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Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities

Author

Listed:
  • Holly Janes

    (Fred Hutchinson Cancer Research Center)

  • Yifan Zhu

    (Fred Hutchinson Cancer Research Center)

  • Elizabeth R. Brown

    (Fred Hutchinson Cancer Research Center)

Abstract

The evolving HIV prevention landscape poses challenges to the statistical design of future trials of candidate HIV vaccines. Study designs must address the anticipated reduction in HIV incidence due to adding new prevention modalities to the standard prevention package provided to trial participants, and must also accommodate individual choices of participants with regard to the use of these modalities. We explore four potential trial designs that address these challenges, with a focus on accommodating the newest addition to the prevention package-antiretroviral-based oral pre-exposure prophylaxis (PrEP). The designs differ with respect to how individuals who take up oral PrEP at screening are handled. An All-Comers Design enrolls and randomizes all eligible individuals, a Decliners Design enrolls and randomizes only those who decline PrEP at screening, and Single and Multi-Stage Run-In Designs enroll all but randomize only those who decline PrEP or show inadequate adherence to PrEP after one or multiple run-in periods. We compare these designs with respect to required sample sizes, study duration, and resource requirements, using a simulation model that incorporates data on HIV risk and PrEP uptake and adherence among men who have sex with men (MSM) in the Americas. We advocate considering Run-In Designs for some future contexts, and identify their advantages and tradeoffs relative to the other designs. The design concepts apply beyond HIV vaccines to other prevention modalities being developed with the aim to achieve further reductions in HIV incidence.

Suggested Citation

  • Holly Janes & Yifan Zhu & Elizabeth R. Brown, 2020. "Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 468-494, December.
  • Handle: RePEc:spr:stabio:v:12:y:2020:i:3:d:10.1007_s12561-020-09292-1
    DOI: 10.1007/s12561-020-09292-1
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    References listed on IDEAS

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    1. Yifan Zhu & Chongzhi Di & Ying Qing Chen, 2019. "Clustering Functional Data with Application to Electronic Medication Adherence Monitoring in HIV Prevention Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(2), pages 238-261, July.
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    Cited by:

    1. Ying Qing Chen, 2020. "Introduction to Special Issue on ‘Statistical Methods for HIV/AIDS Research’," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 263-266, December.

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