Dr John W Stevens PhD, BSc (Hons)

HEDS, ScHARR
The University of Sheffield
Regent Court
30 Regent Street
Sheffield
S1 4DA
UK

Office:

Tel: (+44) (0)114 222 6396
Fax: (+44) (0)114 272 4095

E-mail: j.w.stevens@sheffield.ac.uk

Biography

My primary role is Director of the Centre for Bayesian Statistics in Health Economics (CHEBS). I graduated from Brunel University in 1982 with a BSc in Statistics/Mathematics. After graduating, I worked in the pharmaceutical industry for 24 years, including at SK&F Research Ltd (1982 – 1986), Wellcome Research Laboratories (1986 – 1995), GlaxoWellcome (1995 – 1996) and AstraZeneca R&D Charnwood (1996 – 2006). During this time I gained experience in the design and analysis of pre-clinical studies and in all phases of clinical drug development, and held a variety of management positions. In 1998, I assumed a technical role in the development and application of statistical methods to improve the drug development process, with a particular interest in Bayesian methods. During this time, I became interested in the application of Bayesian methods in health economics and was actively involved in the creation of CHEBS. My PhD was on latent variable modelling of effectiveness and resource use data in cost-effectiveness analyses of clinical trials. I moved to the University of Sheffield in November 2006 to provide leadership to CHEBS and further develop my Bayesian interests.

Research interests

My research interests include:

• the application of Bayesian methods in drug development
• statistical methods in health economics
• evidence synthesis
• sample size determination under uncertainty
• adaptive dose finding

Teaching interests

My teaching interests are:

• HAR670: Medical Statistics and Evidence Synthesis
• HAR6035: An Introduction to Medical Statistics and Critical Appraisal
• PAS6062: Further Clinical Trials

Professional activities

In addition to my role as Director of CHEBS, I am:

• a member of the National Institute for Health and Clinical Excellence (NICE) Appraisal Committee
• on the panel of expert reviewers for the National Institute for Health Research (NIHR) Health Technology Programme
• Editor-in-Chief of the Pharmaceutical Statistics journal

Current projects

I am currently working on the following projects:

• Cost-effectiveness of diagnostic strategies for suspected acute coronary syndrome (ACS). National Institute for Health Research: Health Technology Assessment Programme: 1 April 2010 – 30 June 2011. Co-investigator (£177,757).
• Revisiting the options appraisal for colorectal cancer screening. National Health Service: 1 May 2010 – 31 December 2010. Co-investigator (£58,000).
• Methods of extrapolating RCT evidence for economic evaluation. Medical Research Council: 1 October 2010 – 31 March 2012. Co-investigator (£313,888).

Key publications

• Stevens JW. Nice work: how NICE decides what we should pay for. British Journal of General Practice 2010;60(570):7-8.
  
  
• Nixon RM, O’Hagan A, Oakley J, Madan J, Stevens JW, Bansback N, Brennan A. The Rheumatoid Arthritis Drug Development Model: A case study in Bayesian clinical trial simulation. Pharmaceutical Statistics 2009;8:371-89.
  
  
• Ara R, Pandor A, Stevens J, Rees A, Rafia R. Early high-dose lipid lowering therapy to avoid cardiac events: a systematic review and economic evaluation. Health Technology Assessment 2009;13(34).
  
  
• Nixon RM, Bansback N, Stevens JW, Brennan A, Madan J. Using short-term evidence to predict six-month outcomes in clinical trials of signs and symptoms in rheumatoid arthritis. Pharmaceutical Statistics 2009;8:150-62.
  
  
• Whitehead J, Zhou Y, Stevens JW, Blakey G, Price J, Leadbetter J. Bayesian decision procedures for dose-escalation based on evidence of undesirable events and therapeutic benefit. Statistics in Medicine 2006;25:37-53.
  
  
• Zhou Y, Whitehead J, Bonvini E, Stevens JW. Bayesian decision procedures for binary and continuous bivariate dose-escalation studies. Pharmaceutical Statistics 2006;5:125-133.
  
  

Forthcoming publications

• Stevens JW. A note on dealing with missing standard errors in meta-analyses of continuous outcome measures in WinBUGS. To appear in Pharmaceutical Statistics.
  
  
• Stevens JW. Uncertainty analysis is inherently Bayesian. Value in Health 2011;14(1):