Ms Amy Mulick
BSc MA MSc
in Medical Statistics
I came to medical research in 2009 through the fields of clinical trials and epidemiology and have since focused on ‘translational’ work between the two, particularly in biomarker discovery and assessment. At the Cancer Biomarkers Unit, Institute of Cancer Research (ICR), I evaluated the biochemical effects of novel drugs in early phase clinical trials. In the Departments of Medical Statistics and Non-Communicable Disease Epidemiology here at LSHTM, I have been a statistician for TRACK-ON HD, a prospective observational biomarker study of individuals who have inherited the Huntington's disease genetic mutation, and for the British Women’s Heart and Health Study, a prospective cohort study of heart disease in elderly British women – both collaborations with University College London (UCL)-based Institutes.
Currently (February 2016) I work with Professor Chris Frost in the Department of Medical Statistics, collaborating with researchers at the University of Oxford, Department of Psychiatry, to investigate post-treatment effects of a new depression treatment programme for people with cancer.
I have taught many Term 1 practical sessions on the London-based MSc in Medical Statistics, including Probability, Inference, Analytical Techniques, Linear Regression, Robust Statistical Methods and Introduction to Stata, in Term 2 Statistical Methods in Epidemiology (SME), and on the summer short courses Clinical Trials and Advanced Course for Epidemiological Analysis. In 2015/2016 I will teach practicals on the Term 3 modules Advanced Statistical Methods in Epidemiology (ASME) and Emerging Themes: Big Data and I will tutor on the module ‘Further Statistical Methods for Clinical Trials’ on the distance learning MSc in Clinical Trials. I occasionally deliver the same material for LSHTM elsewhere in the UK and abroad.
Currently I am investigating the longer-term effects of a new integrated depression treatment programme: Depression Care for People with Cancer (DCPC). We are using information in a large depression screening database and results from randomised controlled trials SMaRT-2 and SMaRT-3 to quantify the effect of depression and the successful treatment of depression on overall survival and other outcomes. My ongoing work with Professor JP Casas at UCL is in using metabolomic profiles to quantify heterogeneity in serum high-density lipoprotein (HDL) metabolism and to identify metabolites that can discriminate between different (medical) causes of mortality.
Previously I used longitudinal data to inform future clinical trial design, and evaluated changes in serum circulating tumour cell (CTC), cell-free DNA and cytokine concentrations, and their potential for use as prognostic or predictive biomarkers in people with cancer.
Statistical methods: Survival analysis, linear mixed models and generalised estimating equations, exploratory factor analysis, k-means and hierarchical cluster analysis.