Browsing by Author "Reddy, Tarylee."

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The application of multistate Markov models to HIV disease progression.
(2011) Reddy, Tarylee.; Mwambi, Henry Godwell.
Survival analysis is a well developed area which explores time to single event analysis. In some cases, however, such methods may not adequately capture the disease process as the disease progression may involve intermediate events of interest. Multistate models incorporate multiple events or states. This thesis proposes to demystify the theory of multistate models through an application based approach. We present the key components of multistate models, relevant derivations, model diagnostics and techniques for modeling the effect of covariates on transition intensities. The methods that are developed in the thesis are applied to HIV and TB data partly sourced from CAPRISA and the HPP programmes in the University of KwaZulu-Natal. HIV progression is investigated through the application of a five state Markov model with reversible transitions such that state 1: CD4 count 500, state 2: 350 CD4 count < 500, state 3: 200 CD4 count < 350, state 4: CD4 count < 200 and state 5: ARV initiation. The mean sojourn time in each state and transition probabilities are presented as well as the effect of covariates namely age, gender and baseline CD4 count on transition rates. A key finding, consistent with previous research, is that the rate of decline in CD4 count tends to decrease at lower levels of the marker. Further, patients enrolling with a CD4 count less than 350 had a far lower chance of immune recovery and a substantially higher chance of immune deterioration compared to patients with a higher CD4 count. We noted that older patients tend to progress more rapidly through the disease than younger patients.
Cost-effectiveness of initiating antiretroviral therapy at different points in TB treatment in HIV-TB co-infected ambulatory patients in South Africa.
(Wolters Kluwer., 2015) Naidoo, Kogieleum.; Grobler, Anna Christina.; Deghaye, Nicola.; Reddy, Tarylee.; Gengiah, Santhanalakshmi.; Gray, Andrew Lofts.; Abdool Karim, Salim Safurdeen.
Abstract available in pdf.
MDR-TB patients in KwaZulu-Natal, South Africa: cost-effectiveness of 5 models of care.
(Public Library of Science., 2018) Loveday, Marian Patricia.; Wallengren, Kristina.; Reddy, Tarylee.; Besada, Donela.; Brust, James C. M.; Voce, Anna Silvia.; Desai, Harsha.; Ngozo, Jacqueline.; Radebe, Zanele.; Master, Iqbal.; Padayatchi, Nesri.; Daviaud, Emmanuelle.
Abstract available in pdf.
Modelling CD4 count and mortality in a cohort of patients initiated on HAART.
(2018) Mchunu, Nobuhle Nokubonga.; Mwambi, Henry Godwell.; Reddy, Tarylee.; Yende-Zuma, Fortunate Nonhlanhla.
Longitudinally measured data and time-to-event or survival data are often associated in some ways, and are traditionally analyzed separately (Asar et al., 2015). However, separate analyses are not applicable in this case because they may lead to inefficient or biased results. To remedy this, joint models optimally incorporate all available information (longitudinal and survival data) simultaneously (Wulfsohn & Tsiatis, 1997). Furthermore incorporating all sources of data improves the predictive capability of the joint model and lead to more informative inferences for the purpose of decision-making (Seyoum & Temesgen, 2017). The primary goal of this analysis was to determine the effect of repeatedly measured CD4 counts on mortality. The standard time-to-event models require that the time-dependent covariates of interest are external; where the value of the covariate at a future time point is not affected by the occurrence of the event. This requirement would not be fulfilled in this setting, since the repeatedly measured outcome is directly related to the mortality mechanism. Hence, a joint modeling approach was required. We applied the methods developed in this thesis to the CAPRISA AIDS Treatment program (CAT). We also sought to determine if the patients’ baseline BMI (Body mass index), baseline age, gender, baseline viral load, baseline CD8 count, baseline TB status and clinic site, influence the evolution of the CD4 count over time. Various linear mixed models were fitted to the CD4 count, adjusting for repeated measurements, as well as including intercept and slope as random effects. Different types of covariance structures were assessed and the spatial spherical correlation structure was found to be the best fit. The Cox PH model was employed to model mortality. Finally the joint model for longitudinal and time-to-event data was fitted. Out of the 4014 patients, 1457 (36.30%) were male. There were more patients presenting without TB at ART initiation, 3042 (75.78%) compared to those with prevalent TB, 972 (24.22%). Results from the multivariable random effects model showed that the patients gender, age, baseline viral load and baseline CD8 cell count had statistically significant influences on the rate of change in CD4 cell count over time. The un-adjusted and adjusted hazards regression both found CD4:CD8 ratio, viral load, gender and age of patients to be significant predictors of mortality. The result from the joint model in this study indicated that CD4 count change due to HAART and mortality had been influenced jointly by gender, age, baseline viral load, baseline CD8 count, time (in years) , CD4:CD8 ratio and by the interaction effects of time (in years) with TB status, baseline viral load and baseline CD8 cell count. CD4 count proved to be significantly associated with mortality, after adjusting for age, gender and other potential confounders Model diagnostics were performed for validating model assumptions, and our joint model fitted quite well with fairly good diagnostic attributes. The methods that were developed in this thesis were applied to the CAPRISA AIDS Treatment program (CAT) between June 2004 to December 2013.
Nef-mediated down-regulation of CD4 and HLA class I in HIV-1 subtype C infection: association with disease progression and influence of immune pressure.
(Elsevier., 2014) Mann, Jaclyn Kelly.; Chopera, Denis Rutendo.; Omarjee, Saleha.; Kuang, Xiaomei T.; Le, Anh Q.; Anmole, Gursev.; Danroth, Ryan.; Mwimanzi, Philip.; Reddy, Tarylee.; Carlson, Jonathan M.; Radebe, Mopo.; Goulder, Philip Jeremy Renshaw.; Walker, Bruce D.; Abdool Karim, Salim Safurdeen.; Novitsky, Vladimir.; Williamson, Carolyn.; Brockman, Mark A.; Brumme, Zabrina L.; Ndung'u, Peter Thumbi.
Abstract available in pdf.