James Wason

James Wason

Professor of Biostatistics

Population Health Sciences Institute

Biography

Background

I am a statistician with interests in methods for improving the design and analysis of clinical trials. As well as working in methodology development I have a great interest in collaborating on real trials to apply new methods in practice.

I have been at Newcastle University since July 2017.

Areas of expertise

  • Biostatistics
  • Clinical trials
  • Novel trial design

Research

My research focuses on statistical methods for improved design and analysis of clinical trials. I am particularly interested in:

  1. Adaptive designs for clinical trials;
  2. Methods for incorporating biomarkers into clinical trials to stratify patients by treatment response;
  3. Improved methods for analysing composite endpoints, in particular ones with continuous components.

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Contact

Publications

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Busby AD, Wason J, Pratt AG, Young A, Isaacs JD, Nikiphorou E (2021). Predictors of poor function in RA based on two prospective UK inception cohorts. Do comorbidities matter?. Rheumatology 2021; DOI:10.1093/rheumatology/keab598.

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Grayling MJ, Bigirumurame T, Cherlin S, Ouma L, Zheng H, Wason J (2021). Innovative trial approaches in immune-mediated inflammatory diseases: Current use and future potential. BMC Rheumatol 2021; 5:21.

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Cherlin S, Wason JMS (2021). Developing a predictive signature for two trial endpoints using the cross-validated risk scores method. Biostatistics 2021; DOI: 10.1093/biostatistics/kxaa055.

Collins A, Lendrem D, Wason J, Tarn J, Howard-Tripp N, Bodewes I, Versnel MA, Gottenberg JE, Seror R, Mariette X, Ng WF (2021). Revisiting the JOQUER trial: Stratification of primary Sjögren's syndrome and the clinical and interferon response to hydroxychloroquine. Rheumatol Int 2021; 41:1593-1600.

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Kunzmann K, Grayling MJ, Lee KM, Robertson DS, Rufibach K, Wason JMS (2021). A review of Bayesian perspectives on sample size derivation for confirmatory trials. Am Stat 2021; DOI:10.1080/00031305.2021.1901782.

Vergis N, Phillips R, Cornelius V, Katsarou A, Youngstein T, Cook L, Willicombe M, Pilay C, Shturova T, Almonte M, Charania A, Turner R, Kon OM, Cooke G, Thursz M, Cherlin S, Wason J, Milojkovic D, Innes AJ, Cooper N (2021). Multi-arm Trial of Inflammatory Signal Inhibitors (MATIS) for hospitalised patients with mild or moderate COVID-19 pneumonia: A structured summary of a study protocol for a randomised controlled trial. Trials 2021; 22:270.

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Ouma LO, Grayling MJ, Zheng H, Wason J (2021). Treatment allocation strategies for umbrella trials in the presence of multiple biomarkers: A comparison of methods. Pharm Stat 2021; doi:10.1002/pst.2119.

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Lee KM, Brown LC, Jaki T, Stallard N, Wason J (2021). Statistical consideration when adding new arms to ongoing clinical trials: The potentials and the caveats. Trials 2021; 22:203.

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Fonagy P, Yakeley J, Gardner T, Simes E, McMurran M, Moran P, Crawford M, Frater A, Barrett B, Cameron A, Wason J, Pilling S, Butler S, Bateman A (2020). Mentalization for Offending Adult Males (MOAM): Study protocol for a randomized controlled trial to evaluate mentalization-based treatment for antisocial personality disorder in male offenders on community probation. Trials 2020; 21:1001.

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Ward M, Grayling M, Wason J, Welton NJ, Haji-Ali AL, Jalal H, Thom H (2020). PSU4 Value of information for adaptive trials: Proof of concept study in multi-arm multi-stage trials of interventions for the prevention of surgical site infections. Value Health 2020; 23:S738.

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Witham MD, Anderson E, Carroll CB, Dark PM, Down K, Hall AS, Knee J, Maher ER, Maier RH, Mountain GA, Nestor G, O'Brien JT, Oliva L, Wason J, Rochester L (2020). Ensuring that COVID-19 research is inclusive: Guidance from the NIHR INCLUDE project. BMJ Open 2020; 10:e043634.

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Lin C-J, Wason JMS (2020). Efficient analysis of time-to-event endpoints when the event involves a continuous variable crossing a threshold. J Stat Plan Infer 2020; 208:119-29.

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Wason JMS, Robertson DS (2020). Controlling type I error rates in multi-arm clinical trials: A case for the false discovery rate. Pharm Stat 2020.

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McMenamin M, Grayling MJ, Berglind A, Wason JMS (2020). Increasing power in the analysis of responder endpoints in rheumatology: a software tutorial. medRxiv 2020.

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Cherlin S, Wason JMS (2020). Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores. Stat Med 2020; 39:3285-98.

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Stallard N, Hampson L, Benda N, Brannath W, Burnett T, Friede T, Kimani PK, Koenig F, Krisam J, Mozgunov P, Posch M, Wason J, Wassmer G, Whitehead J, Williamson SF, Zohar S, Jaki T (2020). Efficient adaptive designs for clinical trials of interventions for COVID-19. Stat Biopharm Res 2020; 12:483-97.

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Lee KM, Wason J (2020). Including non-concurrent control patients in the analysis of platform trials: Is it worth it?. BMC Med Res Methodol 2020; 20:165.

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Robertson DS, Wason JMS, Bretz F (2020). Graphical approaches for the control of generalised error rates. Stat Med 2020.

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Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK, Nicholl JP, Coates E, Biggs K, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG (2020). The Adaptive designs CONSORT Extension (ACE) statement: A checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. BMJ 2020; 369:m115.

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Wason J, McMenamin M, Dodd S (2020). Analysis of responder-based endpoints: improving power through utilising continuous components. Trials 2020; 21:427.

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