Summary
Rachel was awarded an NIHR Doctoral Research Fellowship in 2018 to undertake her PhD at Imperial College London. Her research focuses on the reporting and analysis of adverse events in drug trials and developing statistical methods to better identify adverse drug reactions.
Rachel was awarded an NIHR Research Methods Fellowship to complete her MSc in Medical Statistics at the London School of Hygiene and Tropical Medicine in 2009. After she graduated in 2010 she spent two years working as a statistician at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London before moving to Singapore to work for an academic clinical research organisation focusing on clinical trials in infectious diseases and mental health. She joined the Division of Health and Social Care Research, King’s College London in August 2015 as a research fellow to work as a clinical trial statistician including both early and later phase trials. During this time she also worked as a general adviser for the NIHR Research Design Service.
Publications
Journals
Furukawa T, Suganuma A, Ostinelli E, et al. , 2021, Dismantling, optimising and personalising internet cognitive-behavioural therapy for depression: A systematic review and individual participant data component network meta-analysis, The Lancet Psychiatry, ISSN:2215-0366
Furukawa T, Levine S, Buntrock C, et al. , 2021, How can we estimate QALYs based on PHQ-9 scores? Equipercentile linking analysis of PHQ-9 and EQ-5D, Evidence-based Mental Health
Karyotaki E, Efthimiou O, Miguel C, et al. , 2021, Internet-Based Cognitive Behavioral Therapy for Depression, Jama Psychiatry, ISSN:2168-622X
Cornelius V, Cro S, Phillips R, 2020, Advantages of visualisations to evaluate and communicate adverse event information in randomised controlled trials, Trials, Vol:21, ISSN:1745-6215
Phillips R, Cornelius V, Sauzet O, 2020, Statistical methods for the analysis of adverse event data in randomised controlled trials: a scoping review and taxonomy, Bmc Medical Research Methodology, Vol:20, ISSN:1471-2288