Immunological and virological response to initial antiretroviral therapy among older people living with HIV in the Canadian Observational Cohort (CANOC)

OBJECTIVES

The aim of this study was to assess the adequacy of immunological recovery and virological suppression in response to antiretroviral therapy (ART) in the growing population of older people living with HIV (PLWH), as treatment regimens become more effective and tolerable.

METHODS

An interprovincial Canadian cohort of treatment-naïve PLWH who initiated ART after 1 January 2000 was used and age assessed in decades. Longitudinal absolute CD4 count response to treatment was modelled using generalized estimating equations. Cumulative incidence functions and proportional hazards models with a competing risk of death were used to estimate time to: (1) CD4 ≥ 200 cells/µL, (2) CD4 ≥ 500 cells/µL, (3) virological suppression (≤ 50 copies/mL), and (4) virological failure (> 200 copies/mL).

RESULTS

In all, 12 489 individuals starting ART between 2000 and 2016 with one or more post-treatment CD4 count or viral load were included in the analysis. Age > 60 years was associated with lower absolute CD4 recovery (adjusted β = -31 cells/µL) compared with age ≤ 30 years when pre-treatment CD4 count and other covariates were accounted for. Older age groups were less likely to achieve a CD4 ≥ 500 cells/µL, with the greatest effect in the > 60 group [adjusted hazard ratio (aHR) = 0.69, 95% confidence interval (CI): 0.57-0.84 vs. age ≤ 30). Older age groups were more likely to achieve viral suppression (age > 60, aHR = 1.20, 95% CI: 1.05-1.37) and less likely to have virological failure (age > 60, aHR = 0.46, 95% CI: 0.3-0.71) compared with those aged ≤ 30 years.

CONCLUSIONS

Older adults have robust virological responses to ART; however, individuals over the age 60 are more likely to experience blunted CD4 recovery.

A superiority of viral load over CD4 cell count when predicting mortality in HIV patients on therapy

Background

CD4 cell count has been identified to be an essential component in monitoring HIV treatment outcome. However, CD4 cell count monitoring sometimes fails to predict virological failure resulting in unnecessary switch of treatment lines which causes drug resistance and limitations of treatment options. This study assesses the use of both viral load (HIV RNA) and CD4 cell count in the monitoring of HIV/AIDS progression.

Methods

Time-homogeneous Markov models were fitted, one on CD4 cell count monitoring and the other on HIV RNA monitoring. Effects of covariates; gender, age, CD4 baseline, HIV RNA baseline and adherence to treatment were assessed for each of the fitted models. Assessment of the fitted models was done using prevalence plots and the likelihood ratio tests. The analysis was done using the “msm” package in R.

Results

Results from the analysis show that viral load monitoring predicts deaths of HIV/AIDS patients better than CD4 cell count monitoring. Assessment of the fitted models shows that viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count.

Conclusion

From this study one can conclude that although patients take more time to achieve a normal CD4 cell count and less time to achieve an undetectable viral load, once the CD4 cell count is normal, mortality risks are reduced. Therefore, both viral load monitoring and CD4 count monitoring can be used to provide useful information which can be used to improve life expectance of patients living with HIV. However, viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count and hence viral load is deemed superior.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-3781-1) contains supplementary material, which is available to authorized users.

Time-homogeneous Markov process for HIV/AIDS progression under a combination treatment therapy: cohort study, South Africa

BACKGROUND

As HIV enters the human body, its main target is the CD4 cell which it turns into a factory that produces millions of other HIV particles. These HIV particles target new CD4 cells resulting in the progression of HIV infection to AIDS. A continuous depletion of CD4 cells results in opportunistic infections, for example tuberculosis (TB). The purpose of this study is to model and describe the progression of HIV/AIDS disease in an individual on antiretroviral therapy (ART) follow up using a continuous time homogeneous Markov process. A cohort of 319 HIV infected patients on ART follow up at a Wellness Clinic in Bela Bela, South Africa is used in this study. Though Markov models based on CD4 cell counts is a common approach in HIV/AIDS modelling, this paper is unique clinically in that tuberculosis (TB) co-infection is included as a covariate.

METHODS

The method partitions the HIV infection period into five CD4-cell count intervals followed by the end points; death, and withdrawal from study. The effectiveness of treatment is analysed by comparing the forward transitions with the backward transitions. The effects of reaction to treatment, TB co-infection, gender and age on the transition rates are also examined. The developed models give very good fit to the data.

RESULTS

The results show that the strongest predictor of transition from a state of CD4 cell count greater than 750 to a state of CD4 between 500 and 750 is a negative reaction to drug therapy. Development of TB during the course of treatment is the greatest predictor of transitions to states of lower CD4 cell count. Transitions from good states to bad states are higher on male patients than their female counterparts. Patients in the cohort spend a greater proportion of their total follow-up time in higher CD4 states.

CONCLUSION

From some of these findings we conclude that there is need to monitor adverse reaction to drugs more frequently, screen HIV/AIDS patients for any signs and symptoms of TB and check for factors that may explain gender differences further.