Person:

Hernan, Miguel

Objective: This study compared 12-month CD4+ and viral load outcomes in HIV-infected children and adolescents with virological failure, managed with four treatment switch strategies. Design: This observational study included perinatally HIV-infected (PHIV) children in the Pediatric HIV/AIDS Cohort Study (PHACS) and Pediatric AIDS Clinical Trials (PACTG) Protocol 219C. Methods: Treatment strategies among children with virologic failure were compared: continue failing combination antiretroviral therapy (cART); switch to new cART; switch to drug-sparing regimen; and discontinue all ART. Mean changes in CD4+% and viral load from baseline (time of virologic failure) to 12 months follow-up in each group were evaluated using weighted linear regression models. Results: Virologic failure occurred in 939 out of 2373 (40%) children. At 12 months, children switching to new cART (16%) had a nonsignificant increase in CD4+% from baseline, 0.59 percentage points [95% confidence interval (95% CI) −1.01 to 2.19], not different than those who continued failing cART (71%) (−0.64 percentage points, P = 0.15) or switched to a drug-sparing regimen (5%) (1.40 percentage points, P = 0.64). Children discontinuing all ART (7%) experienced significant CD4+% decline −3.18 percentage points (95% CI −5.25 to −1.11) compared with those initiating new cART (P = 0.04). All treatment strategies except discontinuing ART yielded significant mean decreases in log10VL by 12 months, the new cART group having the largest drop (−1.15 log10VL). Conclusion: In PHIV children with virologic failure, switching to new cART was associated with the best virological response, while stopping all ART resulted in the worst immunologic and virologic outcomes and should be avoided. Drug-sparing regimens and continuing failing regimens may be considered with careful monitoring.

Objective: To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART). Design: Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems. Methods: Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9–12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes. Results: In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9–12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were −5.3 (−18.6 to 7.9) and −31.7 (−52.0 to −11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies. Conclusions: Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.

BACKGROUND: Individual-level simulation models are valuable tools for comparing the impact of clinical or public health interventions on population health and cost outcomes over time. However, a key challenge is ensuring that outcome estimates correctly reflect real-world impacts. Calibration to targets obtained from randomized trials may be insufficient if trials do not exist for populations, time periods, or interventions of interest. Observational data can provide a wider range of calibration targets but requires methods to adjust for treatment-confounder feedback. We propose the use of the parametric g-formula to estimate calibration targets and present a case-study to demonstrate its application.

METHODS: We used the parametric g-formula applied to data from the HIV-CAUSAL Collaboration to estimate calibration targets for 7-y risks of AIDS and/or death (AIDS/death), as defined by the Center for Disease Control and Prevention under 3 treatment initiation strategies. We compared these targets to projections from the Cost-Effectiveness of Preventing AIDS Complications (CEPAC) model for treatment-naïve individuals presenting to care in the following year ranges: 1996 to 1999, 2000 to 2002, or 2003 onwards.

RESULTS: The parametric g-formula estimated a decreased risk of AIDS/death over time and with earlier treatment. The uncalibrated CEPAC model successfully reproduced targets obtained via the g-formula for baseline 1996 to 1999, but over-estimated calibration targets in contemporary populations and failed to reproduce time trends in AIDS/death risk. Calibration to g-formula targets improved CEPAC model fit for contemporary populations.

CONCLUSION: Individual-level simulation models are developed based on best available information about disease processes in one or more populations of interest, but these processes can change over time or between populations. The parametric g-formula provides a method for using observational data to obtain valid calibration targets and enables updating of simulation model inputs when randomized trials are not available.