Survival Analysis

Question 1

Survival Time

Answer 1

• Time to an event

- The time starting from a defined point to the occurrence of a given event

Question 2

Events for the end of survival time include

Answer 2

death
disease occurrence
disease recurrence
recovery
other experience of interest

Question 3

Special features in survival time data

Answer 3

• rarely normally distributed
• often skewed
• typically with many early events and relatively few late ones

Question 4

Censored Observations

Answer 4

Those who have not yet reached the terminal event by the end of the study.

Question 5

In censored observations, why might information about a pt’s survival time be incomplete?

Answer 5

• pt hasn’t experienced event by end of study
• pt lost to follow up during study period
• pt experiences different event to make further follow up impossible

Question 6

Issues with censored observations in analysis

Answer 6

these censored survival times will underestimate the true (but unknown) time to the event because it will occur beyond the end of the study.

Question 7

Kaplan-Meier Curve

Answer 7

• visualize estimate of survival over time
• shows probability of an event at a certain time interval
• x-axis for time, y-axis for ‘proportion surviving’
• step function, as the cumulative survival remains the same until the day another person experiences the event

Question 8

Kaplan-Meier Curve Censored Data

Answer 8

x-axis: time
y-axis: ‘proportion surviving’
-step function
-censored observations indicated on K-M curve as “tick marks”
-censored observations do not terminate the interval

Question 9

Kaplan-Meier Curve for 2 Groups

Answer 9

Visualizes the difference between two survival curves. Can be used to compare treatments.

Question 10

Median Survival Time

Answer 10

estimated as small survival time for which survival function is less than or equal to 0.5

Question 11

How can you estimate the Median Survival Time?

Answer 11

1. find the 50% mark on the proportion axis
2. drawing a horizontal line at 50% to find the crossing point with the K-M curve
3. drawing a vertical line at the crossing point down to the time axis to read time

Question 12

Mean Survival Time

Answer 12

• area under survival curve
• may not be best estimate for sample of survival times, highly skewed
• median typically better measure of central location than mean

Question 13

Hazard Rate

Answer 13

• measure of how often an event happens in one group compared to another
• in clinical trials, measures survival point at any point in time in a group given treatment vs control
• can be estimated as being a slope of a K-M curve

Question 14

Interpreting Hazard Ratio

HR = 1

Answer 14

the event rates are the same in both groups

Question 15

Interpreting Hazard Ratio

HR >1

Answer 15

the event rate in the treatment group is faster than in the control group

Question 16

Interpreting Hazard Ratio

HR < 1

Answer 16

event rate in treatment group is slower than in the control group

Question 17

Log-Rank Test

Answer 17

Compares two or more samples with survival data in presence of censored observations

Question 18

How can a log-rank test fail

Answer 18

if two curves cross (no statistical power)

Question 19

Assumption of Log-Rank Test

Answer 19

Hazard Rates of the groups to compare must be proportional

Question 20

Limitations of Log-Rank Test

Answer 20

• We can only test one variable at a time
• can’t control for potential confounders
• can’t control for other potential risk factors
• can’t include interaction terms

Question 21

Cox Proportional Hazard Model

Answer 21

Most commonly used method comparing two or more samples with survival data in presence of censored observations

Question 22

T/F: Cox model can accommodate only one confounding variable

Answer 22

False

can accommodate any number of confounding variables

Question 23

T/F: Cox Model provides the estimate of Hazard Rate with its associated 95% Confidence Interval

Answer 23

True

Question 24

Assumption of Cox Model

Answer 24

The ratio of the hazard functions for any two observations does not vary with time.