Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter July 12, 2019

Crossover and Repeated Randomization in Event Driven Trials for HIV Prevention: Addressing the Impact of Heterogeneity in Risk in the Trial Design

  • Clara P. Domínguez Islas ORCID logo EMAIL logo and Elizabeth R. Brown

Abstract

The availability of effective Pre-Exposure Prophylaxis (PrEP) for HIV introduces new challenges for testing novel on-demand, user-controlled HIV prevention products, including lower placebo arm incidence and increased between-participant variability in HIV risk. In this paper, we discuss how low HIV incidence may result in longer trials in which the variability in participants' risk may impact the estimate of risk reduction. We introduce a measure of per-exposure efficacy that may be more relevant than the population level reduction in incidence for on demand products and explore alternatives to the parallel arm design that could target better this parameter of interest: the crossover and the re-randomization designs. We propose three different ways in which crossover and re-randomization of intervention assignments could be implemented in event-driven trials. We evaluate the performance of these designs through a simulation study, finding that they allow for better estimation and higher power than the traditional event-driven parallel arm design. We conclude by discussing future work, practical challenges and ethical considerations that need to be addressed to take these designs closer to implementation.

Acknowledgements

The authors would like to thank Dr. Holly Janes for her insightful comments and the helpful discussions. This work was supported by a grant from the National Institutes of Health (UM1AI068615).

References

Auvert, B., R. Sitta, K. Zarca, S. G. Mahiane, C. Pretorius, and P. Lissouba. 2011. “The Effect of Heterogeneity on HIV Prevention Trials.” Clinical Trials 8: 144–54.10.1177/1740774511398923Search in Google Scholar

Buyze, J., and E. Goetghebeur. 2013. “Crossover Studies with Survival Outcomes.” Statistical Methods in Medical Research 22: 612–29.10.1177/0962280211402258Search in Google Scholar PubMed

Coley, R. Y., and E. R. Brown. 2016. “Estimating Effectiveness in HIV Prevention Trials with a Bayesian Hierarchical Compound Poisson Frailty Model.” Statistics in Medicine 35: 2609–34.10.1002/sim.6884Search in Google Scholar PubMed

Dimitrov, D., D. Donnell, and E. R. Brown. 2015. “High incidence is not High Exposure: What Proportion of Prevention Trial Participants are Exposed to HIV?” PloS One 10; e0115528.10.1371/journal.pone.0115528Search in Google Scholar

España, G., C. Hogea, A. Guignard, A. Quirine, A. C. Morrison, D. L. Smith, T. W. Scott, A. Schmidt, and T. A. Perkins. 2019. “Biased Efficacy Estimates in Phase-III Dengue Vaccine Trials Due to Heterogeneous Exposure and Differential Detectability of Primary Infections Across Trial Arms.” PloS One 14: e0210041.10.1371/journal.pone.0210041Search in Google Scholar

George, S. L., and M. Desu. 1974. “Planning the Size and Duration of a Clinical Trial Studying the Time to Some Critical Event.” Journal of Clinical Epidemiology 27: 15–24.10.1016/0021-9681(74)90004-6Search in Google Scholar

Hardnett, F. P., and C. E. Rose. 2015. “Measuring the Potential Role of Frailty in Apparent Declining Efficacy of HIV Interventions.” HIV Clinical Trials 16: 219–27.10.1080/15284336.2015.1123944Search in Google Scholar PubMed PubMed Central

Hernán, M. A. 2010. “The Hazards of Hazard Ratios.” Epidemiology 21: 13–15.10.1097/EDE.0b013e3181c1ea43Search in Google Scholar PubMed PubMed Central

Morris, T. P., I. R. White, and M. J. Crowther. 2019. “Using Simulation Studies to Evaluate Statistical Methods.” Statistics in Medicine 38: 2074–02.10.1002/sim.8086Search in Google Scholar PubMed PubMed Central

Nason, M., and D. Follmann. 2010. “Design and Analysis of Crossover Trials for Absorbing Binary Endpoints.” Biometrics 66: 958–65.10.1111/j.1541-0420.2009.01358.xSearch in Google Scholar PubMed

O’Hagan, J. J., M. A. Hernán, R. P. Walensky, and M. Lipsitch. 2012. “Apparent Declining Efficacy in Randomized Trials: Examples of the Thai RV144 HIV Vaccine and South African CAPRISA 004 Microbicide Trials.” AIDS 26: 123–26.10.1097/QAD.0b013e32834e1ce7Search in Google Scholar PubMed PubMed Central

O’Hagan, J. J., M. Lipsitch, and M. A. Hernán. 2014. “Estimating the Per-Exposure Effect of Infectious Disease Interventions.” Epidemiology 25: 134–38.10.1097/EDE.0000000000000003Search in Google Scholar PubMed PubMed Central

Patel, P., C. B. Borkowf, J. T. Brooks, A. Lasry, A. Lansky, and J. Mermin. 2014. “Estimating Per-Act HIV Transmission Risk: A Systematic Review.” AIDS 28: 1509–19.10.1097/QAD.0000000000000298Search in Google Scholar PubMed PubMed Central

Romero-Severson, E. O., S. J. Alam, E. M. Volz, and J. S. Koopman. 2012. “Heterogeneity in Number and Type of Sexual Contacts in a Gay Urban Cohort.” Statistical Communications in Infectious Diseases 4 (1). Retrieved June 20, 2019, from doi: 10.1515/1948-4690.1042.10.1515/1948-4690.1042Search in Google Scholar PubMed PubMed Central

Zhang, J., and E. R. Brown. 2014. “Estimating the Effectiveness in HIV Prevention Trials by Incorporating the Exposure Process: Application to HPTN 035 Data.” Biometrics 70: 742–50.10.1111/biom.12183Search in Google Scholar PubMed PubMed Central

Received: 2019-03-05
Revised: 2019-06-14
Accepted: 2019-06-19
Published Online: 2019-07-12

© 2019 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 30.9.2023 from https://www.degruyter.com/document/doi/10.1515/scid-2019-0009/html
Scroll to top button