|Tel||+44 (0)1865 289355|
My current research interests include monitoring chronic diseases, especially diabetes and hypertension, and clinical prediction rules, especially risk scores. My publications, listed on my webpage at the department of primary care health sciences, give the best overview of my research.
I am currently supervising students in medical statistics including the monitoring of chronic diseases; the reporting and analysis of diagnostic test results; and survival models for competing risks. I also supervise a part-time student on diagnostic accuracy in complementary and alternative medicine, and a research fellow on meta-analysis methods. I would welcome students with an interest in any of these or related areas.
BA MSc PhD
University Research Lecturer
- Deputy Director, Statistics Group
- Associate Professor
As a medical statistician, most of my research, whether I'm leading the project or supporting colleagues, is intended for clinical journals. Much of my research is with colleagues in the Oxford Centre for Monitoring and Diagnosis (MaDOx) on the monitoring of chronic diseases and on diagnosis and prognosis: the list of publications to the right is the best indicator of my research interests.
I also take responsibility for teaching statistics courses to preclinical students in Oxford's Medical Sciences Division, and contribute to statistics teaching on the Evidence Based Healthcare Programme at the Department for Continuing Education in collaboration with the Centre for Evidence Based Medicine.
Since 2010 I have been a member of the Indpendent Scientific Advisory Committee (ISAC) that advises the MHRA on research with databases such as the Clinical Practice Research Datalink (CPRD). I'm also pleased to be affiliated with Oxford's Diabetes Trials Unit, where I collaborate on some projects on cardiovascular risk, and the HRB Centre for Primary Care Research in Dublin, with whom I'm working on papers on the uptake of clinical prediction rules, under the umbrella of the International Diagnosis and Prognosis Prediction (IDAPP) group.
Key Publications5 False False
Cancer outcomes and all-cause mortality in adults allocated to metformin: systematic review and collaborative meta-analysis of randomised clinical trials.
Stevens RJ. et al, (2012), Diabetologia, 55, 2593 - 2603
Quantifying the effect of metformin treatment and dose on glycemic control.
Hirst JA. et al, (2012), Diabetes Care, 35, 446 - 454
Home measurement of blood pressure and cardiovascular disease: systematic review and meta-analysis of prospective studies.
Ward AM. et al, (2012), J Hypertens, 30, 449 - 456
Systematic review and validation of prediction rules for identifying children with serious infections in emergency departments and urgent-access primary care.
Thompson M. et al, (2012), Health Technol Assess, 16, 1 - 100
Against all odds? Improving the understanding of risk reporting.
A'Court C. et al, (2012), Br J Gen Pract, 62, e220 - e223
Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP): Derivation and Validation of a Tool to Improve the Accuracy of Blood Pressure Measurement in Clinical Practice.
Sheppard JP. et al, (2016), Hypertension, 67, 941 - 950
Methods for meta-analysis of pharmacodynamic dose-response data with application to multi-arm studies of alogliptin.
Langford O. et al, (2016), Stat Methods Med Res
Chronic renal disease is not chronic kidney disease: implications for use of the QRISK and Joint British Societies risk scores.
Stevens SL. et al, (2016), Fam Pract, 33, 57 - 60
Accuracy of blood pressure monitors available in high street pharmacies.
Ware A. et al, (2016), Blood Press Monit, 21, 59 - 61
The use of statistical methodology to determine the accuracy of grading within a diabetic retinopathy screening programme.
Oke JL. et al, (2015), Diabet Med