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A Nonparametric Statistical Method for Two Crossing Survival Curves by Huang, Xinghui; Lyu, Jingjing; Hou, Yawen; Chen, Zheng is a Mathematics article available to read on EtoBox.

What is A Nonparametric Statistical Method for Two Crossing Survival Curves about?

Background: In comparative research on time-to-event data for two groups, when two survival curves cross each other, it may be difficult to use the log-rank test and hazard ratio (HR) to properly assess the treatment benefit. Our aim was to identify a method for evaluating the treatment benefits for two groups in the above situation. Methods: We quantified treatment benefits based on an intuitive measure called the area between two survival curves (ABS), which is a robust measure of treatment benefits in clinical trials regardless of whether the proportional hazards assumption is violated or two survival curves cross each other. Additionally, we propose a permutation test based on the ABS, and we evaluate the effectiveness and reliability of this test with simulated data. Results: The ABS permutation test is a robust statistical inference method with an acceptable type I error rate and superior power to detect differences in treatment effects, especially when the proportional hazards assumption is violated. ## Conclusion: The ABS can be used to intuitively quantify treatment differences over time and provide reliable conclusions in complicated situations, such as crossing survival

Who reads A Nonparametric Statistical Method for Two Crossing Survival Curves?

Author

Huang, Xinghui; Lyu, Jingjing; Hou, Yawen; Chen, Zheng

Publisher

Taylor and Francis Group; Informa UK (Taylor & Francis); Dekker; Informa UK Limited (ISSN 0361-0918)

Published

2020

Language

EN

Field

Mathematics (Physical Sciences)