HIV/AIDS
Conditions
Interventions
Pre exposure prophylaxes PrEP
Sponsors
University of Washington
Eligibility
Sex/Gender
Female
Inclusion criteria
Inclusion criteria: For all cisgender women - Age =18 and =30 years old. - Willing to undergo urine pregnancy tests. - Has understood the information provided and has provided written informed consent before any study-related procedures are performed.. - HIV uninfected based on negative HIV rapid tests, according to Kenyan national algorithm. - Normal renal function (estimated glomerular filtration rate >60 mL/min). - Hepatitis B surface antigen Ag negative.. - No active, clinically significant medical or psychiatric conditions that, in the opinion of the investigators, would interfere with study participation . - Lack of severe anemia (Hemoglobin >10 g/dL). - Willing to use DOT and come to clinic frequently for DOT PrEP for at least 10 weeks. - Willing to have home visits for follow up. - Has access to an active smartphone to allow off-site observation of dosing if unable to come to the clinic, or, as determined by the study staff, the participant resides in a close enough location to the clinic to permit a home visit if unable to come to the clinic. That isi.e., potential participants without a smartphone may be enrolled in the study if investigator determines that the participant resides within reasonable distance from the clinic that would permit home visit ID the participant misses their visit for a home visit in the case of a missed clinic visit. - Intention to stay within the study site’s catchment area for at least 10 weeks. Women TAF-FTC Benchmark Study. - Resides or works in catchment area with high speed internet coverage to permit video streaming. - Not pregnant or breast feeding. - Willing to use effective contraception during the study period. - At low risk for HIV. In Kenya, national guidelines define substantial risk for HIV and recommend PrEP be an option for individuals reporting: partner of HIV-infected person not on ART or on ART for 1 partner of unknown status, transactional sex, recent STI, recurrent PEP use,
Exclusion criteria
Exclusion criteria: For all cisgender women – Inability to give informed consent – Positive screening HIV+ as determined by standard rapid serologic assays or suspected acute HIV infection in the opinion of the clinician. (Eexample signs and symptoms of acute HIV infection include combinations of fever, headache, fatigue, arthralgia, vomiting, myalgia, diarrhea, pharyngitis, rash, night sweats, and cervical or inguinal adenopathy cervical or inguinal.) – Positive HBV surface antigen test at screening. – Calculated creatinine clearance 800mg acyclovir or >500mg valacyclovir for >7 days), cyclosporine, amphotericin B, foscarnet, and cidofovir, and products with same or similar active ingredients as the study medications including TAF®, TRUVADA®, ATRIPLA®, COMPLERA®, EMTRIVA®, VIREAD®; or drugs containing lamivudine or adefovir, which are close analogs of FTC and tenofovir, respectively. – Current or past use of PrEP (pre-exposure prophylaxis). – Not willing to have home visits. – Pregnantcy or plan to become pregnant in the next 6 months or unwillingness to use birth control . – Currently breastfeeding. – High risk of HIV infection (for example: sexually active with an HIV infected partner; engages in condomless intercourse with HIV-infected partners or partner of unknown status during the study; females who exchanges sex for money, shelter, or gifts; active injection drug use or during the last 12 months; newly diagnosed sexually transmitted infections in last 6 months.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Primary outcomes Primary outcome 1: The goal is to describe the frequency of adverse events, including emergent HIV infection during the study period. We will conduct a descriptive analysis for meeting PrEP157 eligibility among participants. The distribution of demographics and graded adverse events will characteristics by overall and study arms and proportions will compared between study arms using chi-square statistics. Primary outcome 2: The goal is to quantify the effect of dose on steady state TFV-DP in DBS and PBMC based on an incomplete block design. Css (drug concentration at steady state) will likely require a normalizing log transform, such that geometric means and CIs will be reported. Dose proportionality will be assessed using the power model (on the natural log scale) ln(Yijk) = µ + Si + Pj + ?log(Dk) + ?ijk (Eqn. 1).37 Where Yijk is the response, Css, for the kth dose (k=2, 4, 7 doses/week), jth period (j=1,2), ith subject(i=1,…45); µ is the overall mean, Si is a random subject effect, Pj is the period effect and ?ijk is random error. Dose proportionality dictates that ?=? for dose-dependent parameters and we will assume dose proportionality if the 90% CI is contained within the limits (0.8, 1.25). The SAS mixed procedure will be utilized for model (Eqn 1), again assuming a random subject effect. Although we do not anticipate a period effect, our design allows us to test this effect. For the primary analysis, we assume no effect of ‘non-daily dosing’ regimens; although this will be examined in a secondary analysis. If dose proportionality is not shown, we will examine proportionality separately for each of the ‘‘non-daily dosing’ dosing regimens. If dose proportionality is still not demonstrated when adherence regimens are examined separately, we will consider dose as a categorical predictor. Primary outcome 3: The goal is to identify TFV-DP cut points associated with adherence levels. For the primary analyses, we will attempt to discriminate adherenc | — |
Secondary
| Measure | Time frame |
|---|---|
| 1. Examine models to predict non-daily adherence based on TFV/FTC and FTC-TP/TFV-DP in DBS. We will first consider a saturated model allowing a separate mean for each dose/adherence group. The results will then be compared to a reduced model with a class variable indicating non-daily dosing groups” or 100% dosing (that is, the effect of “non-daily dosing” adherence does not differ by dose groups). Drug concentration predictors of “non-daily dosing” will focus on TFV-DP in relationship to other drug moieties such as FTC-TP and FTC and TFV. For instance, the ratio of TFV-DP to FTC-TP may be used as a predictor of “2” versus “4 dosing per week. A proportional odds logistic approach which allows for an ordinal outcome and extensions which control for correlations between repeated measurements on a subject will be utilized in SAS or R statistical software. In addition, we will employ PK models (see Aim-1) to simulate TFV-DP to FTC-TP ratios for other dose regimens and estimate cut points for predicting non-daily dosing patterns. 2. Examine relationships among drug concentrations in plasma, RBC, DBS, and PBMC.We will use mixed and non-linear mixed effects models to determine if concentrations in various matrices are related. 3. Evaluate the influence of demographics, and biological on drug concentrations. Kruskal-Wallis parametric test will be used to compare demographics and key study variables (e.g., age, pregnancy, HCT, contraception use, study arm, BMI, and eGFR). Non-linear mixed effects models also will be used to probe covariate effects on PK. Secondary analyses are considered hypothesis generating and will not correct for multiple comparisons. 4. Compare drug concentrations in DBS from finger stick versus transferring blood from blood tubes. Since these are paired DBS samples, we will compute the ratio of TFV-DP in the two samples and a mixed model on the natural log of the ratio will be utilized to determine if CI is within 0.8 and 1.25, indicating equivale | — |
Countries
Kenya
Contacts
Public ContactMatilda Saina
Study Physician KEMRI CCR PHRD
Outcome results
None listed