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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Statistical modelling for thoracic surgery using a nomogram based on logistic regression
Run-Zhong Liu1, Ze-Rui Zhao2, Calvin S H Ng2
1Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China ;
Abstract:
A well-developed clinical nomogram is a popular decision-tool, which can be used to predict the outcome of an individual, bringing benefits to both clinicians and patients. With just a few steps on a user-friendly interface, the approximate clinical outcome of patients can easily be estimated based on their clinical and laboratory characteristics. Therefore, nomograms have recently been developed to predict the different outcomes or even the survival rate at a specific time point for patients with different diseases. However, on the establishment and application of nomograms, there is still a lot of confusion that may mislead researchers. The objective of this paper is to provide a brief introduction on the history, definition, and application of nomograms and then to illustrate simple procedures to develop a nomogram with an example based on a multivariate logistic regression model in thoracic surgery. In addition, validation strategies and common pitfalls have been highlighted.
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