Florence Nightingale Colloquium presents Eni Musta
- vrijdag 17 december 2021
- The seminar is targeted at a broad audience, in particular we invite master students, PhD candidates and supervisors interested or involved in the Data Science Research programme as well as colleagues from LIACS and MI to attend. The seminar is organized by the DSO, MI and LIACS.
- Florence Nightingale Colloquium
- Online only
Cure rate models: long-term survival of cancer patients
Survival analysis is a branch of statistics that studies the time until a certain event of interest. In oncology, such event is cancer relapse or cancer related death. However, thanks to recent medical advances, curative cancer treatments are now a possibility meaning that some patients will not experience cancer relapse during their lifetime. This poses new types of questions such as: What are the chances that a patient is cured? Does a treatment cure more patients or just prolong their life? Answering them is crucial, particularly in childhood oncology, but at the same time also statistically challenging because, since it is not possible to follow all patients throughout their life, we cannot determine who is cured. Cure rate models have been developed as an alternative modelling approach for survival analysis that accounts for the presence of cured patients. In this talk I will give an introduction into cure models and explain how the additional insights they provide can help in counselling patients and treatment decision making. I will illustrate this through a study of childhood osteosarcoma.
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