A Multilevel HPV Self-Testing Intervention to Increase Cervical Cancer Screening Among Women in Appalachia
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 802
- 试验地点
- 8
- 主要终点
- Effectiveness of Human Papillomavirus (HPV) Intervention
研究概览
简要总结
This trial studies how well a multilevel human papillomavirus (HPV) self-testing intervention works in increasing cervical cancer screening among women in Appalachia. Most cases of cervical cancer occur among unscreened and underscreened women. A multilevel HPV self-testing intervention may help to improve cervical cancer screening rates.
详细描述
PRIMARY OBJECTIVES:
Determine the effectiveness of the intervention in increasing cervical cancer screening.
OUTLINE: Participants are randomized to 1 of 2 groups.
GROUP I: Participants receive the HPV self-testing intervention consisting of mailed HPV self-test devices. Participants also receive an information about cervical cancer. Participants who do not return their self-test within a few weeks receive telephone-based patient navigation.
GROUP II: Participants receive usual care consisting of a reminder letter to get a clinic-based cervical cancer screening test and information about cervical cancer.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Screening
- 盲法
- None
入排标准
- 年龄范围
- 30 Years 至 64 Years（Adult）
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- •Not within recommended cervical cancer screening guidelines for women in this age range (i.e., no Papanicolaou [Pap] test in last 3 years or no Pap test plus clinic-based HPV test in last 5 years)
- •Resident of an Appalachian county
- •Not currently pregnant
- •Intact cervix
- •No history of invasive cervical cancer
- •Seen in a participating clinic/health system in last 2 years (i.e., active patient)
- •Have a working telephone
排除标准
- 未提供
结局指标
主要结局
Effectiveness of Human Papillomavirus (HPV) Intervention
时间窗: Up to 1 years
The patient-level effectiveness will be whether or not women get "screened" during the project. Will examine the proportion of women screened, and use an intent-to-treat approach. To compare treatment groups (Group 1 versus Group 2), will use generalized linear mixed models (GLMMs) to account for the correlation between women from the same health system.
次要结局
未报告次要终点
研究者
Paul Reiter
Principal Investigator
Ohio State University Comprehensive Cancer Center