Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2024 Feb 26;8:49. doi: 10.1038/s41698-024-00538-5

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

PMC Copyright notice

Fig. 6 — a Univariate analysis of the clinicopathologic characteristics and PCDI in the TCGA-LUAD cohort. b Multivariate analysis of the clinicopathologic characteristics and PCDI in the TCGA-LUAD cohort. c A nomogram was established to predict the prognosis of TCGA-LUAD patients. d Calibration plots showing the probability of 1-, 3-, and 5-year overall survival in the TCGA-LUAD cohort. e–f Decision curve analysis (DCA) of a nomogram predicting 1- and 3-year overall survival. g Kaplan‒Meier analyses for the two LUAD groups based on the nomogram score. h–k Receiver operator characteristic (ROC) analysis of the nomogram in the TCGA-LUAD, GSE31210, GSE50081, and GSE72094 cohorts.