**The Centre for Mathematical Sciences**** research seminars and events are listed below.**

The four main seminar series are in applied mathematics, pure mathematics, statistics and theoretical physics. Visit the centre's webpages for the latest seminar updates and information.

**16 July, 11:00-12:00 (Room 210, Rolle Building): Xmeta: a comprehensive tool-box for advanced meta-analysis - meta-analysis, publication bias, and beyond**

- Speaker: Yong Chen, University of Pennsylvania

**Abstract: **In this talk, Yong is going to introduce a web-platform that they have been developing over the last few years, known as ‘xmeta’, which aims to facilitate advanced comprehensive meta-analysis for applied investigators within and beyond the Perelman School of Medicine at University of Pennsylvania. The functionality of this platform includes implementation of various multivariate meta-analysis for continuous and/or binary outcomes in randomised controlled trials, meta-analysis of diagnostic tests with/without gold standard, as well as methods to identify and correct for publication biases or small study effects. In addition, Yong will also introduce the online-analysis feature, which allows applied investigators to conduct these analyses without programing by themselves. At the end, Yong will talk about the future direction of incorporating semi-automated text mining to speed up the systematic review process.

Seminar organiser: Dr Yinghui Wei (yinghui.wei@plymouth.ac.uk)

**20 July, 14:00-15:00 (Room 2.13, South Cloisters Building, St Luke's Campus, University of Exeter): Methodological advances in evidence synthesis**

- Speaker: Orestis Efthimiou, University of Bern

**Abstract: **Network meta-analysis (NMA) is an extension of the usual (pairwise) meta-analysis. It is a statistical tool for synthesizing evidence obtained from studies comparing multiple competing interventions for the same disease. In this lecture, we will go through some recent advances in the field. First, we will discuss a new model for the NMA of binary outcomes. This model generalises the well-known Mantel-Haenszel method, and can be especially valuable for the case of rare events, e.g. when synthesising data on mortality or serious adverse events. The method has been implemented in R in freely available, easy-to-use routines. Second, we will discuss models for including non-randomised studies in NMA. Non-randomised studies can reveal whether or not interventions are effective in real-life clinical practice and there is a growing interest in including such evidence in the decision-making process. Here we present and compare an array of alternative methods, and we apply some of the methods in previously published clinical examples. Finally, we will discuss methods for individual participant data network meta-analysis (IPD-NMA). IPD are considered the gold standard in evidence synthesis, and inclusion of IPD in NMA offers unique advantages, such as increase in precision, decrease in heterogeneity, as well as the capacity to individualise the treatment according to a patient’s characteristics. We showcase our methods using an example from depression.

Note: This is a joint RSS South West Local Group and Exeter Health Statistics event.

Seminar organiser: Dr Yinghui Wei (yinghui.wei@plymouth.ac.uk)

**23 July, 14:00-15:00 (venue: Room 210, Rolle Building): N-of-1 Trials for Making Personalised Treatment Decisions with Personalised Designs Using Self-Collected Data**

- Speaker: Christopher Schmid, Brown University

**Abstract: **N-of-1 trials hold great promise for enabling participants to create personalised protocols to make personalised treatment decisions. Fundamentally, N-of-1 trials are single-participant multiple-crossover studies for determining the relative comparative effectiveness of two or more treatments for one individual. An individual selects treatments and outcomes of interest, carries out the trial, and then makes a final treatment decision with or without a clinician based on results of the trial. Established in a clinical environment, an N-of-1 practice provides data on multiple trials from different participants. Such data can be combined using meta-analytic techniques to inform both individual and population treatment effects. When participants undertake trials with different treatments, the data form a treatment network and suggest use of network meta-analysis methods. This talk will discuss ongoing and completed clinical research projects using N-of-1 trials for chronic pain, atrial fibrillation, inflammatory bowel disease, fibromyalgia and attention deficit hyperactivity disorder. Several of these trials collect data from participants using mobile devices. I will describe design, data collection and analytic challenges as well as unique aspects deriving from use of the N-of-1 design and mobile data collection for personalised decision-making. Challenges involve defining treatments, presenting results, assessing model assumptions and combining information from multiple participants to provide a better estimate of each individual’s effect than from his or her own data alone.

Seminar organiser: Dr Yinghui Wei (yinghui.wei@plymouth.ac.uk)