Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/5467
Title: Survival analysis of patients with multidrug-resistant tuberculosis in KwaZulu-Natal, South Africa : a comparison of cox regression and parametric models
Authors: Mbona, Sizwe Vincent
Mwambi, Henry
Ramroop, Shaun 
Chifurira, Retius
Keywords: Cox Model;MDR-TB;Parametric models
Issue Date: 21-Jun-2024
Publisher: Common Ground Research Networks
Source: Mbona, S.V. et al. 2024. Survival analysis of patients with multidrug-resistant tuberculosis in KwaZulu-Natal, South Africa: a comparison of cox regression and parametric models. International Journal of Science, Mathematics and Technology Learning. 31(1): 571-581.
Journal: International Journal of Science, Mathematics and Technology Learning; Vol. 31, Issue 1
Abstract: 
Researchers in medical sciences often prefer the Cox semi-parametric model instead of
parametric models because of its restrictive distributional assumptions, but under certain circumstances,
parametric models estimate the parameters more efficiently and powerful than the Cox model. The
objective of this study was to compare the Cox and parametric models by studying a dataset of patients
diagnosed with multidrug-resistant tuberculosis (MDR-TB). A total of 1 542 patients were included in the
study from four decentralised sites located in rural areas and one centralised hospital in KwaZulu-Natal,
South Africa from 1 July 2008 to 30 July 2012. Out of 1 542 patients with MDR-TB, 886 (57.5%) were
cured and 245 (15.9%) died. According to the AIC, the Lognormal and Weibull regression models were
the best fitting to data and the Cox regression model was the weakest. According to the results from
parametric models, baseline weight of patients had an increased risk of death in both univariate and
multivariate analysis. Patients with ages 31 – 40, 41 - 50 and >50 years at diagnosis had an increased
risk for death in Cox proportional hazards model. In univariate analysis the data strongly supported the
Lognormal regression among parametric models, while in multivariate analysis Weibull and Lognormal
are approximately similar, according to Akaike Information Criterion. Although it seems that there may not
be a single model that is substantially better than others, Lognormal is the most favorable as an
alternative to Cox for identifying risk factors for patients with MDR-TB.
URI: https://hdl.handle.net/10321/5467
ISSN: 2327-7971
2327-915X (Online)
Appears in Collections:Research Publications (Applied Sciences)

Files in This Item:
File Description SizeFormat
IJSMTL Copyright Clearance.docx252.4 kBMicrosoft Word XMLView/Open
Mbona et al_2024.pdf889.54 kBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.