Dessie, Ethiopia
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Abstract
Human Immunodeficiency Virus (HIV) is a virus that kills CD4 cells. These CD4 cells are white blood cells that fight infection. CD4 count is like a snapshot of how well our immune system is functioning. Studying the way of CD4+ count over time provides an insight to the disease evolution. This study was considering the data of HIV/AIDS patients who were undergoing Antiretroviral Therapy in the ART clinic of Menellik II Referral Hospital, Addis Ababa, Ethiopia, during the period 1st January 2014 to 31st December 2017. For separate survival model log-logistic model is more appropriate for the survival data than other parametric models. Therefore; functional status and regimen class are significant covariates in determining the hazard function patients. Log rank and Wilcoxon tests showed that the significant difference in survival situation among the categorical variables selected for this study sex, marital status, functional status, WHO-clinical stages and regimen class subgroups. But, there was no significant difference in the time-to-event between subgroups of sex, Marital Status and WHO clinical Stage, while, Regimen Class and Functional Status there was a significant difference in the time-to-event between subgroups.
Keywords
FT Model, HAART, HIV/AIDS Data, Log-logistic Model, Survival Data Analysis
To cite this article
Getnet Bogale Begashaw, Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART, American Journal of Theoretical and Applied Statistics. Vol. 8, No. 6, 2019, pp. 193-202. doi: 10.11648/j.ajtas.20190806.11
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Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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