Award Title: Missing data in paediatric clinical trials; why does it happen and what can we do about it?
Funder: Department of Health and Social Care

Abstract: Research questionThis research will address two problems in paediatric randomised controlled trials (RCTs):	Lack of understanding as to why missing data occurs, and how it can be reduced. 	Limited guidance on appropriate statistical methods, and how these are implemented, when missing data are suspected to be Missing Not At Random (MNAR).Background There are not enough well-designed, high-quality paediatric trials leading to treatments being used which have only been tested in adults or not tested at all. Preliminary results from a literature review has shown that retention rates may be lower in paediatric trials compared to adult trials. If paediatric trials were of higher-quality with fewer missing data, more evidence would be available on appropriate treatments. If data are missing, failure to appropriately account for these in analyses can lead to bias and loss of precision, such that misleading conclusions may be drawn from the results. An estimated 65% of studies do not report how missing data were dealt with, and that even if reported, the methods used were inadequate. Analyses of data from paediatric RCTs are often carried out under the Missing At Random (MAR) assumption but sensitivity analysis methods that allow missing data to be Missing Not At Random (MNAR) are rarely carried out, despite RCT analysis guidance. Aims and objectives The overall aim is to improve the estimates of effectiveness and cost-effectiveness of paediatric trials through:	Reducing missing data 	Improving the analyses of incompletely observed data suspected to be MNARMethods There are four projects in this research:	Literature review of retention rates in paediatric trials	Qualitative study using interviews with children/young people and their parent/carer(s) who have taken part in paediatric RCTs: exploring their understanding of retention; identifying reasons for missing data and investigating the acceptability of alternative data-capture methods and data-linkage. 	Literature review of statistical methods for analyses where missing data are suspected to be MNAR. 	Quantitative analyses involving a simulation study to compare statistical methods for analyses where missing data are suspected to be MNAR, and an illustration of these methods using real trial data.Anticipated impact and dissemination In the short-term, my research will inform those currently conducting paediatric RCTs in how to reduce missing data at follow-up, improving retention. For future RCTs, this research is likely to change the data collected (for example, from schools/parents) which can be used in analysis methods when missing data is suspected to be MNAR. In the medium to long term, this will improve estimates of effectiveness and cost-effectiveness of treatments from paediatric trials and increase the subsequent evidence base for paediatric treatment. I will disseminate the results of this research to patients through working with charities, patient and public involvement groups, the Science Media Centre and University Press Office. I also additionally raise awareness of my research with trialists, clinicians and statisticians through publishing articles and practical guidance in how to implement methods found in Projects 2 and 4.

Lay Abstract: Aim of the research To improve trials testing treatments in children/teenagers by reducing the amount of missing data and using better methods to deal with it if it happens. Background In a trial for children/teenagers, we collect data to see which treatments work best. Trials for children/teenagers are more complicated than in adults because data can be collected from children and their parents/carers. Missing data can mean researchers make the wrong decision about whether a treatment works. Missing data may occur because patients do not like how questions are asked, feel too ill, stop taking part in the trial or for other reasons that we do not know about. Little is known about how to reduce the amount of data that is missing and the best way to summarise results of trials with missing data in children/teenagers. Design and methods Aim 1: Understand how to support/encourage children/teenagers, and parents/carers, to provide data in trials.In Project 1, I will look at reports of trials of treatments for children/teenagers to understand why children/teenagers and their parents might not provide data. In Project 2, I will interview children/teenagers and their parents/carers who are taking part in trials to understand their opinions and experiences about:	reasons for missing data (for example, the child/teenager felt ill) 	how they can be helped to complete questionnaires (such as, completing on an app) 	whether they would allow other information to be collected (such as, school records) 	also collecting the same data about the child/teenager's illness from parents/carersAim 2: Improve the understanding and use of methods for dealing with missing data. If data is missing, we might be able to estimate it using other data that is available. There are several methods to do this, but they depend all on why the data is missing. I will focus on methods that can be used when we think the reason for missing data is related to the missing data itself. For example, when a child/teenager is too ill to complete a questionnaire on health and therefore it is missing. This type of missing data is 'Missing Not At Random' (MNAR) and is rarely used in trials at the moment. Trials in children/teenagers are suited to using these MNAR methods because there are often data available from parents/carers or school records (which are almost always available). In Project 3, I will review the literature on methods used to summarise results of trials when the missing data are MNAR. In Project 4, I will test these methods. I will create different copies of the trial results based on data from real trials (data simulation). I will then use these copies of the data to compare the methods found in Project 3 and report which of these methods works the best. I will also repeat the calculations of the results of completed trials in children/teenagers using the methods found to see what happens to the results, and if it affects the decisions about treatments that were made from these results. Impact Improving trials in children/teenagers will make the results more trustworthy, which will help doctors to make better decisions about the best treatment for children/teenagers who are ill. Patient and public involvement I will work with an existing group for children/teenagers with different experiences of research in health and other groups of children/teenagers who have different health problems and their parents/carers. Dissemination I will disseminate the results of my research by: publishing articles, attending conferences, working with the press office and writing summaries for children's medical charities and teams that carry out trials.

Research Activity Codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health Categories: GENERIC HEALTH RELEVANCE