Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART

Getnet Bogale Begashaw

doi:doi:10.11648/j.ajtas.20190806.11

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Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART

Getnet Bogale Begashaw

Published in American Journal of Theoretical and Applied Statistics (Volume 8, Issue 6)

Received: 3 May 2019 Accepted: 24 October 2019 Published: 31 October 2019

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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 1^st January 2014 to 31^st 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.

Published in	American Journal of Theoretical and Applied Statistics (Volume 8, Issue 6)
DOI	10.11648/j.ajtas.20190806.11
Page(s)	193-202
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

FT Model, HAART, HIV/AIDS Data, Log-logistic Model, Survival Data Analysis

References

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APA Style

Getnet Bogale Begashaw. (2019). 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, 8(6), 193-202. https://doi.org/10.11648/j.ajtas.20190806.11

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ACS Style

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. Am. J. Theor. Appl. Stat. 2019, 8(6), 193-202. doi: 10.11648/j.ajtas.20190806.11

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AMA Style

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. Am J Theor Appl Stat. 2019;8(6):193-202. doi: 10.11648/j.ajtas.20190806.11

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@article{10.11648/j.ajtas.20190806.11,
  author = {Getnet Bogale Begashaw},
  title = {Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {8},
  number = {6},
  pages = {193-202},
  doi = {10.11648/j.ajtas.20190806.11},
  url = {https://doi.org/10.11648/j.ajtas.20190806.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20190806.11},
  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.},
 year = {2019}
}

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TY  - JOUR
T1  - Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART
AU  - Getnet Bogale Begashaw
Y1  - 2019/10/31
PY  - 2019
N1  - https://doi.org/10.11648/j.ajtas.20190806.11
DO  - 10.11648/j.ajtas.20190806.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 193
EP  - 202
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20190806.11
AB  - 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.
VL  - 8
IS  - 6
ER  -

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Author Information

Getnet Bogale Begashaw

Department of Statistics, College of Natural Science, Wollo University, Dessie, Ethiopia

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Plain Text BibTeX RIS

APA Style

Getnet Bogale Begashaw. (2019). 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, 8(6), 193-202. https://doi.org/10.11648/j.ajtas.20190806.11

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ACS Style

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. Am. J. Theor. Appl. Stat. 2019, 8(6), 193-202. doi: 10.11648/j.ajtas.20190806.11

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AMA Style

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. Am J Theor Appl Stat. 2019;8(6):193-202. doi: 10.11648/j.ajtas.20190806.11

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@article{10.11648/j.ajtas.20190806.11,
  author = {Getnet Bogale Begashaw},
  title = {Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {8},
  number = {6},
  pages = {193-202},
  doi = {10.11648/j.ajtas.20190806.11},
  url = {https://doi.org/10.11648/j.ajtas.20190806.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20190806.11},
  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.},
 year = {2019}
}

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TY  - JOUR
T1  - Demonstrating the Performance of Accelerated Failure Time Model Over Cox-PH Model of Survival Data Analysis with Application to HIV-Infected Patients Under HAART
AU  - Getnet Bogale Begashaw
Y1  - 2019/10/31
PY  - 2019
N1  - https://doi.org/10.11648/j.ajtas.20190806.11
DO  - 10.11648/j.ajtas.20190806.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 193
EP  - 202
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20190806.11
AB  - 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.
VL  - 8
IS  - 6
ER  -

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