Survival Analysis: Why? What? How?

Description and Objectives:

Survival analysis is a pillar in many health technology assessments, especially in the field of oncology. This half day course will provide participants with a comprehensive introduction to the basics of survival analysis. It will cover topics ranging from the interpretation of a Kaplan-Meier curve to addressing complex hazard patterns, using hands-on exercises to allow attendees to practice the application of different survival extrapolation methods.

The course will start by introducing the Kaplan-Meier (KM) curve and the interpretation of such curves. Theoretical concepts will be illustrated with real examples and participants will get hands-on experience with plotting KM curves, fitting a Cox model and evaluating the assumption of proportional hazards. This will allow practice with interpreting results of a trial dataset.

Special attention will be given to the hazards underlying the survival curves and these hazard curves will be used as a basis to discuss and compare different standard parametric models. Model selection is a key element of survival analysis, and choices made in the model selection can have a strong impact on health technology assessments. The discussion will investigate technical aspects of the models, but also relate this to clinical interpretation. Participants will be provided with a dataset and some simple code with which to explore multiple parametric models themselves. A completed code set will be provided following the hands-on exercises.

Once the standard parametric models have been explored, the concept of complex hazard functions will be introduced as well as methods for modelling more complex survival data. The course will be wrapped up by highlighting the importance of validating survival analyses.\

Completing this course will allow participants to:

  1. Identify contexts in which survival analysis is relevant and appropriate

  2. Plot and interpret KM curves

  3. Assess the assumption of proportional hazards

  4. Extrapolate observed survival using standard parametric models

  5. Understand complexity in survival data and suggest appropriate methods for analysis

  6. Discuss the impact of choices made in the survival analysis

Register Now | Return to Short Course Listings

Become a Member

SMDM members contribute critically to health policy research in the areas of evidence-based medicine, cost effective health care, patient decision making and public health. SMDM helps you to be more than just a face in the crowd. The connections you make through SMDM can help you build a network of long-term contacts to help you throughout your career.

Learn More about Membership

Member Stories

Heather Taffet Gold, PhD
Heather Taffet Gold, PhD

"While my research is more methodological, I fully appreciate the exposure to clinical applications I get at SMDM."

 continue »

MDM Journal

MDM Journal

MDM offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health policy development.

Learn More >