Survival Analysis

Learning Objectives

• 1. Incidence measures do not fully describe the development of events over time.

• 2. The survival function, S(t) represents the probability of being alive at a particular time, t.

• 3. For a graphical presentation of the survival function:

  • a. Survival for any particular follow-up time is estimated by a vertical line to S(t).

  • b. Median survival is estimated by a horizontal line from S(t) = 0.5.

• 4. The logrank test evaluates whether whole survival curves are statistically different from each other.

• 5. Survival analysis is typically used to describe the first occurrence of a particular outcome.

• 6. Censoring occurs when a subject leaves a study before incurring the outcome of interest.

• 7. The Kaplan–Meier method is used to estimate S(t) in the presence of censoring.

• 8. Kaplan–Meier plots are typically unadjusted.

• 9. The Cox model can adjust for confounding and account for censoring.

• 10. The Cox model yields a hazard ratio, which very closely parallels the relative risk.

• 11. Hazard ratios are meaningful for studies in which the relative risk remains constant throughout the study period; studies with changing risks over time should present separate hazard ratios for the relevant time periods of interest.