# Expanding a pragmatic randomized trial to assess mailed self-sample HPV testing to increase cervical cancer screening participation among Asian immigrant women in a safety net health system

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2022 · $383,065

## Abstract

SUMMARY
Clinic-based screening for cervical cancer has dramatically reduced the incidence of this disease in the U.S. and
other countries with widespread screening programs. However, almost 20% of U.S. women remain at high risk
for cervical cancer due to non- and under-participation in screening. Testing self-collected cervicovaginal
samples for high-risk human papillomavirus (HR-HPV) is known to be an effective strategy for addressing
barriers to clinic-based screening in global settings. However, there are limited data on its effectiveness and
implementation in U.S. health systems, particularly in safety net health systems that serve socioeconomically
disadvantaged minority populations who carry the highest burden of cervical cancer. In the context of safety net
health systems, pairing mailed self-sample HPV testing with patient navigation, an evidence-based outreach
intervention, may have a synergistic effect for increasing screening participation among underscreened women.
The Prospective Evaluation of Self-Testing to Increase Screening (PRESTIS) trial is the first trial to evaluate
mailed self-sample HPV testing in U.S. safety net health settings. The patient population of the safety net health
system where the PRESTIS trial is embedded is predominantly Hispanic and non-Hispanic Black. Reflecting this
demographic composition and logistical constraints of implementing the trial, eligibility is currently limited to
patients who speak English or Spanish. Asian/Asian American women who speak English currently comprise a
small proportion of trial participants (4%). Furthermore, Asian/Asian American women who speak languages
other than English (particularly Vietnamese, the primary language of 68% of Asian patients) are currently
ineligible for the trial. The small number of Asian/Asian American patients in the trial is problematic as it precludes
their inclusion in subgroup analyses and limits the generalizeability of trial findings. The inclusion of Asian/Asian
American women in self-sampling trials is critical given that cervical cancer screening participation is low among
Asian/Asian American women and certain Asian subpopulations, notably Vietnamese women, have higher
cervical cancer incidence compared to women of other race/ethnicities. With the proposed Administrative
Supplement, we will expand the PRESTIS trial by adapting patient education materials and navigation strategies
to broaden the trial’s population and recruit Asian/Asian American women who are not up-to-date with cervical
cancer screening. In doing so, we will ensure that the PRESTIS trial is powered to rigorously assess and compare
screening participation across racial/ethnic and linguistic subpopulations inclusive of Asian/Asian American
women. We will also assess acceptability and experiences with self-sampling among Asian/Asian American
women, as well as barriers and facilitators to clinical follow-up among Asian/Asian American women who test
positive for HR-HPV.

## Key facts

- **NIH application ID:** 10675374
- **Project number:** 3R01MD013715-04S2
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Jane R Montealegre
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $383,065
- **Award type:** 3
- **Project period:** 2019-04-16 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10675374

## Citation

> US National Institutes of Health, RePORTER application 10675374, Expanding a pragmatic randomized trial to assess mailed self-sample HPV testing to increase cervical cancer screening participation among Asian immigrant women in a safety net health system (3R01MD013715-04S2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10675374. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*