Survival Analysis [ESP28]

Detailed information about this course:

Description

Faculty: Prof. Hein Putter, PhD 

This course will not be scheduled during the Erasmus Summer Programme in August 2017.

Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). Survival analysis is most prominently (but not only) used in the biomedical sciences.A special feature of survival data is that it takes time to observe the event of interest. A result of this seemingly innocent observation is that for a number of subjects the event is not observed, but instead it is known that it has not taken place yet. This phenomenon is called censoring and it requires special statistical methods.

During the course different types of censored and truncated data will be introduced and techniques for estimating the survival function by employing both parametric and non-parametric methods will be illustrated. Also techniques for testing equality of survival functions (the log-rank test and alternatives) are discussed. Finally regression models for survival analysis, based on the hazard function (most notably the Cox proportional hazards model), will be studied in great detail.Special aspects such as time-dependent covariates and stratification will be introduced. Techniques to be used to assess the validity of the proportional hazards regression model will be discussed. The last part of the course touches on models for multivariate survival analysis, including competing risks and multi-state models and frailty models. Finally, aspects of the planning of clinical trials with lifetime data will be discussed.

Teaching methods:

All aspects of the course will be illustrated with real data examples and will be practiced with computer practicals and/or pen-and-paper exercises.

Written exam on Friday 2 September 2016 (only for NIHES MSc students and for ‘keuzevak students’), date resit is to be announced. Course materials are allowed during the examination. If other students wish to do this exam, they have to pay a fee of €75,- per exam. Credits are 1.9 ECTS when you take the exam, instead of 1.4 ECTS.

This course is equivalent to Survival Analysis for Clinicians (EWP24).

Objectives

After competing this course the student should:

• Understand the concept of censoring and its implications for statistical analysis;
• Be familiar with the most important techniques in survival analysis, such as the Kaplan-Meier estimate, the log-rank test and proportional hazards regression;
• Understand the underlying assumptions and limitations of these techniques;
• Be able to perform statistical analysis of time-to-event data and interpret the results
  

Participant profile

Clinicians who are involved in clinical research with time-to-event data or want to learn the concepts and techniques for the analysis of such data.

Assessment

Attendance, Written exam