The team at Exploristics has an extensive publication record, with a selection of relevant examples listed below.

Speciality Statistics

  1. Watson, L. et al., Cart analysis as a tool to determine optimal treatment intensification time in diabetes. Value in Health 2015 11;18(7): A682. View
  2. Jenkins, R. G. et al., Longitudinal change in collagen degradation biomarkers in idiopathic pulmonary fibrosis: an analysis from the prospective multicentre PROFILE study.  Lancet Respir Med 2015; 3: 6: 462-472. View
  3. Maher, T. M. et al., An epithelial biomarker signature for idiopathic pulmonary fibrosis: an analysis from the multicentre PROFILE cohort study. Lancet Respir Med 2017; 5: 946-55. View
  4. Win, T. et al., Pulmonary 18F-FDG uptake helps refine current risk stratification in idiopathic pulmonary fibrosis (IPF). Eur J Nucl Med Mol I 2018; 45:806-15. View
  5. Alderton, W. et al., CA19.9 Profiles in Samples Predating Pancreatic Cancer Diagnosis – a Nested Case Control Study in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). View
  6. International Survey on Diabetic Retinopathy. View
  7. Meta-analysis on cardiovascular disease. View

Epidemiology and Real World

  1. Watson, L., et al., Consequences of delaying treatment intensification in type 2 diabetes: evidence from a UK database. Curr Med Res Opin 2016; 32(9), 1465-75. View
  2. Amber, V. et al., A database analysis of patients eligible for second-line lipid-lowering treatment for hypercholesterolaemia in England. Value in Health. 2014. 17(7): A476-A477. View
  3. Bushe, C. et al., Understanding the treatment of adult Attention Deficit Hyperactivity Disorder patients in general practice: A United Kingdom Database Study. Pragmatic and Observational Research 2015; 6: 1-12. View
  4. Chrystyn, H., et al., Device errors in asthma and COPD: systematic literature review and meta-analysis. NPJ Prim Care Respir Med 2017; 27 (1):22. View

Precision Medicine

  1. Flynn, A. Pharmacogenetics: practices and opportunities for study design and data analysis. Drug Discov Today 2011; 16 (19-20): 862-6. View
  2. Trusheim, M. et al., Quantifying factors for the success of stratified medicine. Nat Rev Drug Discov 2011; 10, 817-833. View
  3. Flynn, A. et al., Advances in Predictive, Preventive and Personalised Medicine. 2015 Vol 9 – Preventive and Predictive Genetics: Towards Personalised Medicine. Editors: Godfrey Grech and Iris Grossman ISBN: 978-3-319-15343-8 (Print) 978-3-319-15344-5.
  4. Olazarán et al. A Blood-Based, 7-Metabolite Signature for the Early Diagnosis of Alzheimer’s Disease. J Alzheimer’s Dis 2015; 45 (4): 1157–73. View
  5. Exploristics profile in Personalized Medicine 2015; 12 (6), 537-40. View
  6. Jenkins, M., et al., A statistician’s perspective on biomarkers in drug development. Pharm Stat 2011; 10 (6): 494-507. View

Other Relevant Capabilities

  1. Denny, F. et al., Rasch Analysis of the Daily Living Tasks Dependent on Vision (DLTV). Invest Ophthamol Vis Sci 2007; 48:1976-82. View
  2. Beatty, S. et al., Secondary Outcomes in a Clinical Trial of Carotenoids with Coantioxidants Versus Placebo in Early Age-Related Macular Degeneration. Ophthalmol 2013; 120 (3): 600-606. View