Emily Zabor - Reporting Survival Analysis Results with the gtsummary and ggsurvfit Packages

Reporting Survival Analysis Results with the gtsummary and ggsurvfit Packages by Emily Zabor

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Abstract: Survival analysis is an essential tool to handle censored time-dependent endpoints such as overall survival, which are common across a variety of biomedical and other applications. The survival package in R provides the most essential tools to conduct a survival analysis, including estimating survival probabilities, fitting Cox proportional hazards models, and plotting Kaplan-Meier curves. While the functions are powerful, user-friendly, and well documented, getting publication-ready tables and figures can still be a challenge. In this talk, I will review the basics of survival analysis, and will demonstrate how to take results from the console to the manuscript using the gtsummary and ggsurvfit packages.

Bio: Emily is an Associate Staff Biostatistician at Cleveland Clinic in the Department of Quantitative Health Sciences. Emily primarily works in applied cancer research, and her methodologic research is focused on early phase clinical trial design and statistical methods for observational studies using survival endpoints.

Twitter:   / clevelandclinic  

Presented at the 2024 New York R Conference (May 16, 2024)
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