Session 6: Survival Analysis I

Lecture

Learning Objectives

1. Define main types of censoring
2. Define the assumption of uninformative censoring
3. Define survival function, hazard functions, cumulative event function
4. Perform a Kaplan-Meier estimate
5. Perform, interpret, and identify assumptions of the logrank test
6. Define and calculate potential follow-up time
7. Calculate median survival time

Outline

1. Introduction to censored data
   • Outcome variable: time-to-event
   • Types of censored data
   • Assumption of uninformative censoring
2. Survival function and Kaplan-Meier estimator
3. Comparing groups: Log-rank test

• Vittinghoff sections 3.1-3.5
• Tutorial Paper Survival Analysis Part I: Basic concepts and first analyses by Clark, Bradburn, Love, Altman. British Journal of Cancer (2003) 89, 232 – 238

Lab

Learning Objectives

1. Calculate Kaplan-Meier estimates of survival probability over time
2. Plot survival curves for censored time-to-event data
3. Perform and interpret log-rank test
4. Define "informative" censoring

Exercises

1. Calculate the follow-up table for 6 MP patients in the leukemia study
2. Plot the Kaplan-Meier estimate of the follow-up table from 1. library(survminer) is recommendable.
3. What is the 75th percentile of survival times for the 6 MP group? For the Placebo group? This is the time that 75% of the patients survive.
4. Suppose you were instructed to cap follow-up times at 20 weeks. Re-do the Kaplan-Meier plot for both groups, and re-do the logrank test.
5. Give a hypothetical example of how censoring in this example might be "informative."