Darren Burns joins Delta Hat
We are pleased to welcome Darren Burns to the Delta Hat team. Darren is a modeller and statistician who joins from another consultancy, bringing experience working across a range of disease areas. He will be working on a combination of statistical analyses and health technology assessment, adding to our capability and capacity.
Academic Work
Darren’s previous academic work is varied, ranging from his thesis on international trade and population health in low and middle income countries to cost-effectiveness analyses of health interventions in the UK (1–3).
Since moving into consultancy in 2016, Darren has continued to produce varied academic work including registry data and meta-analysis of health-state utilities, evaluating the usefulness of mixture-cure models, and even discussing the use-case for moving to web applications from Excel for HTA (4-8).
HTA Work
Darren has been involved in a series of complex HTA projects since moving into consultancy in 2016 across a range of disease areas:
| Disease area | Role | Model & statistics |
|---|---|---|
| Non-small cell lung cancer | Led modelling and SMC submission, modeller and writer for NICE submission | 4-state partitioned survival model, separating post-progression by CNS metastases |
| Mylofibrosis | Led modelling and NICE submission writing | Patient-level discrete event simulation in Excel+VBA |
| Glioblastoma | Early modelling & feasibility assessment | 3-state partitioned survival models |
| Gastrointestinal stromal tumours | Led modelling, statistics and NICE submission writing | 3-state partitioned survival model, parametric survival models applied to data matched using inverse propensity score weighting |
| Leukemia | Modeller & reviewer on several CAR-T models | 3-state partitioned survival model, mixture-cure models |
| Small-bowel syndrome | Modeller and NICE submission writer | Markov model for transitions between living states, with separate mortality modelling |
| Peanut allergy | Led modelling and NICE submission writing | Markov model for transitions between living states, with separate mortality modelling |
| Neovascular macular degeneration | Lead modeller | Patient-level simulation of continuous parallel correlated outcomes in R |
| Interstitial lung disease | Modeller & reviewer | Patient level simulation of continuous health outcome in Excel+VBA |
| Antimicrobial resistant infections (gram negative, carbapenem resistant) | Led modelling and co-wrote NICE AMR de-linkage pilot submission | Complicated patient and population level simulation in R |
Hobbies
Darren likes climbing rocks, wild swimming, cooking, and making his own beer. Finally, Darren likes playing around with code.
References
- Burns, D. K., Jones, A. P., & Suhrcke, M. (2016). The relationship between international trade and non-nutritional health outcomes: A systematic review of quantitative studies. Social Science & Medicine, 152, 9–17. https://doi.org/http://dx.doi.org/10.1016/j.socscimed.2016.01.021
- Burns, D. K., Jones, A. P., Goryakin, Y., & Suhrcke, M. (2017). Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach. Social Science & Medicine, 181, 74–82.
- Burns, D. K., Edward F Wilson, B. C., Paula Browne, B., Sandra Olive, B., Allan Clark, B., Penny Galey, B., Emma Dix, B., Helene Woodhouse, B., Sue Robinson, B., & Andrew Wilson, B. (2016). The Cost Effectiveness of Maintenance Schedules Following Pulmonary Rehabilitation in Patients with Chronic Obstructive Pulmonary Disease: An Economic Evaluation Alongside a Randomised Controlled Trial. Appl Health Econ Health Policy, 14, 105–115. https://doi.org/10.1007/s40258-015-0199-9
- Hart, R., Burns, D., Ramaekers, B., Ren, S., Gladwell, D., Sullivan, W., Davison, N., Saunders, O., Sly, I., Cain, T., et al. (2020). R and Shiny for cost-effectiveness analyses: Why and when? A hypothetical case study. PharmacoEconomics, 38(7), 765–776.
- Grant, T. S., Burns, D., Kiff, C., & Lee, D. (2020). A case study examining the usefulness of cure modelling for the prediction of survival based on data maturity. Pharmacoeconomics, 38(4), 385–395.
- Hatswell, A. J., Burns, D., Baio, G., & Wadelin, F. (2019). Frequentist and Bayesian meta-regression of health state utilities for multiple myeloma incorporating systematic review and analysis of individual patient data. Health Economics, 28(5), 653–665.
- Burns, D., Lee, D., Vesely, S., George, J., Cerdobbel, A., De Naeyer, L., & Heylen, J. (2018). PSY192-PATIENT HEALTH-RELATED QUALITY OF LIFE ASSOCIATED WITH REMISSION OF ATTP, a REGRESSION ANALYSIS USING NON-RANDOMISED OBSERVATIONAL DATA FROM THE OKLAHOMA TTP REGISTRY. Value in Health, 21, S469.
- Porter, J. K., Burns, D., Di Tanna, G. L., Lipton, R. B., Palmer, S., Sapra, S., & Villa, G. (2018). PRM154-MODELING MIGRAINE DAY FREQUENCY BY RESPONDER STATUS: A RE-ANALYSIS OF DATA FROM ERENUMAB CLINICAL TRIALS. Value in Health, 21, S382.