Rapid CD4 decline prior to antiretroviral therapy predicts subsequent failure to reconstitute despite HIV viral suppression.

HIV-1 infection is characterized by loss of CD4T cells, leading to immunodeficiency. Initiation of antiretroviral therapy (ART) results in suppression of the viral load and increased CD4 counts. Both viral and host factors determine CD4 cell responses to ART with approximately 15-30% of individuals having suboptimal increase of CD4T cell count, most commonly due to lack of compliance to ART. A smaller fraction of patients will have immune reconstitution failure and suboptimal CD4 increase despite suppression of HIV replication, and these individuals are at risk for adverse health outcomes. We sought to characterize the factors associated with decreased immunological response among Manitoba's HIV patient population. This retrospective case-control study included HIV patients with immune reconstitution failure despite suppression of HIV replication by ART. The immune reconstitution failure was defined by CD4 cell count increase from baseline of less than 100 CD4 cells/mm3 or lack of increase to above 200 CD4 cells/mm3 within one year of viral load suppression. Age and nadir CD4 cell counts are known risk factors associated with immune reconstitution failure. We chose controls (Patients with immune reconstitution success) of similar age and CD4 nadir cell with cases (Patients with immune reconstitution failure). We explored the potential effects of gender, HLA type, presence of co-infection, ethnicity, ART type, and rate of pre-treatment CD4 decline among cases and controls. Of more than 550 patients followed by our HIV clinic, 42 individuals met our definition of immune reconstitution failure and they were assigned to the cases group. 31 patients, comprising a range of ages and CD4 nadirs similar to those of the cases, were assigned to the control group. Our primary analysis was a regression model, predicting post-ART change in CD4 over time. After controlling for age and nadir CD4 cell counts, the only potential predictor that appears consistently associated with the rate of post-ART rise in CD4 over time in our cohort, regardless of the other variables that we have controlled for, is the rate of decline in CD4 pre-ART initiation. Several factors have been variably correlated with immune reconstitution failure of CD4 T cell count. Age and low CD4 nadir are factors previously shown to correlate with immune reconstitution failure; and we have controlled for them in our study. Another possible predictor is the rate of decline in CD4 pre-ART, which can serve as an additional marker of reconstitution failure and necessitate prioritizing individuals to ART initiation or identification of a subset of individuals that may be targeted for future adjunct strategies to improve immune recovery.

The role of the natural epidemic dynamics and migration in explaining the course of the HIV epidemic in rural Uganda: a modelling study.

BACKGROUND: Human immunodeficiency virus (HIV) prevalence in Uganda fell during the 1990s and has risen since 2000. The changing trends since 2000 may be due to changing risky sexual behaviour, but other factors may also contribute. We explore the possible impact that two factors may have on cohort trends: natural epidemic dynamics and local migration. We simultaneously fit a mathematical model to the contrasting prevalence trends by age/gender in a southwest Ugandan cohort, which has never been done before. METHODS: We fit a model to HIV trends, by age groups and gender, assuming: (i) neither migration nor intentional behaviour change, (ii) migration changes, (iii) intentional behaviour changes and (iv) both change. The model fits were assessed through sum of squares goodness of fits. We also explored the impact of the natural course of the epidemic on average partner acquisition rates, under the condition of no intentional behaviour change over time. RESULTS: Without allowing intentional change in partner acquisition rates, an excellent fit was achievable to prevalence trends by gender. However, all of the contrasting trends by age/gender could not be replicated simultaneously. Adding intentional behaviour change improved the fit to some groups, but not all. Adding both intentional behaviour change and migration further improved the fit. CONCLUSIONS: While some of the increasing HIV prevalence in Uganda since 2000 may be due to increased risky behaviour, some of the observed epidemiologic trends would likely occur without any intentional change in behaviour. Average population-level behaviour can change due to preferential mortality among higher risk takers, without individuals changing their behaviour.