Title: AMS Professorship award for Professor Maia Lesosky, Liverpool School of Tropical Medicine
Funder: The Academy of Medical Sciences

Abstract: This professorship will be used launch a biostatistics research unit at the Liverpool School of Tropical Medicine (LSTM) to carry out methodological research in biostatistics and clinical trials. This professorship award will enable me to build immediate capacity with statistical research staff who are able to work independently and at a high level which will have multiple benefits. The major benefit will be in the immediate presence of a statistical team that will be able to commit time to new statistical methodology approaches in study design and analysis, leveraging existing collaborations and ongoing projects. Having a team in place composed of early career research staff (postdoctoral research associates and medical statisticians) represents a significant shift in depth of expertise compared to my current team, largely made of postgraduate trainees. Postdoctoral research staff have a huge impact on the contributions a statistical unit can make to global health studies as they have expertise and scope for methodological development. The second benefit is to the statistical staff currently in place both at LSTM, within the Global Health Trials Unit and with our low- and middle-income based teams, who will have access to additional senior mentorship and supervision that is currently lacking. For me personally, this award will enable me to oversee and carry out statistical research that would otherwise be limited due to my other academic responsibilities including Directorship of the Global Health Trials Unit and serving as senior statistician on a number of active trials. This professorship award would represent a big shift in my research career to move from leadership of a lab filled with postgraduate trainees to leadership of a group with sufficient expertise and capacity to contribute to biostatistical methods applied to global health research. The research questions we propose to focus on have been identified from recent collaborations. In cluster randomised trials with binary endpoints where interim analysis or adaptive designs are proposed, information accrues unevenly depending on the degree of correlation within the cluster and the rate or speed at which outcomes accrue. This leads to methodological challenges when specifying the appropriate time to carry out the interim analysis or sample size re-estimation. This issue, in turn, impacts directly on the statistical power at which the endpoint can be evaluated, and failure to account for this in the design stage can result in an underpowered or erroneously stopped trial. Existing data from the MRC and Gates Foundation funded cluster randomised trials in pneumonia and malaria will be used to support this work in collaboration with investigators. The second research theme that I will pursue with this professorship award builds on my National Institute of Health (USA) funded research into routine HIV monitoring using simulation modelling approaches to generate empirical data. This professorship will allow me to dedicate staff time to extend this model to multiple disease settings by generalising to any joint longitudinal process, with application to asthma in collaboration with my previous Newton Advanced Fellowship co-applicant and in malaria.


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS;2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE;INFECTION