Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression

Desalegn Petros Kelkile

doi:doi:10.11648/j.sjams.20160405.12

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Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression

Desalegn Petros Kelkile

Published in Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 5)

Received: 4 August 2016 Accepted: 13 August 2016 Published: 13 September 2016

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Abstract

This study has been intended to apply the cox proportional hazard model to review the determinant factors of survival time and discrete time homogeneous semi markov model to predict the clinical progression of AIDS disease by secondary data obtained from the antiretroviral therapy unit of Dilla and Hawassa University Referral Hospitals. Patients were followed for a median of 34 months. Of total sample, 517 (68.4%) were female and 239 (31.6%) were male. In the followed up period, 110 (14.5%) patients died and 646 (85.5%) patients were censored. The cox regression result indicated that the survival time of the HIV patient was significantly connected with adherence level, age, alcohol use, CD4, condom use, functional status, marital status and WHO stage. The outcome of homogenous semi-markov model showed that the survival probability of a patient increased when CD4 count increased. The study is suggested that the above significant variables should be viewed as significant component of the routine clinical care for patients on ART and patients require checking CD4 count in the suitable day as physician arrange to know their disease stage.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 5)
DOI	10.11648/j.sjams.20160405.12
Page(s)	189-201
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), 2016. Published by Science Publishing Group

Keywords

Antiretroviral Therapy, Cox Proportional Hazard Model, Discrete Time Homogeneous Semi-Markov Model, AIDS Progression

References

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[2]	Andinet, W. (2009). Pattern and Determinants of Survival in Adult HIV patients on ART, Ethiopia. Umea International School of Public Health, Umea University.
[3]	Birtukan, T. (2010). Predictors of Early Death in HIV Positive Individuals Enrolled for Chronic HIV Care in Jimma Zone, South Western Ethiopia. Masters Thesis, Addis Abeba University. Addis Abeba.
[4]	Etard, J. F., Ndiaye I, Thierry M, Gueye NF, Gueye PM, Laniece I,Dieng AB, Diouf A, Laurent C, Mboup S, Sow PS, Delaporte E (2006). Mortality and Causes of Death in Adults Receiving Highly Active ART in Senegal. A 7-year cohort study, 20:1181-1189.
[5]	Federal Ministry of Health (2006). AIDS in Ethiopia, Sixth Report, Addis Ababa, Ethiopia, pp. 150.
[6]	Federal Ministry of Health (2008). AIDS in Ethiopia, Report, Addis Ababa, Ethiopia, pp. 180.
[7]	Federal Ministry of Health (2007). Antiretroviral Treatment for Adult and Adolescence. Addis Abeba, Ethiopia.
[8]	Federal Ministry of Health (2010). Antiretroviral Therapy in Ethiopia. Addis Abeba, Ethiopia.
[9]	Giuseppe, D., Amico, G. D., A. Girolamo, J. Janssen, S. Iacobelli, N. Tinari, R. Manca (2007). A Stochastic Model for the HIV/AIDS Dynamic Evolution. Mathematical Problems in Engineering, ART. ID 65636, Vol. 20, pp. 14.
[10]	Isidore, S., S. Mohamadou, M.S. Anne, M. Joris, B. Marleen, (2009). Determinants of Survival in AIDS Patients on ART in a Rural Center in the Far-North Province, Cameron. Journal of Tropical Medicine and International Health. 14 (1): 36 43.
[11]	Lawn, S. D., Myer L, Harling G, Orrell C, Bekker LG, Wood R (2006). Determinants of Mortality and Non-death Losses from an ART service in South Africa: Implications for Program Evaluation. Journal of Clinical Infectious Disease. 43: 770-776.
[12]	Michael, A. T. (2010). Antiretroviral Therapy. MPH, USA.
[13]	Mogiyana, T., D. Mariw and C. Tiana (2009). Mortality and Causes of Death in HIV Positive Patients Receiving Antiretroviral Therapy at Tshepang Clinic in Doctor George Mukhari Hospital. 118 (10).
[14]	Nuredin Ibrahim (2007). Education of Factor Affecting the Chance of Survival/Death Status Among HIV Positive People Under the Antiretroviral Treatment Program: The Case of Adama Referral Hospital, M.Sc. Thesis, Addis Ababa University, Ethiopia.
[15]	Stringer, J.S., Zulu I, Levy J, Stringer EM, Mwango A, Bulterys M, Saag MS, Marlink RG, Mwinga A,Ellerbrock TV, Sinkala M (2006). Rapid Scale-up of ART at Primary Care Sites in Zambia: Feasibility and Early Outcomes. JAMA, 296: 782-793.
[16]	United Nations Program on AIDS (2006). Report on the Global HIV/ AIDS Epidemic. Geneva, 11: 85-97.
[17]	United Nation Program on AIDS (2010). Global Health Report (http:/www.globalhealthre Porting.org/diseaseinfo.25, June, 2011).
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[19]	Zelalem Getahun (2010). Statistical Modelling of HIV/ AIDS Progression and Survival of AIDS Patients. A Case Study of Bahir-Dar, Feleg-Hiwot Referral Hospital. M.Sc. Thesis. Hawassa University, Hawassa, Ethiopia.
[20]	Zhang, X. (2007). HIV/AIDS Relative Survival Analysis. Master’s Thesis Published in Georgia University. USA.

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APA Style

Desalegn Petros Kelkile. (2016). Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression. Science Journal of Applied Mathematics and Statistics, 4(5), 189-201. https://doi.org/10.11648/j.sjams.20160405.12

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ACS Style

Desalegn Petros Kelkile. Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression. Sci. J. Appl. Math. Stat. 2016, 4(5), 189-201. doi: 10.11648/j.sjams.20160405.12

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AMA Style

Desalegn Petros Kelkile. Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression. Sci J Appl Math Stat. 2016;4(5):189-201. doi: 10.11648/j.sjams.20160405.12

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@article{10.11648/j.sjams.20160405.12,
  author = {Desalegn Petros Kelkile},
  title = {Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {5},
  pages = {189-201},
  doi = {10.11648/j.sjams.20160405.12},
  url = {https://doi.org/10.11648/j.sjams.20160405.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160405.12},
  abstract = {This study has been intended to apply the cox proportional hazard model to review the determinant factors of survival time and discrete time homogeneous semi markov model to predict the clinical progression of AIDS disease by secondary data obtained from the antiretroviral therapy unit of Dilla and Hawassa University Referral Hospitals. Patients were followed for a median of 34 months. Of total sample, 517 (68.4%) were female and 239 (31.6%) were male. In the followed up period, 110 (14.5%) patients died and 646 (85.5%) patients were censored. The cox regression result indicated that the survival time of the HIV patient was significantly connected with adherence level, age, alcohol use, CD4, condom use, functional status, marital status and WHO stage. The outcome of homogenous semi-markov model showed that the survival probability of a patient increased when CD4 count increased. The study is suggested that the above significant variables should be viewed as significant component of the routine clinical care for patients on ART and patients require checking CD4 count in the suitable day as physician arrange to know their disease stage.},
 year = {2016}
}

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TY  - JOUR
T1  - Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression
AU  - Desalegn Petros Kelkile
Y1  - 2016/09/13
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160405.12
DO  - 10.11648/j.sjams.20160405.12
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 189
EP  - 201
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160405.12
AB  - This study has been intended to apply the cox proportional hazard model to review the determinant factors of survival time and discrete time homogeneous semi markov model to predict the clinical progression of AIDS disease by secondary data obtained from the antiretroviral therapy unit of Dilla and Hawassa University Referral Hospitals. Patients were followed for a median of 34 months. Of total sample, 517 (68.4%) were female and 239 (31.6%) were male. In the followed up period, 110 (14.5%) patients died and 646 (85.5%) patients were censored. The cox regression result indicated that the survival time of the HIV patient was significantly connected with adherence level, age, alcohol use, CD4, condom use, functional status, marital status and WHO stage. The outcome of homogenous semi-markov model showed that the survival probability of a patient increased when CD4 count increased. The study is suggested that the above significant variables should be viewed as significant component of the routine clinical care for patients on ART and patients require checking CD4 count in the suitable day as physician arrange to know their disease stage.
VL  - 4
IS  - 5
ER  -

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Author Information

Desalegn Petros Kelkile

Department of Statistics, Dilla University, Dilla Town, Ethiopia

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Plain Text BibTeX RIS

APA Style

Desalegn Petros Kelkile. (2016). Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression. Science Journal of Applied Mathematics and Statistics, 4(5), 189-201. https://doi.org/10.11648/j.sjams.20160405.12

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ACS Style

Desalegn Petros Kelkile. Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression. Sci. J. Appl. Math. Stat. 2016, 4(5), 189-201. doi: 10.11648/j.sjams.20160405.12

Copy | Download

AMA Style

Desalegn Petros Kelkile. Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression. Sci J Appl Math Stat. 2016;4(5):189-201. doi: 10.11648/j.sjams.20160405.12

Copy | Download

@article{10.11648/j.sjams.20160405.12,
  author = {Desalegn Petros Kelkile},
  title = {Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {5},
  pages = {189-201},
  doi = {10.11648/j.sjams.20160405.12},
  url = {https://doi.org/10.11648/j.sjams.20160405.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160405.12},
  abstract = {This study has been intended to apply the cox proportional hazard model to review the determinant factors of survival time and discrete time homogeneous semi markov model to predict the clinical progression of AIDS disease by secondary data obtained from the antiretroviral therapy unit of Dilla and Hawassa University Referral Hospitals. Patients were followed for a median of 34 months. Of total sample, 517 (68.4%) were female and 239 (31.6%) were male. In the followed up period, 110 (14.5%) patients died and 646 (85.5%) patients were censored. The cox regression result indicated that the survival time of the HIV patient was significantly connected with adherence level, age, alcohol use, CD4, condom use, functional status, marital status and WHO stage. The outcome of homogenous semi-markov model showed that the survival probability of a patient increased when CD4 count increased. The study is suggested that the above significant variables should be viewed as significant component of the routine clinical care for patients on ART and patients require checking CD4 count in the suitable day as physician arrange to know their disease stage.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Statistical Analysis of Adult HIV/AIDS Patients and Modelling of AIDS Disease Progression
AU  - Desalegn Petros Kelkile
Y1  - 2016/09/13
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160405.12
DO  - 10.11648/j.sjams.20160405.12
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 189
EP  - 201
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160405.12
AB  - This study has been intended to apply the cox proportional hazard model to review the determinant factors of survival time and discrete time homogeneous semi markov model to predict the clinical progression of AIDS disease by secondary data obtained from the antiretroviral therapy unit of Dilla and Hawassa University Referral Hospitals. Patients were followed for a median of 34 months. Of total sample, 517 (68.4%) were female and 239 (31.6%) were male. In the followed up period, 110 (14.5%) patients died and 646 (85.5%) patients were censored. The cox regression result indicated that the survival time of the HIV patient was significantly connected with adherence level, age, alcohol use, CD4, condom use, functional status, marital status and WHO stage. The outcome of homogenous semi-markov model showed that the survival probability of a patient increased when CD4 count increased. The study is suggested that the above significant variables should be viewed as significant component of the routine clinical care for patients on ART and patients require checking CD4 count in the suitable day as physician arrange to know their disease stage.
VL  - 4
IS  - 5
ER  -

Copy | Download