An Individual Risk Prediction Model for Lung Cancer Based on a Study in a Chinese Population

2015 ◽  
Vol 101 (1) ◽  
pp. 16-23 ◽  
Author(s):  
Xu Wang ◽  
Kewei Ma ◽  
Jiuwei Cui ◽  
Xiao Chen ◽  
Lina Jin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prediction Model ◽  
Risk Prediction ◽  
Chinese Population ◽  
Risk Prediction Model ◽  
Individual Risk

scholarly journals Risk prediction model for lung cancer incorporating metabolic markers: Development and internal validation in a Chinese population

2020 ◽  
Vol 9 (11) ◽  
pp. 3983-3994 ◽  
Author(s):  
Zhangyan Lyu ◽  
Ni Li ◽  
Shuohua Chen ◽  
Gang Wang ◽  
Fengwei Tan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prediction Model ◽  
Risk Prediction ◽  
Chinese Population ◽  
Risk Prediction Model ◽  
Metabolic Markers ◽  
Internal Validation

scholarly journals The LLP risk model: an individual risk prediction model for lung cancer

2007 ◽  
Vol 98 (2) ◽  
pp. 270-276 ◽  
Author(s):  
A Cassidy ◽  
J P Myles ◽  
M van Tongeren ◽  
R D Page ◽  
T Liloglou ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prediction Model ◽  
Risk Prediction ◽  
Risk Model ◽  
Risk Prediction Model ◽  
Individual Risk

Accuracy of the Vancouver Lung Cancer Risk Prediction Model Compared With That of Radiologists

CHEST Journal ◽  
2019 ◽  
Vol 156 (1) ◽  
pp. 112-119 ◽  
Author(s):  
Heber MacMahon ◽  
Feng Li ◽  
Yulei Jiang ◽  
Samuel G. Armato
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Prediction Model ◽  
Risk Prediction ◽  
Lung Cancer Risk ◽  
Risk Prediction Model

scholarly journals The Cytokinesis-Blocked Micronucleus Assay as a Strong Predictor of Lung Cancer: Extension of a Lung Cancer Risk Prediction Model

2014 ◽  
Vol 23 (11) ◽  
pp. 2462-2470 ◽  
Author(s):  
Randa A. El-Zein ◽  
Mirtha S. Lopez ◽  
Anthony M. D'Amelio ◽  
Mei Liu ◽  
Reginald F. Munden ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Prediction Model ◽  
Risk Prediction ◽  
Lung Cancer Risk ◽  
Strong Predictor ◽  
Micronucleus Assay ◽  
Risk Prediction Model

scholarly journals Establishment of non–small-cell lung cancer risk prediction model based on prognosis-associated ADME genes

2021 ◽  
Author(s):  
Ke Han ◽  
Jukun Wang ◽  
Kun Qian ◽  
Teng Zhao ◽  
Yi Zhang
Keyword(s):  
Lung Cancer ◽  
Prediction Model ◽  
Risk Prediction ◽  
Risk Score ◽  
Small Cell ◽  
Risk Prediction Model ◽  
Low Risk ◽  
Regression Analyses ◽  
Small Cell Lung ◽  
Immune Infiltration

Purpose: ADME genes are those involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs. In this study, a non–small-cell lung cancer (NSCLC) risk prediction model was established using prognosis-associated ADME genes, and the predictive performance of this model was evaluated and verified. In addition, multifaceted difference analysis was performed on groups with high and low risk scores. Methods: An NSCLC sample transcriptome and clinical data were obtained from public databases. The prognosis-associated ADME genes were obtained by univariate Cox and lasso regression analyses to build a risk model. Tumor samples were divided into high-risk and low-risk score groups according to the risk score. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the differentially expressed genes and the differences in the immune infiltration, mutation, and medication reactions in the two groups were studied in detail. Results: A risk prediction model was established with seven prognosis-associated ADME genes. Its good predictive ability was confirmed by studies of the model’s effectiveness. Univariate and multivariate Cox regression analyses showed that the model’s risk score was an independent prognostic factor for patients with NSCLC. The study also showed that the risk score closely correlated with immune infiltration, mutations, and medication reactions. Conclusion: The risk prediction model established with seven ADME genes in this study can predict the prognosis of patients with NSCLC. In addition, significant differences in immune infiltration, mutations, and therapeutic efficacy exist between the high- and low-risk score groups.

scholarly journals Individualized Risk Prediction Model for Lung Cancer in Korean Men

PLoS ONE ◽  
2013 ◽  
Vol 8 (2) ◽  
pp. e54823 ◽  
Author(s):  
Sohee Park ◽  
Byung-Ho Nam ◽  
Hye-Ryung Yang ◽  
Ji An Lee ◽  
Hyunsun Lim ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prediction Model ◽  
Risk Prediction ◽  
Risk Prediction Model
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