Contact information
Research groups
Trishna Rathod Mistry
Senior Medical Statistician/Senior Data Scientist
I joined the Pharmaco and Device Epidemiology research group within the NDORMS department in January 2022 as a senior statistician. I have an interest in applying complex longitudinal models to routinely collected medical record data, particularly in the estimation of time-varying treatment in the presence of time-varying confounding.
Previously, I was employed by Keele University, School of Medicine (2010-2022) as a statistician. I completed my PhD in 2021 which aimed to estimate the time-varying effect of allopurinol in gout using marginal structural models and propensity score stratification. I have worked on a wide variety of primary care research projects across different study populations (musculoskeletal conditions, dementia, and chest pain) and study designs (randomised controlled trials, prognosis, case-crossover, and longitudinal cohorts).
My interest in medical statistics started when I studied Mathematical Sciences BSc at the University of Birmingham. After which, I studied Medical Statistics MSc at the University of Leicester.
Recent publications
ssociation of nociplastic pain with executive function decline in a longitudinal cohort of middle-age adults: a prospective cohort study.
Journal article
Kelleher EM. et al, (2025), Br J Anaesth, 135, 1717 - 1729
Brain signatures of nociplastic pain: Fibromyalgia Index and descending modulation at population level.
Journal article
Kelleher EM. et al, (2025), Brain
Type 2 diabetes, metabolic health, and the development of frozen shoulder: a cohort study in UK electronic health records.
Journal article
Dyer BP. et al, (2025), BMC Musculoskelet Disord, 26
Hospital resource utilization and costs of imminent subsequent fractures in postmenopausal women: a distributed network analysis using data from the UK and Spain mapped to OMOP common data model
Conference paper
Fabiano G. et al, (2024), Value in Health, 27
e patients with newly diagnosed frozen shoulder more likely to be diagnosed with type 2 diabetes? A cohort study in UK electronic health records.
Journal article
Dyer BP. et al, (2024), Diabetes Obes Metab, 26, 5915 - 5921