Learning Objectives:  To understand the basic principles of survival analysis and Kaplan Meier
curves, including:
 The advantages of using survival analysis
 How to create a survival table and KaplanMeier curve
 How to critically analyze studies that use survival analysis
Reading: Questions:
 In
what kind of studies do we use survival analyses or KaplanMeier analyses?
 What
are some of the advantages to analyzing data using survival analysis?
 What
is censoring? When does it occur? Why is censoring important in survival
analysis?
In the article by Lee, et al.:
 What
study outcome is analyzed using a survival analysis method and KaplanMeier
curve?
 How
was “death” or “failure” defined?
 What are other ways that this study outcome could
have been analyzed (e.g. other than using survival analysis)?
 How would another type of analysis be better
than survival analysis?
 How
would another type of analysis be worse than survival analysis?
 Why
is there such a steep decline in the KaplanMeier curve (Figure 1) at 1
week?
In the article by Alford,
et al.:
 In
12 sentences, describe the study findings demonstrated in Figure 1.
 What
study outcome is analyzed using a survival analysis method and Kaplan
Meier curve?
 How
was “death” or “failure” defined?
 In
what situation(s) were data censored? Do you agree with why/how the
authors censored data?
 In the results section on p. 75, the authors
state that the mean duration of treatment retention for both the homeless
and housed groups was 9 months (180 days). How/why does the KaplanMeier
curve in Figure 1 extend out to 350 days?
 From the KaplanMeier curve in Figure 1, what is
the 3month (90day) treatment survival rate for both groups? What is the
12month (350day) treatment survival rate for both groups? How does this
compare to what the authors state in the results section in terms of
remaining in treatment at 3 and 12 months? Why is there a discrepancy?
