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Translating randomized controlled trial data to an external target population: a secondary analysis of data from the RV1 trial in South Africa and Malawi
Proposal
11504
Title of Proposed Research
Translating randomized controlled trial data to an external target population: a secondary analysis of data from the RV1 trial in South Africa and Malawi
Lead Researcher
Denise St. Jean
Affiliation
University of North Carolina at Chapel Hill, Department of Epidemiology
Funding Source
Potential Conflicts of Interest
Data Sharing Agreement Date
14 January 2021
Lay Summary
Although the burden of rotavirus has steadily declined over the past decade, rotavirus continues to be a leading cause of acute gastroenteritis among children younger than five years. Annually, rotavirus accounts for about 258 million diarrhea episodes and 128,500 deaths. However, low-and-middle- income countries (LMIC) experience a disproportionate amount of the world's rotavirus infections compared to high-income settings.As new vaccines move down the pipeline it is increasingly important that estimates from vaccine trials are transportable to external target populations. While randomized controlled trials (RCTs) are popularly considered the “gold standard” for verifying the safety and efficacy of disease interventions, they suffer from a lack of external validity and may not be applicable to real-world populations or alternate settings that may utilize the intervention.The aim of this study to utilize propensity score methods to transport Rotarix vaccine efficacy estimate from the South Africa and Malawi trials to a target population of all eligible children in Malawi using the 2015/6 Malawi Demographic and Health Survey data to represent a random sample of our target population.A peer reviewed publication will be submitted summarizing the results. As additional rotavirus vaccines and other oral vaccines move down the pipeline, ministries of health can greatly benefit from this research when considering their vaccination implementation strategy.
Study Data Provided
[{ "PostingID": 1296, "Title": "GSK-102248", "Description": "Multi-Center Study to Assess the Efficacy, Safety and Immunogenicity of 2 or 3 Doses of GSK Biologicals' Oral Live Attenuated Human Rotavirus (HRV) Vaccine Given Concomitantly With Routine EPI Vaccinations in Healthy Infants" },{ "PostingID": 1297, "Title": "GSK-111274", "Description": "Multi-Center Study to Assess the Efficacy, Safety and Immunogenicity of 2 or 3 Doses of GSK Biologicals' Oral Live Attenuated Human Rotavirus (HRV) Vaccine Given Concomitantly With Routine EPI Vaccinations in Healthy Infants" }]
Statistical Analysis Plan
Using a main effects multivariable logistic regression model, we will combine individual data from the RCT and individual data from the DHS survey to estimate the probability of study participation. The weight for each individual who did not participate in the trial is 0. Otherwise, the weight will be calculated as the inverse odds of the sampling probability scaled by the ratio of the marginal sampling probability to the marginal non-sampling probability. Using the weighted RCT data, we will use Cox proportional hazard models to estimate the hazard ratio and 95% CI for the comparison of rotavirus gastroenteritis. We will also use the inverse of the Kaplan Meier curve to estimate the one-year risk for rotavirus AGE under vaccination in the target population. The primary endpoint will be the one-year vaccine efficacy against rotavirus AGE, where the risk ratio (RR) = cumulative incidence of rotavirus AGE in vaccinated children compared to the unvaccinated children, calculated as (1-RR) x 100%. We will conduct this analysis for both the Malawi and South Africa sites to produce two estimates of vaccine efficacy in the target population.
Publication Citation
Transporting monovalent rotavirus vaccine efficacy estimates to an external target population: a secondary analysis of data from a randomized controlled trial in Malawi D.T.St Jean, J.K.Edwards, E.T.Rogawski McQuade, P.Thompson, J.C.Thomas, S.Becker-Dreps.
Journal of Epidemiology & Infection, 2023
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