Survival Analysis for Decision Making CPD Course
Dates: TBC
Following on from the successful delivery of the Survival Analysis for Decision Making CPD course in 2021 and 2022 with Delta Hat, we are delighted to be running the course again (dates TBC). The course will run virtually and is designed with special attention to the issues that are posed in applications of survival analysis and is informed by a rich programme of statistical and conceptual examples.
This course has been developed as a collaboration between PenTAG, the Peninsula Technology Assessment Group (University of Exeter), a longstanding HTA unit providing advice to NICE, and Delta Hat, a leading consultancy in health economics and evidence-based medicine.
About the course
Survival analysis, or the analysis of time-to-event data, is a central part of health technology assessment (HTA), with important implications both for understanding the clinical effectiveness of treatments and for modelling their cost-effectiveness.
This course is especially designed for HTA assessors, medical affairs specialists, Health Economics and Outcomes Researchers among other professionals in the field of HTA. It is led by experts from two groups: Peninsula Technology Assessment Group (PenTAG) at the University of Exeter and Delta Hat. PenTAG has been providing advice to NICE on the clinical and cost-effectiveness of drugs and other interventions since 2001, while Delta Hat is a cutting-edge consultancy comprised of economists and statisticians working in HTA. Both groups have been working together to share their strengths since 2018, having developed a strong record of collaboration to better meet the needs of NICE and the NHS through timely, innovative approaches to HTA.
The course is designed with special attention to the issues that are posed in applications of survival analysis and is informed by a rich programme of statistical and conceptual examples. The audience will engage with expert knowledge on the role of survival analysis in the HTA process on multiple perspectives.
Learning outcomes
- Learn and implement key survival analysis methods in R statistical software (assuming little or no prior knowledge)
- Critically appraise applications of survival analysis in the HTA context
- Understand how survival analysis informs economic modelling
- Develop strategies for the extrapolation of time-to-event data
- Apply learning techniques and examples in future projects
Testimonials
Read what previous delegates have said about the course:
“This course was well thought out and structured, with the perfect balance of theory and interactive practical sessions focused on the application of survival analysis methods in R Studio. The content was comprehensive, well explained, and delivered in a very clear and accessible way. Courses with such a technical focus are relatively hard to find - I would highly recommend to colleagues and other Health Economists wanting a hands-on practical course.”
“Brilliant to find an interactive course tailored to improving skills for conducting and critiquing survival analysis. The live examples and R code have been so helpful for applying new skills to our own data. I would highly recommend to those with a technical and/or strategic interest in survival analysis.”
“G. J. and Ash were fantastic teachers and I learned more about survival analysis than I did in my entire masters! I really appreciated the help and the opportunities to ask questions about the course. They both emphasised that no question was small enough, enabling me to ask questions I had never thought I could before.”
Please find below the programme from the February 2022 iteration of the course. The next course may have minor amendments.
Pre-Course - Wednesday 26th January 2022
| 14:00 - 16:30 |
This optional preparation session will be for troubleshooting any queries or issues with the R statistical software. |
Day 1 - Wednesday 2nd February 2022
| 09:00 - 09:30 | LOG ON |
| 09:30 - 09:45 | Welcome and Goals |
| 09:45 - 10:15 | Describing and depicting time to event data • What are ‘time-to-event’ data? • The Kaplan-Meier plot and its interpretation • Basic tests of difference and what they do and don’t tell you |
| 10:15 - 10:45 | Practical 1: Interpreting and understanding KM plots |
| 10:45 - 11:00 | Questions and consolidation |
| 11:00 - 12:00 | From difference to inference • Introducing the hazard ratio • What do we mean by hazards? • Testing and depicting the proportional hazards assumption • Introducing accelerated failure time as counterpart to hazard ratios |
| 12:00 - 12:30 | Practical 2: Fitting and checking proportional hazards models |
| 12:30 - 13:30 | LUNCH |
| 13:30 - 13:45 | Practical 2 wrap-up |
| 13:45 - 14:15 | Questions and consolidation |
| 14:15 - 15:15 | From estimation to extrapolation • Semiparametric to fully parametric models • Introducing parametric distributions: what are they and how do they work? • Revisiting accelerated failure time in parametric models • Fitting models with flexsurvreg • Standard models with 1 arm • Including covariates • Extracting parameters • Obtaining key metrics (e.g. survival at time X, median survival time, restricted mean survival time) • Parametric models and extrapolation |
| 15:15 - 15:30 | BREAK |
| 15:30 - 16:30 | Practical 3: Fitting and checking parametric survival models |
| 16:30 - 17:00 | Questions, consolidation and close. |
Day 2 - Thursday 3rd February 2022
| 09:00 - 09:15 | LOG ON |
| 09:15 - 09:30 | Overnight musings |
| 09:30 - 10:30 | Key issues in extrapolation |
| 10:30 - 11:00 | Practical 4: Revisiting extrapolations for parametric survival models |
| 11:00 - 11:15 | Questions and consolidation |
| 11:15 - 12:00 | Implementing standard parametric models in an Excel model • Information required • Dealing with parameter uncertainty • Obtaining estimates of mean survival |
| 12:00 - 12:15 | BREAK |
| 12:15 - 13:00 | Practical 5: Excel and parametric models |
| 13:00 - 14:00 | LUNCH |
| 14:00 - 14:15 | Questions and consolidation |
| 14:15 - 15:00 | Other modelling considerations • Time horizons • Estimation of QALYs within a partitioned-survival analysis • Adjusting extrapolations for background mortality |
| 15:00 - 15:15 | BREAK |
| 15:15 - 16:15 | Making fair comparisons; Alternative models used in NICE appraisals • Piecewise models • Spline-based models • Mixture-cure models • Landmark models |
| 16:15 - 17:00 | Questions and consolidation; Open forum and close |
Speakers
Ash Bullement
Ash is an Associate at the University of Exeter (collaborating with PenTAGon NICE assessments), and a health economics analyst at Delta Hat, an independent consultancy focusing on the technical aspects of evidence-based medicine and health technology assessment. Ash has a background in Mathematics, Operational Research and Statistics (Cardiff University); and also holds an MSc in Health Economics and Decision Modelling(University of Sheffield). He has over seven years experience from a consultancy and industry perspective, and his work is predominantly concerned with survival analysis and economic modelling, with a particular focus on cancer medicines.
Recent publications
- Cranmer H, Shields GE, Bullement A. A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology. J Med Econ.2020 Jul 30:1-10.
- Bullement A, Willis A, Amin A, et al. Evaluation of survival extrapolation in immuno-oncology using multiple pre-planned data cuts: learnings to aid in model selection.BMC Med Res Methodol. 2020 May 6;20(1):103.
- Gladwell D, Bullement A, Cowell W, et al. “Stick or Twist?” Negotiating Price and Data in an Era of Conditional Approval. Value Health. 2020 Feb;23(2):191-199.
Prof G.J. Melendez-Torres
Louise Crathorne
Louise is a Senior Research Fellow in health technology assessment (HTA) and Associate Director of Peninsula Technology Assessment Group (PenTAG) at the University of Exeter. Louise has worked in consultancy, industry and academia. She has over 15 years experience within HTApredominantly for the UK setting (NICE, Scottish Medicines Consortium[SMC], All Wales Medicines Strategy Group [AWMSG]), but also for other HTA agencies including the Zorginstituut Nederland ZIN, The Netherlands), National Centre for Pharmacoeconomic Evaluation (NCPE, Republic of Ireland). She also has experience as a SeniorSystematic Reviewer for the National Guidelines Alliance (NGA), working to produce NICE clinical guidelines, and of conducting other types of evidence synthesis for decision makers, such as the NHS (North, East and West [NEW] Devon Clinical Commissioning Group). Louise has an MSc in Health Economics and Health Policy.
Recent publications
- Farmer C, Bullement A, Packman D, Long L, Robinson S, Nikram E et al.. VoretigeneNeparvovec for Treating Inherited Retinal Dystrophies Caused by RPE65 Gene Mutations: An Evidence Review Group Perspective of a NICE Highly Specialised Technology Appraisal.Pharmacoeconomics 2020, doi: 10.1007/s40273-020-00953-z
- Tikhonova IA, Huxley N, Snowsill T, Crathorne L, Varley-Campbell J, Napier M et al. EconomicAnalysis of First-Line Treatment with Cetuximab or Panitumumab for RAS Wild-Type MetastaticColorectal Cancer in England. Pharmacoeconomics 2018; 36(7):837-851
- Dabbous O, Wight C, Crathorne L, Qadan A. Progression-free survival is a predictor of survival in patients with untreated metastatic pancreatic cancer: A systematic literature review.Ann Oncol 35(15 suppl): e15724
Contact us
For a full programme and/or any other enquiries about the course, please email us or call +44 (0)1392 722964
G. J. and Ash were fantastic teachers and I learned more about survival analysis than I did in my entire masters! I really appreciated the help and the opportunities to ask questions about the course. They both emphasised that no question was small enough, enabling me to ask questions I had never thought I could before.
Delegate
February 2022
The lecturing was fantastic! I also really appreciated the different experiences G.J. and Ash brought to the table because they covered a range of academic and industry perspectives.
Delegate
February 2022
"I’m currently undertaking an MSc in Economic Evaluation and this course really cemented survival analysis for me. I could not have done my dissertation without it."
January 2021 Delegate
"Courses with such a technical focus are relatively hard to find - I would highly recommend to colleagues and other Health Economists wanting a hands-on practical course."
January 2021 Delegate
"The live examples and R code have been so helpful for applying new skills to our own data. I would highly recommend to those with a technical and/or strategic interest in survival analysis. "
January 2021 Delegate
