# A Randomized Controlled Trial of Mail-Self Stamped HPV Testing to Increase Cervical Cancer Screening Participation Among Minority/Underserved Women in an Integrated Safety Net Healthcare System

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2022 · $636,719

## Abstract

PROJECT SUMMARY
The implementation of clinic-based Papanicolaou (Pap) test screening for cervical cancer has dramatically
reduced the incidence of this disease in the US and other countries with widespread screening programs.
However, many women remain at high risk for cervical cancer due to their inability or unwillingness to periodically
attend for clinic-based screening. At present, evidence-based, client-directed strategies such as patient
reminders and recalls, patient education, and patient navigation are the basis for many behavioral interventions
to increase screening participation. However, these strategies alone are often unable to resolve many of the
barriers faced by screening non-attendees. Using mailed self-sampling kits to test for high-risk human
papillomavirus (HPV), the virus that causes cervical cancer, may overcome multiple barriers to clinic-based
screening. However, this mailed self-sampling has not been evaluated in safety net health systems in the US
that provide care for a large portion of socioeconomically disadvantaged individuals. We hypothesize that in the
context of a safety net health system, pairing mailed self-sample HPV testing with patient navigation, an outreach
intervention with strong evidence among underserved minority populations, will have a synergistic effect for
increasing screening participation among underscreened women.
We propose to conduct a randomized controlled trial to compare the effectiveness of three outreach interventions
to increase primary screening participation and clinical follow-up among underscreened women ages 30-65
years in a safety net health system. The trial setting is Harris Health System, the third largest publicly-funded
safety net health system in the nation, which serves a predominantly racially/ethnically minority and
socioeconomically disadvantaged population. The three study arms are: 1) telephone recall (control); 2)
telephone recall with mailed self-sample HPV testing kits (intervention); and 3) telephone recall with mailed self-
sample HPV testing kits and patient navigation (intervention plus). The primary outcome is primary screening
participation. Secondary outcomes are predictors of screening and attendance for clinical follow-up among
screen-positive women. Our study will also identify attitudes and experiences toward self-sampling among
women who receive a mailed self-sampling kit and toward clinical follow-up among women who test positive for
high-risk HPV. Finally, our study will evaluate the cost-effectiveness of mailed self-sample HPV testing, alone
and in combination with patient navigation, to increase screening participation and reduce cervical cancer risk in
safety net health systems. Collectively, these data will define the impact of self-sample HPV testing in a real-
world health system setting, a critical step toward the development of scalable, cost-effective programs to
eliminate cervical cancer disparities among underserved racial/ethnic minority wom...

## Key facts

- **NIH application ID:** 10320732
- **Project number:** 5R01MD013715-04
- **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:** $636,719
- **Award type:** 5
- **Project period:** 2019-04-16 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10320732

## Citation

> US National Institutes of Health, RePORTER application 10320732, A Randomized Controlled Trial of Mail-Self Stamped HPV Testing to Increase Cervical Cancer Screening Participation Among Minority/Underserved Women in an Integrated Safety Net Healthcare System (5R01MD013715-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10320732. Licensed CC0.

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