Statistical methods for survival data: accounting for cured patients
Survival analysis is a branch of statistics that analyzes time-to-event data, where the variable of interest is the time until occurrence of a certain event, e.g. time to cancer relapse/death. It helps us answer questions like:
-What percentage of cancer patients will survive more than 4 years?
-Which factors affect the survival time of cancer patients?
Even though the main motivation comes from the medical setting, survival analysis is used in a variety of fields. In this talk, I will focus on situations where a fraction of the population never experiences the event of interest. Cure rate models have been introduced as an alternative modelling approach that accounts for the presence of cure, i.e. the possibility that the event never happens. They can provide additional insights with respect to the traditional methods and are of particular interest in studies of some cancer types for which advanced medical treatments can lead to cure from the disease.
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