# Statistical Methods for Evaluating and Guiding Implementation of New HIV Prevention Strategies

> **NIH NIH R56** · FRED HUTCHINSON CANCER CENTER · 2022 · $41,105

## Abstract

PROJECT SUMMARY
The HIV prevention field has advanced dramatically in recent years through the development of antiretroviral-
based prevention strategies such as Treatment-as-Prevention and oral pre-exposure prophylaxis (PrEP). Numer-
ous challenges remain that impede the implementation of these interventions and HIV remains a major global
health problem. We need new preventive interventions to combat the pandemic. The rapid advancements in
the field have complicated the statistical design of efficacy trials of new interventions. For instance, oral PrEP is
now part of the standard HIV prevention package offered to trial participants, which poses challenges in ensur-
ing adequate statistical power. Currently, available statistical methods for guiding the implementation of effective
interventions are inadequate. Considering this complex HIV prevention context, our goal in Aim 1 is to iden-
tify suitable efficacy trial designs for evaluating the next generation of HIV prevention tools. We will consider
crossover designs, sequential randomization designs, active-arm only designs, and non-inferiority designs with
adaptive margins; each of these approaches addresses a key limitation of the prototypical phase 2b/3 trial de-
sign currently in use. Through simulation studies and application to candidate interventions, we will investigate
the relative statistical performance of the designs. We will also work with leaders in the HIV prevention field, to
identify the clinical, ethical, logistical issues and other critical factors that must be considered. We will use these
factors to refine our design comparisons and to identify the trial design that is most appropriate for each setting.
Under Aim 2, we will address specific implementation questions in HIV prevention, through the development of
improved statistical analysis methods. We will develop methods for evaluating sub-population-specific HIV risk
and prevention efficacy, to identify strategies for implementing interventions, and for bridging HIV incidence and
prevention efficacy to new settings or populations. Our approach will rely on fewer assumptions than existing
methods, use a framework that leverages statistical learning to extract information from multiple predictors of risk
and efficacy, and accommodate data from multiple sources. We will use important and relevant datasets in HIV
prevention and simulation studies designed to mimic their structure and content to gauge the performance of the
approaches. Our team members include lead statistical investigators in the major HIV prevention trial networks,
with considerable expertise in statistical methods development and clinical trial design, and established collabo-
rations with other leaders in the clinical and laboratory science of HIV prevention. Our positions and connections
make us uniquely poised to translate the novel methods into practice.

## Key facts

- **NIH application ID:** 10593374
- **Project number:** 6R56AI143418-02
- **Recipient organization:** FRED HUTCHINSON CANCER CENTER
- **Principal Investigator:** Holly Janes
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $41,105
- **Award type:** 6
- **Project period:** 2019-08-15 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10593374

## Citation

> US National Institutes of Health, RePORTER application 10593374, Statistical Methods for Evaluating and Guiding Implementation of New HIV Prevention Strategies (6R56AI143418-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10593374. Licensed CC0.

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