Sample Size Considerations in the Design of Cluster Randomized Trials of Combination Hiv Prevention

• Activity Number: 447
• Type: Topic Contributed
• Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Rui Wang*+ and Ravi Goyal and Quanhong Lei and M. Essex and Victor DeGruttola
• Companies: Brigham & Women's Hospital and Harvard School of Public Health and Harvard School of Public Health and Harvard School of Public Health and Harvard School of Public Health
• Keywords: cluster randomized trial ; network models ; design effect ; HIV prevention

Abstract

Cluster randomized trials (CRTs) have been utilized to evaluate the effectiveness of HIV prevention strategies on reducing incidence. We introduce a new agent-based model to simulate the impact of combination prevention strategy, using a Botswana study as an illustration. We construct collections of sexual networks and propagate HIV on them to simulate the disease epidemic. Simulation studies allow us to take into consideration information on sexual network characteristics and coverage levels for different prevention modalities. Increasing level of sexual mixing between intervention and SOC communities reduces the difference in cumulative incidence in the two sets of communities. Fifteen clusters per arm and 500 members per community provides 95% power to detect the projected difference in cumulative incidence between SOC and intervention communities (3.93% and 2.34%) at the end of the study, using a coefficient of variation 0.25. Although available formulas for calculating sample size for CRTs can be derived by assuming an exchangeable correlation structure within clusters, we show that deviations from this assumption do not generally affect the validity of such formulas.