Course Advanced Survival Analysis

April 14-17, Leiden


“It takes time to observe time” is the famous quote of one of the pioneers in the development of survival analysis, Odd Aalen. The consequence of this trivial fact is profound: it implies right-censoring.  For basic outcomes, the Kaplan-Meier estimate of the survival curve, the log-rank test for testing equality of survival curves and Cox’s proportional hazards regression model are standard tools. However, for many common situations these techniques do not suffice, e.g., when more than one event is considered, when the effects of risk factors or treatments change over time, when patients are clustered in groups or when a patient population is compared to the general population.

This course goes beyond the fundamental techniques in survival analysis, and considers a wide range of more specialized topics, such as non-proportional hazards and time-dependent covariates, competing risks and multi-state models, landmarking and dynamic prediction, pseudo-observations, frailty models, survival analysis in clinical trials, informative censoring and inverse probability weighting, Poisson regression, multiple time scales, and relative survival. There will be a balance between concepts, mathematical background, implementation and interpretation. To ensure the relevance for clinical practice, almost all clinical examples discussed come from the collaborative work of the teachers with clinicians. The majority of these examples is dedicated to the analysis of outcomes after stem cell transplantation. The generalizability to other fields of application will be discussed.


  • Hein Putter (Leiden University Medical Center)
  • Liesbeth de Wreede (Leiden University Medical Center)


  • Liesbeth de Wreede (Leiden University Medical Center)
  • Hein Putter (Leiden University Medical Center)
  • Henning Baldauf (DKMS Clinical Trials Unit, Dresden)
  • Nan van Geloven (Leiden University Medical Center)
  • Simona Iacobelli (Rome University “Tor Vergata”)

Topics covered

The course material will be presented in a lecture format, changing between theory and illustrations. Ample attention will be devoted to the practical implementation of the methods covered in the course, by use of R. The lectures will be interspersed with computer practicals in R.

Topics covered include:

  • Introduction: Survival analysis, pitfalls and solutions
  • Competing risks
  • Time-dependent covariates in Cox regression models and landmarking
  • Non-proportional hazards/pseudo-observations
  • Multi-state models
  • Dynamic prediction
  • Frailty models
  • Survival analysis in clinical trials
  • Informative censoring/IPW
  • Estimands in competing risks
  • Poisson models, multiple timescales
  • Relative survival

Learning strategy

The material will be presented using slides and through class discussion. All slides, which will contain clear descriptions of the methodology, of applications, and of how to implement analyses in R, and exercise material will be made available.


This course is directed at statisticians, epidemiologists and clinicians with a good background in statistics. Participants are expected to have a fair knowledge of the standard techniques from survival analysis. Interest in stem cell transplantation can be helpful, but is not necessary.

About the instructors

Hein Putter is full professor at the Leiden University Medical Center (Department of Biomedical Data Sciences). His research interests include competing risks and multi-state models, frailty models and dynamic prediction. He is co-author of the book “Dynamic Prediction in Clinical Survival Analysis”, with Hans van Houwelingen.

Liesbeth de Wreede is assistant professor in medical statistics at Leiden University Medical Center. She mainly works in survival analysis, with a special interest in competing risks and multi-state models, relative survival and methods for missing data. She collaborates with several organizations in the field of haematology.

Henning Baldauf is the team leader of Data Management and Statistics at the DKMS Clinical Trials Unit in Dresden, Germany. He is a statistician working in the field of allogeneic stem cell transplantation with a special interest in heterogeneity in clinical trials.

Nan van Geloven is assistant professor in biostatistics at Leiden University Medical Center. Her statistical research interests are in survival analysis (informative censoring, dynamic survival prediction, competing risks) and in the evaluation of treatments from observational data. Her main application area is in Reproductive Medicine.

Simona Iacobelli is assistant professor in Medical Statistics at Rome University “Tor Vergata”. Her statistical research interests are in survival analysis (time-dependent treatments and multiple events) and in clinical trials. Her main application area is in onco-haematology and stem cell transplantation.


The course will take place at the Education Building of the Leiden University Medical Center (LUMC). More detailed information about the schedule and location will be provided upon registration.

Course prices

  • For early registration, before 31/01/2020, costs are €800 (ISCB members €750)
  • For late registration costs are €900 (ISCB members €850)
  • If you have an affiliation to the LUMC, costs are €350
  • If you are affiliated with the EBMT, costs are €700


To register for the course, please fill in the form found via this link: Note that the number of places is limited and will be allocated on a first-come-first-serve basis. Your registration will be confirmed within 2 weeks.

If you have any questions regarding the course, feel free to send an e-mail to, stating ‘ASA’ in the subject line.