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Activity Number: 88 - Data Visualization in Practice
Type: Contributed
Date/Time: Monday, August 9, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Graphics
Abstract #318331
Title: Two-Sample Survival Probability Curves: A Graphical Approach for Time-to-Event Data in Clinical Trials
Author(s): Sandra Castro-Pearson* and Xianghua Luo and Chap Le
Companies: University of Minnesota and University of Minnesota and University of Minnesota
Keywords: survival; clinical trials; model fit; time to event outcome; graphical assessment; Kaplan-Meier

With the aim to improve the communication of trial results, we introduce a novel graphical approach that complements the analysis of time to event outcomes in two-arm randomized trials. We define the so-called two-sample survival probability curve and propose a nonparametric estimator of the curve based on a random walk using Kaplan-Meier survival estimates for the two arms. We then use the estimated curve to visualize treatment effect as well as potential effect modification of factors of interest. We also propose to estimate two-sample survival probability curves within the framework of the Cox model to graphically assess model fit. The proposed two-sample survival probability plot puts trials in a standardized [0,1]×[0,1] space, allowing for a simple visualization of the main effect, effect modification, and the adequacy of a model fit.

Authors who are presenting talks have a * after their name.

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