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Abstract

Cancer Research

An R-Based Landscape Validation of a Competing Risk Model

Published: September 16th, 2022

DOI:

10.3791/64018

1Department of Hepatobiliary Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 2Department of Medical Oncology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, 3Department of Colorectal Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine

* These authors contributed equally

Abstract

The Cox proportional hazard model is widely applied for survival analyses in clinical settings, but it is not able to cope with multiple survival outcomes. Different from the traditional Cox proportional hazard model, competing risk models consider the presence of competing events and their combination with a nomogram, a graphical calculating device, which is a useful tool for clinicians to conduct a precise prognostic prediction. In this study, we report a method for establishing the competing risk nomogram, that is, the evaluation of its discrimination (i.e., concordance index and area under the curve) and calibration (i.e., calibration curves) abilities, as well as the net benefit (i.e., decision curve analysis). In addition, internal validation using bootstrap resamples of the original dataset and external validation using an external dataset of the established competing risk nomogram were also performed to demonstrate its extrapolation ability. The competing risk nomogram should serve as a useful tool for clinicians to predict prognosis with the consideration of competing risks.

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Keywords Competing Risk Model

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