RESEARCH PAPER
A survival analysis of prognostic determinant factors of time-to-death of HIV/TB co-infected patients under HAART followed-up in a public hospital in Ethiopia
 
More details
Hide details
1
Ethiopian Environment and Forest Research Institute, Ethiopia
 
 
Submission date: 2022-08-03
 
 
Final revision date: 2022-09-22
 
 
Acceptance date: 2022-09-22
 
 
Publication date: 2022-12-08
 
 
HIV & AIDS Review 2023;22(2):110-130
 
KEYWORDS
TOPICS
ABSTRACT
Introduction:
Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) and its’ damage are prevailing at a shocking level in the world, and tuberculosis (TB) also adds to this damage, which make things “Mumps on the Goiter”. In this case, highly active antiretroviral treatment (HAART) plays a great role in reducing the damage, and it is a lifetime treatment to reduce HIV-related mortality and morbidity, and prolong patients’ survival time.

Material and methods:
A retrospective survival study was conducted among 407 HIV-positive TB co-infected patients under HAART to observe the effects of HAART treatment and other covariates for the improvement of patient’s life expectancy. Appropriate survival model was selected using AIC, BIC, and log-likelihood values.

Results:
Out of the total 407 patients, 120 (29.48%) experienced the event of interest. A majority (n = 74, 61.67%) of those who died of HIV/TB co-infection were males, 108 (90%) had pulmonary TB, and 12 (10%) patients suffered from extra-pulmonary TB. For the log-normal AFT model, mari¬tal status, WHO clinical stages, functional status, antiretroviral treatment (ART) regimen, religion, sqrt CD4+, and baseline CD4+ were among significant predictors at a 5% level of significance for the change in patient's lifetime.

Conclusions:
From this study, AFT models presented a better fit compared with Cox regression model. Among AFT models, the log-normal AFT model was selected, and hence, the study showed that prognostic factors, such as WHO clinical stages, functional status, sqrt CD4+ counts, ART regimen, marital status, baseline CD4+ counts, and their interactions with time, were among the significant predictors for the selected model at 5% significance level.

REFERENCES (45)
1.
World Health Organization. Updated Recommendations on HIV Prevention, Infant Diagnosis, Antiretroviral Initiation and Monitoring; 2021.
 
2.
World Health Organization. ‘HIV-Associated Tuberculosis: factsheet’. Retrieved from: https://www.who.int/tb/areas-o...; 2018 (Accessed: 11.12.2021).
 
3.
UNAIDS. Fact Sheet – World Tuberculosis Day 2022. Unaids. Published online 2022:1-2.
 
4.
Federal Democratic Republic of Ethiopia, Ministry of Health. Ethiopia – National Strategic Plan Tuberculosis and Leprosy Control 2013-2020. Moh. 2017; 13 (November 2017): 92.
 
5.
WHO. TB Burden Report 2018. Vol 63; 2018. Available at: https://apps.who.int/iris/hand....
 
6.
Alene KA, Viney K, Moore HC, Wagaw M, Clements ACA. Spatial patterns of tuberculosis and HIV coinfection in Ethiopia. PLoS One 2019; 14: 1-15.
 
7.
Onyango DO, Yuen CM, Cain KP, Ngari F, Masini EO, Borgdorff MW. Reduction of HIV-associated excess mortality by antiretroviral treatment among tuberculosis patients in Kenya. PLoS One 2017; 12: 1-13. doi: 10.1371/journal.pone.0188235.
 
8.
Alemu A, Bitew ZW, Yesuf A, Zerihun B, Getu M. The effect of long-term haart on the incidence of tuberculosis among people living with hiv in addis ababa, ethiopia: A matched nested case–control study. Infect Drug Resist 2021; 14: 5189-5198. doi: 10.2147/IDR.S345080.
 
9.
Tiruneh F, Deyas Y. Effect of highly active antiretroviral treatment on TB incidence among HIV infected children and their clinical profile, retrospective cohort study, South West Ethiopia. Sci Rep 2020; 10: 1-6. doi: 10.1038/s41598-020-78466-0.
 
10.
WHO. WHO publishes new clinical and service delivery recommendations for HIV prevention, treatment and care. Published online 2021. Available at: https://www.who.int/news/item/....
 
11.
Kaplan EL, Meier P. Nonparametric estimation from incomplete samples. J Am Stat Assoc 1958; 53: 457-481.
 
12.
Greenwood M. The errors of sampling of the survivorship Table, vol. 33 of report on the public health and medical subjects. London: His Majesty’s Stationery Office; 1926.
 
13.
Cox DR. Regression Models and Life-Tables. Royal Statistical Society, Series B, 1972; 34: 187-220.
 
14.
Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika 1982; 69: 239-241.
 
15.
Harrell F. The Phglm Procedure. In: SAS Supplemental Library User’s Guide, Version 5. Cary, NC: SAS Institute Inc; 1986.
 
16.
Bengura P, Ndlovu P, Managa MA. Accelerated failure time modelling of tuberculosis predictors in HIV/AIDS patients in Albert Luthuli Municipality of South Africa. Published online 2020. Available at: https://lens.org/004-557-456-5....
 
17.
Sanhueza-Sanzana C, Kerr L, Kendall C. Mortality from AIDS and tuberculosis-HIV coinfection in the Chilean AIDS cohort of 2000-2017. Cad Saude Publica 2021; 37. doi: 10.1590/0102-311X00212920.
 
18.
Tancredi MV, Sakabe S, Waldman EA. Mortality and survival of tuberculosis coinfected patients living with AIDS in São Paulo, Brazil: a 12-year cohort study. BMC Infect Dis 2022; 22: 1-13. doi: 10.1186/s12879-022-07232-6.
 
19.
Camara A, Sow MS, Toure A, et al. Treatment outcome, survival and their risk factors among new tuberculosis patients co-infected with HIV during the Ebola outbreak in Conakry. Epidemiol Public Health 2017; 1–8. doi: 10.1016/j.respe.2017.05.011.
 
20.
Gezae KE. Predictors of accelerated mortality of TB/HIV co-infected patients on ART in Mekelle, Ethiopia: an 8 years retrospective follow-up study. Ann Biostat Biometric Appl 2019; 3: 2-6. doi: 10.33552/abba.2019.03.000572.
 
21.
Deres G, Nigussie ZM, Chanie MG, Worku N. Survival time and associated factors among adults living with HIV after initiation of HAART in South Gondar, Northwest Ethiopia: a retrospective cohort. J Multidiscip Healthc 2021; 14: 1463-1474.
 
22.
Brand ÉM, Rossetto M, Hentges B, et al. Survival and predictors of death in tuberculosis/HIV coinfection cases in Porto Alegre, Brazil: a historical cohort from 2009 to 2013. PLoS Glob Public Health 2021; 1: e0000051. doi:10.1371/journal.pgph.0000051.
 
23.
Wondimu W, Dube L, Kabeta T. Factors affecting survival rates among adult TB/HIV co-infected patients in Mizan Tepi University Teaching Hospital, South West Ethiopia. HIV AIDS (Auckl) 2020; 12: 157-164.
 
24.
Birhan H, Derebe K, Muche S, Melese B. Statistical analysis on determinant factors associated with time to death of HIV/TB co-infected patients under HAART at Debre Tabor Referral Hospital: an application of accelerated failure time-shared frailty models. HIV AIDS (Auckl) 2021; 13: 775-787.
 
25.
de Melo MC, Donalisio MR, Cordeiro RC. Survival of patients with AIDS and co-infection with the tuberculosis bacillus in the South and Southeast regions of Brazil. Cien Saude Colet 2017; 22: 3781-3792.
 
26.
Azeez A, Mutambayi R, Akinwumi O, Ndege J. Survival model analysis of tuberculosis treatment among patients with human immunodeficiency virus coinfection. Int J Mycobacteriol 2019; 8: 244-251.
 
27.
Kosgei RJ, Callens S, Gichangi P, et al. Gender difference in mortality among pulmonary tuberculosis HIV co-infected adults aged 15-49 years in Kenya. PLoS One 2020; 15(12 December): 1-15. doi: 10.1371/journal.pone.0243977.
 
28.
World Health Organization. HIV-Associated Tuberculosis: factsheet, 2022. Available at: https://www.who.int/news-room/....
 
29.
Lelisho ME, Teshale BM, Tareke SA, et al. Modeling survival time to death among TB and HIV co-infected adult patients: an institution-based retrospective cohort study. J Racial Ethn Health Disparities 2022; doi: 10.1007/s40615-022-01348-w.
 
30.
Seyoum D, Degryse JM, Kifle Y, et al. Risk factors for mortality among adult HIV/AIDS patients following antiretroviral therapy in Southwestern Ethiopia: an assessment through survival models. Int J Environ Res Public Health 2017; 14: 296. doi: 0.3390/ ijerph14030296.
 
31.
Erango M, Goshu A, Buta G, Dessiso A. Bayesian joint modelling of survival of HIV/AIDS patients using accelerated failure time data and longitudinal CD4 cell counts. Br J Med Med Res 2017; doi: 10.9734/bjmmr/2017/32123.
 
32.
Kenesa Umeta A, Yermosa SF, Dufera AG. Bayesian parametric modeling of time to tuberculosis co-infection of HIV/AIDS patients under antiretroviral therapy treatment at Jimma University Medical Center, Ethiopia. Sci Rep 2022; 12: 16475; doi: https://doi.org/10.21203/rs.3.....
 
33.
Wondimu W, Dube L, Kabeta T. Time to death and its predictors among adult TB/HIV co-infected patients in Mizan Tepi University Teaching Hospital, South West Ethiopia. medRxiv 2019; doi: https://doi.org/10.1101/190042....
 
34.
Saikia R, Pratim M. A review on accelerated failure time models. Int J Stat Syst 2017; 12: 311-322.
 
35.
Gebremichael SG. Determinants of survival time among HIV-infected patients receiving care at antiretroviral therapy (ART) clinic of a public hospital, Ethiopia. MOJ Public Health 2020; 9: 201-207.
 
36.
Gebremichael SG. AIDS-duration predictors of HIV/AIDS patients on antiretroviral therapy at Debre Berhan referral hospital, north-central Ethiopia. MOJ Public Health 2020; 9: 99-105.
 
37.
Kaplan R, Hermans S, Caldwell J, Jennings K, Bekker LG, Wood R. HIV and TB co-infection in the ART era: CD4 count distributions and TB case fatality in Cape Town. BMC Infect Dis 2018; 18: 356. doi: 10.1186/s12879-018-3256-9.
 
38.
Faruk A. The comparison of proportional hazards and accelerated failure time models in analyzing the first birth interval survival data. J Phys Conf Ser 2018; 974; doi: 10.1088/1742-6596/974/1/012008.
 
39.
Sarfo B, Vanderpuye NA, Addison A, Nyasulu P. HIV case management support service is associated with improved CD4 counts of patients receiving care at the antiretroviral clinic of Pantang Hospital, Ghana. AIDS Res Treat 2017; 2017: 4697473; doi: 10.1155/2017/4697473.
 
40.
Legese H, Degefa H, Gebrewahd A, Gebremedhin H. Utilization of isoniazid prophylaxis therapy and its associated factors among HIV positive clients taking antiretroviral therapy at Fre Semaetat primary hospital, Hawzien districts, Tigrai, Northern Ethiopia. Trop Dis Travel Med Vaccines 2020; 6: 11. doi: 10.1186/s40794-020-00106-2.
 
41.
Abdu M, Ali Y, Anteneh S, et al. Determinant factors for the occurrence of tuberculosis after initiation of antiretroviral treatment among adult patients living with HIV at Dessie Referral Hospital, South Wollo, Northeast Ethiopia, 2020. A case-control study. PLoS One 2021; 16: e0248490. doi:10.1371/journal.pone.0248490.
 
42.
Mardhiah K, Wan-Arfah N, Naing N, Hassan M, Chan HK. Comparison of Cox proportional hazards model, Cox proportional hazards with time-varying coefficients model, and lognormal accelerated failure time model: application in time to event analysis of melioidosis patients. Asian Pac J Trop Med 2022; 15: 128-134. doi: 10.4103/1995-7645.340568.
 
43.
Liu E, Lim K. Using the Weibull accelerated failure time regression model to predict time to health events. bioRxiv 2018; doi: https://doi.org/10.1101/362186.
 
44.
Ogungbola OO, Akomolafe AA, Musa AZ. Accelerated failure time model with application to data on tuberculosis/HIV co-infected patients in Nigeria. Am J Epidemiol Public Health 2018; 2: 21-26.
 
45.
Khamis A, Azmeeza Che Hamat C, Asrul Affendi Abdullah M. Modeling students performance using Cox and parametric accelerated failure time models. Sci Res J 2020; 8: 44-49.
 
eISSN:1732-2707
ISSN:1730-1270
Journals System - logo
Scroll to top