Jose Leal PhD, MSc
- Economic Evaluation
- Newborn Disease Screening
- Prostate Cancer Screening
- Hunter Jessica, Rivero-Arias Oliver, Angelov Angel, Kim Edward, Fotheringham Iain, and Leal Jose (2014) Epidemiology of fragile X syndrome: A systematic review and meta-analysis. Am J Med Genet A, 164(7):1648-58.
- Leal Jose, Hamdy Freddie, and Wolstenholme Jane (2014) Estimating age and ethnic variation in the histological prevalence of prostate cancer to inform the impact of screening policies International Journal of Urology , Epub (DOI: 10.1111/iju.12458).
- Leal Jose, Wordsworth Sarah, Oerton Juliet, Khalid Javaria M, and Dezateux Carol (2014) Synthesis framework estimating prevalence of MCADD and sensitivity of newborn screening programme in the absence of direct evidence. J Clin Epidemiol, Epub (pii: S0895-4356(14)00204-2. doi: 10.1016/j.jclinepi.2014.05.011).
- Leal J, Ades Ae, Wordsworth S, and Dezateux C (2013) Regional differences in the frequency of the c.985A>G ACADM mutation: findings from a meta-regression of genotyping and screening studies. Clin Genet.
- Leal Jose, Hayes Alison J, Gray Alastair M, Holman Rury R, and Clarke Philip M (2013) Temporal validation of the UKPDS outcomes model using 10-year posttrial monitoring data. Diabetes Care, 36(6):1541-6.
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José Leal joined the Health Economics Research Centre in January 2004, having completed his MSc in Health Economics at the University of York in 2003. Since joining HERC, José has worked on several projects, including an economic evaluation of genetic testing for sudden cardiac death, an economic evaluation of MS/MS screening for Medium Chain Acyl-CoenzymeA Dehydrogenase Deficiency, elicitation of expert opinion and several cost-of-illness studies.
José has recently completed a doctoral thesis at the University of Oxford on the use of multi-parameter evidence synthesis to inform economic evaluations. His current research interests include the use of expert opinion to inform decision models, evidence synthesis frameworks in economic evaluation and individual patient level modelling.