Statistical modelling for thoracic surgery using a nomogram based on logistic regression.
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.
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China ;
Run-Zhong
RZ
Liu
Division of Cardiothoracic Surgery, Department of Surgery, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.
Ze-Rui
ZR
Zhao
Division of Cardiothoracic Surgery, Department of Surgery, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China.
Calvin S H
CS
Ng
Logistic regression model; nomogram; outcome; procedure