Cancer Survival: Principles, Methods and Applications
This short course is run by the School's Cancer Survival Group.
A highly experienced international faculty will present a stimulating and intensive one-week course on the principles, methods and applications of cancer survival estimated with population-based cancer registry data. You will enjoy lectures and discussions, computer-based exercises with real data, daily review sessions and a session for participants to present their own work or ideas for debate. You will be provided with digital or printed copies of all lectures, practical exercises and solutions. For computer-based exercises, you will be expected to use your own laptop.
Net survival will be the main approach to analysis, with discussion of recent methodological developments. The methodological concepts of cancer survival will be illustrated by public health and policy applications throughout the week. Results from recent survival studies will be presented and their interpretation discussed.
The faculty will include internationally renowned experts in the field of cancer survival analysis and methods, and 10 researchers in the Cancer Survival Group. External faculty members will include:
- Prof Paul Dickman, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Dr Maja Pohar Perme, Institute of Biostatistics and Medical Informatics, University of Ljubljana, Slovenia
- Prof Jacques Estève, Professor Emeritus, Lyon-Sud University, Lyon, France
- to teach the main statistical methods for estimating population-based cancer survival
- to discuss the main controversies in estimation and interpretation of cancer survival
- to provide students with an intensive learning environment in which faculty members will attend all sessions of the course, not just their own
- to provide opportunities for computer-based practical analysis of real cancer data
Methods and topics
- measures of the cancer burden (incidence, prevalence, mortality, survival, cure)
- all-cause (crude), net and relative survival and excess mortality hazard
- construction of abridged and complete life tables
- net survival estimation, including cohort, complete, period and hybrid approaches
- adjustment of cancer survival estimates for age and other factors
- impact of data quality, completeness, stage migration, screening and lead-time bias
- methods for handling missing data in cancer survival analysis
- avoidable premature deaths and population "cure"
- multi-variable modelling of relative survival, and comparison with Cox and Poisson approaches
- the UN Sustainable Development Goals for 2030
- public health interpretation of cancer survival trends and inequalities
Epidemiologists, statisticians, physicians and oncologists, public health specialists and others with a direct interest in applied cancer survival analysis, and particularly those working in a cancer registry.
You should have a basic understanding of cancer survival, since this course will include discussion of advanced statistical methods and practical computing, as well as discussion of the public health applications of cancer survival data.
We do not insist that you have a qualification in statistics, but some experience is essential for you to take full advantage of the statistical components of the course. All practical sessions will use Stata, so some experience of Stata should be considered essential. Free online video tutorials are available on the Stata website to introduce the basic functionality.
The applied public health elements of the course will be accessible and relevant to all groups.