Survival analysis-part 2: Cox proportional hazards model

Abstract

Learning objectives: 1. To understand the log-rank test and limitations of the log-rank test in comparing survival between groups. 2. To understand the fundamental concepts of the proportional hazards assumption. 3. To understand basic steps in the development of the Cox proportional hazards model and reported hazard ratios. 4. To understand how results of a Cox model run using STATA© (a commonly used proprietary statistical software) can be understood and interpreted.

Supplementary information: The online version contains supplementary material available at 10.1007/s12055-020-01108-7.

Keywords: Biostatistics; Cox proportional hazards regression; Hazard rate; Survival analysis.

Fig. 1

This is an observational study comparing the all-cause mortality of post-surgical stage III lung cancer patients. The survival estimates of males and females in our cohort were calculated using the Kaplan and Meier estimates. This figure presents the estimated survival of males (red) and females (blue) with their respective 95% confidence intervals (colored bands). The difference in survival between these females and males was compared with the log-rank test (observed p value = 0.001)