AHRI.STAR.WHO.PrEP.Data
STAR–Sharing of PrEP participant data with the WHO
Name | Country code |
---|---|
South Africa | ZA |
Background
In 2015, WHO published a recommendation on the use of antiretroviral medications for PrEP as an additional prevention choice for individuals at substantial HIV risk. WHO subsequently published modular implementation guidance (a tool) in 2017 to assist countries with introducing PrEP into their health systems. Since the publication of the WHO recommendation and the implementation tool, further positive clinical research findings from studies in men who have sex with men on the use of event-driven ('on-demand') dosing have been published. Key population groups such as men who have sex with men and transgender women are at particularly high risk of HIV globally, and may benefit from a shorter PrEP regimen (4 pills in total taken before and after a sexual exposure, rather than daily dosing.
PrEP is a comparatively new intervention, and data on related toxicities such as renal toxicity among healthy individuals has been limited but is growing. WHO would like to review the evidence on renal function relating to ARVs used in PrEP in order to inform an update to the clinical module on the frequency of creatinine monitoring required.
The results from these literature and clinical data reviews will used to update WHO PrEP clinical guidance and will be included in updated ARV guidelines to be published in 2020. WHO is conducting a systematic review of the available evidence on renal function related to PrEP use. However, the evidence is limited and the number of publications that present results by age or over time are few. Since studies and programs implementing PrEP routinely screen for renal function using creatinine screening, WHO is now requesting de-identified individual patient data from Principal Investigators and PrEP programs that contain the information needed but are not yet published, in order to conduct pooled analyses and generate evidence for updated guidance.
Purpose of analyses
The purpose of this analysis is to review the data on creatinine clearance and screening frequency among PrEP users to inform WHO PrEP clinical guidance for the frequency of creatinine screening.
Data collected by peer-navigators will be summarised by cluster (peer-navigator pair).
V1.0.0
Topic | Vocabulary | URI |
---|---|---|
HIV-1; Incidence; Phylogeny; Epidemics; Population Surveillance; Rural Population; HIV Infections; Africa | Africa Health Research Institute | www.ahri.org |
Demographic surveillance area of the Africa Health Research Institute.
The study population include 24 pairs of area (Ward/izigodi) based peer navigators working with over 2000 young people particularly young women aged 18-24 years. More than 2000 young people (males and females) will be reached during the trial in the 21 wards representing the study area.
Name | Affiliation |
---|---|
Dr Maryam, Shahmanesh | Africa Health Research Institute |
Pillay, Deenan | Africa Health Research Institute |
Name |
---|
Africa Health Research Institute |
Name | Role |
---|---|
South African Medical Research Council | Genotyping funding source |
Name | Affiliation | Role |
---|---|---|
Wilkinson, Eduan | KwaZulu-Natal Research Innovation Sequencing Platform | Cleaned, aligned and help analyse the sequence data |
Since the study is a cluster randomised control trial with three arms where all areas in the southern Population Intervention Platform (PIP) were included, no formal sampling was done. We estimated that ~500 age eligible 18-24 years olds will be enrolled per peer navigator team catchment area, of whom we anticipate at least 200, 18-24-year-old females will be handed a coupon (so cluster size at least 200). We calculated the sample size calculation using the primary outcome, the rate of linkage after 3 months among women ages 18-24 years. Using our existing data on uptake of HIV testing in the DREAMS interventions as well as our data on uptake of testing and linkage to HIV care in the demographic surveillance rounds of, we estimate that 1 woman will link per 7 months of peer educators outreach work time in the standard of care. With 7 peer educator pairs (or clusters) per arm and a cluster coefficient of variation (k) of 0.25, we have 80% power to detect a 100% increase in rate from 1 woman to 2 women per 7 months of follow-up, and 90% power to detect a 150% increase from 1 woman to 2.5 women per 7 months of follow-up. We have chosen policy and clinically relevant increases in linkage to care. Assuming additional clustering of the outcome within peer educators and increasing the coefficient of variation (k) to 0.35, we have 80% power to detect a 150% increase in rate from 1 woman to 2.5 women per 7 months of follow-up. All sample size calculations assume two-tailed statistical tests with alpha=0.05.
Start | End |
---|---|
2019-03-15 | 2020-06-30 |
The representative of the Receiving Organization agrees to comply with the following conditions:
DDI.AHRI.STAR.WHO.PrEP.Data
Name |
---|
Africa Health Research Institute |