This randomized phase II trial studies how well carrageenan-containing gel (vaginal gel) works in reducing the rate of human papilloma virus (HPV) infection in healthy participants. Carrageenans, which are naturally derived from seaweed, are enhancements to natural lubrication and may be effective in blocking HPV infection.
PRIMARY OBJECTIVES: I. To measure the overall efficacy of the intervention in reducing the rate of incident cervical HPV infection. SECONDARY OBJECTIVES: I. Perform in vitro exploratory testing of how long after vaginal application the drug retains biological activity by collecting cervicovaginal lavage (CVL) at different times and spiking the samples with HPV pseudovirions (PsVs) and measuring PsV entry into target cells. II. These studies will be expanded to test multiple HPV types and to examine whether the anti-HPV activity of the intervention is preserved in the setting of semen. III. Store swabs to potentially test candidate biomarkers of microbicide efficacy and safety. OUTLINE: Participants are randomized to 1 of 2 arms. ARM I: Participants apply carrageenan-containing gel vaginally within 12 hours prior to each vaginal sex act and as soon as possible within 12 hours after each vaginal sex act and use condoms for 12 months. ARM II: Participants apply placebo gel vaginally within 12 hours prior to each vaginal sex act and as soon as possible within 12 hours after each vaginal sex act and use condoms for 12 months.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
DOUBLE
Rutgers New Jersey Medical School
Newark, New Jersey, United States
Rate of incident cervical HPV infection
The primary analysis will be based upon the intent to treat approach. The cumulative incidence of HPV infection for each treatment group will be estimated as described above and the percent reduction in incidence due to intervention will be computed along with the corresponding one-sided 80% lower confidence bound.
Time frame: Up to 1 year
Cumulative incidence rates of HPV in the target population (using data from the placebo group)
Multivariate logistic regression models that incorporate additional subject data (e.g., frequency of intercourse and number of recent sex partners, anal sex, and smoking behavior) will be fit to the data to control for potential imbalances in subject characteristics that may occur despite randomization with HPV infection status as the binary dependent variable. A generalized estimating equation approach will also be used to model treatment effect on infection with multiple HPV types.
Time frame: At 1 year
Subject adherence as measured by monthly applicator collection and counting
Will perform a per protocol analysis including only "adherent" subjects, defined as subjects who report gel use as recommended (within one hour of intercourse) in \> 50% of all vaginal intercourse acts. Will perform additional analyses to identify any imbalances in subject characteristics across groups, and in secondary analyses using logistic regression models to incorporate this as above.
Time frame: Up to 1 year
Behavioral characteristics assessed by questionnaires
Multivariate logistic regression models that incorporate additional subject data (e.g., frequency of intercourse and number of recent sex partners, anal sex, and smoking behavior) will be fit to the data to control for potential imbalances in subject characteristics that may occur despite randomization with HPV infection status as the binary dependent variable. A generalized estimating equation approach will also be used to model treatment effect on infection with multiple HPV types.
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Ancillary studies
Time frame: Up to 1 year
Biological activity of carrageenan-containing gel or placebo as measured by CVL at different times and spiking the samples with HPV PsVs and measuring PsV entry into target cells
Changes in this variable at each time point relative to baseline will be compared between groups using analysis of covariance models to adjust for baseline level. In addition, linear mixed effects models will be fit to all the repeated measurements to evaluate and compare trends over time while adjusting for the within-subject correlation in the data.
Time frame: Baseline to up to 12 months