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Establishing a Competing Risk Regression Nomogram Model for Survival Data

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Published on: October 23, 2020

Comprehensive nomogram models for predicting checkpoint inhibitor pneumonitis.

Xiaohui Jia¹, Yajuan Zhang¹, Ting Liang²

¹Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University Xi'an 710061, Shaanxi, P. R. China.

American Journal of Cancer Research

|July 10, 2023

Summary

Checkpoint inhibitor pneumonitis (CIP), a severe immune-related adverse event, lacks predictive tools. This study developed two nomograms to accurately predict CIP risk in patients receiving immunotherapy, aiding clinical decision-making.

Keywords:

Immunotherapy biomarkers cancers checkpoint inhibitor pneumonitis nomogram

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Published on: January 2, 2017

Area of Science:

Oncology
Pulmonology
Immunology

Background:

Checkpoint inhibitor pneumonitis (CIP) is a frequent immune-related adverse event (irAE) associated with poor prognosis.
Effective biomarkers and predictive models for CIP occurrence are currently lacking.

Purpose of the Study:

To develop and validate predictive models for checkpoint inhibitor pneumonitis (CIP).
To identify independent risk factors for predicting CIP in patients undergoing immunotherapy.

Main Methods:

Retrospective enrollment of 547 patients receiving immunotherapy.
Development of two nomograms (Nomogram A and Nomogram B) using multivariate logistic regression.
Internal and external validation of the nomograms' predictive performance.

Main Results:

Nomogram A for any grade CIP showed C-indexes of 0.827 (training) and 0.860 (validation).
Nomogram B for grade ≥2 CIP demonstrated C-indexes of 0.873 (training) and 0.904 (validation).
Both nomograms exhibited satisfactory predictive power and clinical utility.

Conclusions:

Nomograms A and B are promising, personalized clinical tools for assessing CIP risk.
These visual and convenient tools can aid in the early identification and management of CIP.
Further clinical application of these nomograms may improve patient outcomes in immunotherapy.