Background: Immunological and virological responses to ART are important outcome indicators that are mostly used to evaluate the success of an ART program. A comparative performance between ART providers based on the two outcomes can be useful in optimising resources to underperforming providers and advising quality improvement plans.
Aim: To compare immunological and virological responses of ART for adult HIV positive patients between providers in Tshwane District, Gauteng Province, South Africa.
Methodology: This study was an analytical observational study that retrospectively compared patient treatment outcomes on immunological and virological responses between 16 Antiretroviral Therapy (ART) providers. The analysis compared baseline patients’ status on these two outcomes with their statuses after 6 and12 months on ART. Ordinary logistic regression was used to calculate Standardised Incidence Ratios (SIR), while multilevel model analysis was used to calculate specific provider random effects of poor immunological and virological responses.
Results: After 6 months of treatment, the SIR of poor immunological outcome for all clinics under study, as predicted by the unadjusted logistic regression models was 0.29 (95% CI: 0.27-0.31), but varied from a low of 0.14 (95% CI: 0.00-0.40) to a high of 0.66 (95% CI: 0.13-1.20) between the clinics. Two clinics had a Standardised Incidence Ratio (SIR) of poor immunological response that was significantly below 1 (poor immunological rate below average), while three clinics had an SIR above 1 (poor immunological rate above average) under the unadjusted logistic models. After adjusting for the effects of gender, age, drug combination, religion and present virological status, no clinic had a SIR that was significantly below 1, but two clinics had a SIR that was significantly above 1.
Under the logistic multilevel (MLLR) analysis, the unadjusted model flagged two clinics whose clinic specific effects were below zero (lower rate of poor immunological outcome below that of the total sample) and one clinic whose clinic specific effect was above zero (higher rate of poor immunological outcome below the total sample rate). The adjusted model showed that no clinic had residual effects that were significantly below or above zero. The confidence intervals for MLLR model were found not to be wider than those of the logistic regression (LR) models particularly for clinics with small sample sizes. A number of clinics changed the relative order of their SIR/random effects after case-mix adjustments under both the LR and MLLR modelling.
For poor virological response, both the LRD and MLLR models indicated no clinic specific effects. The predicted poor virological response rate by the case-mix unadjusted LR model was 0.12 (95% CI 0.11 - 0.13). All clinics except one had SIRs that were not significantly different from 1. After adjusting for CD4 count and age, no clinic had an SIR that was significantly different from 1.
Conclusions: Case-mix or patients baseline characteristics explained much of the variation in the Standardised Incidence Ratios (SIR) of poor immunological outcome after 6 months of patient treatment, while provider (clinic) specific effects explained much of the variation after 12 months of treatment. After 6 months of treatment, the results also showed that there were significant differences in the SIR between the clinics before case-mix adjustments, but the differences disappeared after case-mix adjustments. This shows that comparison of treatment outcomes between providers (clinics) can be misleading if no proper adjustment are made for confounding factors.
Differences in the SIRs for poor virological outcome, after 6 months of patient treatment were no longer significant between clinics after taking account of CD4 count and age.