Dr Pradeep Virdee
BSc, MSc, DPhil
I am a Medical Statistician based in the Nuffield Department of Primary Care Health Sciences, University of Oxford. I joined in January 2022 and work primarily on cancer research observational studies. My projects include BLOTTED, developing clinical prediction models for cancer detection using routinely collected repeated-measures blood test data from CPRD, and SYMPLIFY, assessing diagnostic performance of a multi-cancer early detection blood test (GalleriTM) in symptomatic patients.
From August 2014 to December 2021, I was based in the Centre for Statistics in Medicine (CSM), University of Oxford. I worked primarily in oncology clinical trials, providing statistical expertise in all aspects of study execution, covering a range of cancer types, study designs, and trial phases. From January 2019 to December 2021, I underwent a DPhil (PhD) in CSM, funded by the NIHR Doctoral Research Fellowship Programme. My research involved developing dynamic prediction models (multivariate joint models) using patient-level trends in the full blood count (FBC) blood test for two-year risk of colorectal cancer.
My interests include improving efficiency in statistical programming, such as to make data management easier and less time-consuming. My interests also include teaching, teaching statistical courses on departmental undergraduate and graduate courses and having been the Lead Teacher for the University's IT Learning Centre's Stata courses since January 2018.
In 2016, I was awarded with the University of Oxford's Award for Excellence for my "consistent exceptional performance."
Before joining Oxford, I graduated from Coventry University in 2012 with a BSc in Mathematics and from the University of Leicester in 2013 with a MSc in Medical Statistics.
Full BLOOD count TRends for colorectal cAnCer deteCtion (BLOODTRACC): development of dynamic prediction models for early detection of colorectal cancer using trends in blood tests from primary care
Virdee PS. et al, (2023)
BLOod Test Trend for cancEr Detection (BLOTTED): protocol for an observational and prediction model development study using English primary care electronic health record data.
Virdee PS. et al, (2023), Diagn Progn Res, 7
Early detection of colorectal cancer using symptoms and the ColonFlag: case-control and cohort studies
HOLT T. et al, (2023), NIHR Open Research
Full blood count trends for colorectal cancer detection in primary care: development and validation of a dynamic prediction model
Virdee PS. et al, (2022), Cancers
Diffusion-weighted magnetic resonance imaging as an early predictive marker of chemoradiotherapy response in squamous cell carcinoma of the anus: an individual patient data meta-analysis
VIRDEE P. et al, (2022)