Nomogram Based on microRNA Signature Contributes to Improve Survival Prediction of Clear Cell Renal Cell Carcinoma
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-24
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Objective.
Numerous microRNAs (miRNAs) have been identified in ccRCC and recommended to be used for predicting clear cell renal cell carcinoma (ccRCC) prognosis.
However, it is not clear whether a miRNA-based nomogram results in improved survival prediction in patients with ccRCC.
Methods.
miRNA profiles from tumors and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) database and analyzed using the “limma” package.
The association between differentially expressed miRNAs and patient prognosis was identified using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses.
Next, all patients were randomly divided into development and validation cohorts at a ratio of 1 : 1.
A nomogram was established based on independent prognostic factors in the development cohort.
The prognostic performance of the nomogram was validated in both cohorts using the concordance index (C-index) and calibration plots.
Results.
Multivariate Cox analysis identified the 13-miRNA signature, as well as AJCC stage and age, as independent prognostic factors after adjusting for other clinical covariates.
The nomogram was built based on the independent variables.
In the development cohort, the C-index for the constructed nomogram to predict overall survival (OS) was 0.792, which was higher than the C-index (0.731) of the AJCC staging system and C-index (0.778) of the miRNA signature.
The nomogram demonstrated good discriminative ability in the validation cohort in predicting OS, with a C-index of 0.762.
The calibration plots indicated an excellent agreement between the nomogram predicted survival probability and the actual observed outcomes.
Furthermore, decision curve analysis (DCA) indicated that the nomogram was superior to the AJCC staging system in increasing the net clinical benefit.
Conclusions.
The novel proposed nomogram based on a miRNA signature is a more reliable and robust tool for predicting the OS of patients with ccRCC compared to AJCC staging system, thus, improving clinical decision-making.
American Psychological Association (APA)
Zhao, Enfa& Bai, Xiaofang. 2020. Nomogram Based on microRNA Signature Contributes to Improve Survival Prediction of Clear Cell Renal Cell Carcinoma. BioMed Research International،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1136862
Modern Language Association (MLA)
Zhao, Enfa& Bai, Xiaofang. Nomogram Based on microRNA Signature Contributes to Improve Survival Prediction of Clear Cell Renal Cell Carcinoma. BioMed Research International No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1136862
American Medical Association (AMA)
Zhao, Enfa& Bai, Xiaofang. Nomogram Based on microRNA Signature Contributes to Improve Survival Prediction of Clear Cell Renal Cell Carcinoma. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1136862
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136862