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Validating the test-negative case-control design for estimating rotavirus vaccine effectiveness using gold-standard randomized controlled trial data from South Africa and Malawi (Rota-037)
Proposal
1090
Title of Proposed Research
Validating the test-negative case-control design for estimating rotavirus vaccine effectiveness using gold-standard randomized controlled trial data from South Africa and Malawi (Rota-037)
Lead Researcher
M. Elizabeth Halloran
Affiliation
Fred Hutchinson Cancer Research Center;
Department of Biostatistics, University of Washington
Funding Source
Gates Foundation to PATH with subcontract to Fred Hutchinson Cancer Research Center and additional NIH/NIAID Grant Funding
Potential Conflicts of Interest
Merck (HPV Vaccine Scientific Advistory Committee)- no conflict
Sanofi Pasteur (Dengue Vaccine) - no conflict
Data Sharing Agreement Date
15 April 2015
Lay Summary
Rotavirus is the leading cause of severe diarrhea in children worldwide. Annually there are about 453,000 deaths attributable to rotavirus diarrhea in children. Most of these deaths occur in sub-Saharan Africa and south Asia. Recently low-income countries have introduced rotavirus vaccine into national immunization schedules. After introduction of a new vaccine case-control studies are conducted to assess vaccine effectiveness in a particular setting. The classical case-control study for rotavirus vaccine includes rotavirus diarrheal cases ascertained at a hospital or through surveillance, and controls include subjects without diarrhea but from the same hospital for a different disease or healthy subjects from a nearby community. Researchers have begun to conduct test-negative case-control studies for rotavirus vaccine. In these studies, cases include laboratory confirmed rotavirus-diarrhea but the controls are those with diarrhea caused by a pathogen other than rotavirus. The test-negative case-control design has been validated for influenza vaccines by analyzing RCT data as if it were collected through an observational case-control study (De Serres 2013). A similar validation method could be used for rotavirus vaccine. This can be accomplished by analyzing the dataset from the Rotarix-037 vaccine clinical trial.
Aims:
1. Compare original estimates of efficacy of Rotarix from the 037 trial to those generated using a test-negative case-control design.
2. Explore estimates of vaccine effectiveness (VE) using participant and specimen-based analyses.
3. Explore the sensitivity of estimates to different methods of case capture.
4. Explore sensitivity of estimates under the test-negative design to various precision variables, such as country, age, sex, race, clinic, month of hospital/clinic admission.
The main analysis (Aim 1) includes assessment of the RCT as if it were a test-negative case control study. Cases will include subjects with severe rotavirus gastroenteritis and controls will include subjects who tested rotavirus negative at any time within the study period. Vaccine effectiveness will be calculated and compared to original vaccine efficacy estimates. In Aim 2 we explore additional analyses including participant-based analysis with censoring for rotavirus where controls are rotavirus negative throughout the entire study period. A specimen-based analysis will also be conducted. For Aim 3 we will calculate separate VE estimates when cases are obtained through weekly home visits and through health clinics. In Aim 4 we will explore the sensitivity of the test-negative case-control study by adjusting for precision covariates. Adjusting for these covariates may lead to more precise and less biased estimates if these variables are prognostic of severe rotavirus gastroenteritis.
Findings: We will publish the results in a peer-reviewed scientific journal. Results will inform future studies on the effectiveness of rotavirus vaccine.
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
Medicine: Rotavirus Vaccine, Condition: Infections, Rotavirus, Phase: 3, Clinical Study ID: 102248, Sponsor: GSK" },{ "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
Medicine: Rotavirus Vaccine, Condition: Infections, Rotavirus, Phase: 3, Clinical Study ID: 111274, Sponsor: GSK" }]
Statistical Analysis Plan
Statistical tests and methods:
For aims 1-3 vaccine effectiveness will be calculated using the formula VE%=(1-OR) X 100. Odds ratios, 95% confidence intervals and 2-sided p-values will be calculated. 95% confidence intervals will be computed using the asymptotic normal distribution for Wald-type maximum likelihood methods. Two-sided p-values will be based on the chi squared statistic. Adjusted odds ratios in aim 4 will be calculated using logistic regression with severe rotavirus gastroenteritis as the outcome and vaccine status as the main exposure, adjusting for country, age, sex, race, clinic, month of hospital/clinic admission. Two-sided p values and 95% confidence intervals will be computed assuming the asymptotic normal distribution for the logistic regression parameter estimates.
Statistical Power:
The original study calculated 3960 infants would provide 84% power to detect a significant difference in the pooled vaccine and placebo groups given a vaccine efficacy of 60%.
While we currently do not have exact numbers of cases and test-negative controls for the three types of analyses we can estimate power based on published results during the first year. In the trial with an estimated 126 cases and 308 rotavirus test-negative controls and a two-sided alpha=0.05, we estimate the sample provides 99.4% power to detect a relative odds of 38.8% (VE=61.2%, the original estimated efficacy). Secondary aims for subgroups analyses likely have significantly reduced power to detect an association due to the limited sample size.
Missing Data: Missing data will be handled as in the original analysis.
Publication Citation
http://dx.doi.org/10.1016/j.vaccine.2016.10.077
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