Title: Assessing and testing multivariate meta-analysis methods to improve the precision of studies with multiple correlated outcomes—the example of vaccine trials
Funder: Department of Health and Social Care

Abstract: Vaccination is a key area of NHS policy and one of the most cost-effective public health interventions for protecting the population from disease. Changes to the schedule of vaccinations in the UK do not occur often, however recently there have been multiple changes. Decisions on changes to vaccination policy need to be based on the best analysis of available data.Vaccines have changed greatly from the time they were first developed in the late 18th century and are now complex multi-component multi-dose interventions. As interventions become more complex, the statistical analysis of data to evaluate such interventions needs to keep pace. The multi-component nature of vaccine interventions means that trials usually have multiple primary outcomesone for each vaccine component. Antibody concentrations are used to assess immune response to a vaccine and are measured simultaneously from one blood sample. Thus a trial of a pneumococcal vaccine might contain 13 primary outcomesone for each of the 13 serotypes of pneumococcal disease contained in the vaccine. Responses to different components of a vaccine can be highly correlated yet analyses generally treat each component as if it is independent of all other components, and assess effectiveness separately at the 5% significance level. This increases the chance of finding falsely significant results (type 1 error bias) [6]. Methods are available for controlling type 1 error when multiple comparisons are independent of each other. However, for situations where outcomes are highly correlated there is no simple method for adjusting the results as the extent of bias is related to the underlying correlation structure in the data. This research seeks to investigate newer multivariate statistical methods for meta-analysis of studies with multiple correlated outcomes. Meta-analysis is a well-established method of combining information from multiple clinical trials or observational studies to obtain more precise estimates of treatment effects or differences. However, meta-analyses are conducted almost entirely using univariate methods i.e. each outcome is analysed independently even though outcomes may be related. Recently methods and software for conducting meta-analyses under a multivariate framework have become readily available enabling the correlation between study treatment effects to be controlled [7]. Multivariate meta-analysis has the potential to reduce the type 1 error bias which occurs when multiple outcomes are treated as independent analyses as the correlation structure of the data can be modelled. Individual participant data are available from 21 randomised controlled trials of combined diphtheria-tetanus-pertussis-polio vaccines. After a thorough review of different multivariate methods for meta-analysis and a comparison with univariate methods, multivariate methods will be used to answer two important questions about vaccines: whether girls respond differently to vaccination than boys, and the best ages for vaccinating infants. Some research has suggested that girls can have a detrimental immune response to certain vaccines compared to boys, however this is controversial. In the UK infants are vaccinated at 2, 3, and 4 months of age; in other countries they are vaccinated at different times e.g. at 2, 4, and 6 months. The timing of a vaccine can affect a person's response to it, and therefore how well they are protected against disease. In the UK we have never tested which vaccination strategy is most effective in infants. Our children may therefore be less protected than they could be. Changes might be possible to how we vaccinate our children that would protect them more fully without adding anything to the schedule. There may be health benefits from such changes without additional costs. This research will address such questions, providing information for policy makers when reviewing the current UK vaccination schedule.

Lay abstract: Vaccines protect people in the UK from many diseases. They are quick and inexpensive ways of providing protection for large numbers of people and work best when everyone receives their vaccines at the right times. There is a list of which vaccines each person in the UK should receive and at what age, starting from the age of 2 months old. This list does not change very often but has changed in recent years. It is important that when changes are made to the list these decisions are based on high quality information. This research will look at how we can improve our analysis of vaccine data to provide the best possible evidence. Modern vaccines often protect against more than one disease (e.g. diphtheria, tetanus, whooping cough, and polio are combined into one vaccine). Studies which measure the benefit of vaccines therefore measure markers of immunity for more than one disease at the same time. This is done by taking one blood sample and testing it many times using different tests. The way a person responds to vaccination against one disease (e.g. diphtheria) relates to the way they respond to vaccination against another (e.g. tetanus) when given at the same time. These relationships are important but are not generally included in current analyses. In order to include them, a different type of analysis can be used called 'multivariate analysis'. This research will look at new ways to analyse these vaccine data using the 'multivariate' method. It will compare the old and new methods to see if the newer methods give us better information. The new methods will then be used to answer two further questions about vaccines: whether girls respond differently to vaccination than boys, and what ages are best for giving vaccines to infants. In the UK infants are given vaccines at 2, 3, and 4 months of age; in other countries they are given at different time such as at ages 2, 4, and 6 months. The timing of a vaccine can affect a person's response to it, and therefore how well they are protected against disease. In the UK we have never tested which is the best time to give vaccines to children. They may therefore be less protected than they could be.

Research activity codes: 3.4 VACCINES;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: INFLAMMATORY AND IMMUNE SYSTEM