Cancer Survival Analysis

Day 1 (November 6, 2017)
Concept of time to event analysis
Descriptive analysis (Life table, Kaplan Meier, Median survival, Log rank)
Regression: semi-parametric vs parametric

Cancer survival analysis: clinical trial data, hospital-based data, population-based data
Core measures of cancer surveillance (Incidence, Survival, Mortality)
Bias (lead time, length time, overdiagnosis)
Population-based cancer survival: importance and use


Day 2 (November 7, 2017)
Overall survival
Cancer prognosis (remove competing causes of death): relative survival, cause-specific survival
Actual prognosis (include competing causes of death)
Relative survival ratio and Net survival: Ederer I, Ederer II, Hakulinen, Pohar Perme
Age-standardized relative survival (Standard cancer patient population)

Cohort vs Period vs Complete approach
Practice with given a data set
Practicum in relative survival analysis
Practicum in risk models for survival

Workshop materials