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Updated: Nov 7, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Living With Survival Analysis in Orthopedics
Cynthia S Crowson1, Dirk R Larson2, Katrina L Devick3
1Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN; Division of Rheumatology, Mayo Clinic, Rochester, MN.
Abstract:
Time to event data occur commonly in orthopedics research and require special methods that are often called "survival analysis." These data are complex because both a follow-up time and an event indicator are needed to correctly describe the occurrence of the outcome of interest. Common pitfalls in analyzing time to event data include using methods designed for binary outcomes, failing to check proportional hazards, ignoring competing risks, and introducing immortal time bias by using future information. This article describes the concepts involved in time to event analyses as well as how to avoid common statistical pitfalls. Please visit the followinghttps://youtu.be/QNETrx8B6IUandhttps://youtu.be/8SBoTr9Jy1Qfor videos that explain the highlights of the paper in practical terms.
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