A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma
- 5 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in European Radiology
- Vol. 31 (8), 6259-6268
- https://doi.org/10.1007/s00330-020-07676-x
Abstract
Objectives This study aims to develop a clinically practical model to predict EGFR mutation in lung adenocarcinoma patients according to radiomics signatures based on PET/CT and clinical risk factors. Methods This retrospective study included 583 lung adenocarcinoma patients, including 295 (50.60%) patients with EGFR mutation and 288 (49.40%) patients without EGFR mutation. The clinical risk factors associated with lung adenocarcinoma were collected at the same time. We developed PET/CT, CT, and PET radiomics models for the prediction of EGFR mutation using multivariate logistic regression analysis, respectively. We also constructed a combined PET/CT radiomics-clinical model by nomogram analysis. The diagnostic performance and clinical net benefit of this risk-scoring model were examined via receiver operating characteristic (ROC) curve analysis while the clinical usefulness of this model was evaluated by decision curve analysis (DCA). Results The ROC analysis showed predictive performance for the PET/CT radiomics model (AUC = 0.76), better than the PET model (AUC = 0.71, Delong test: Z = 3.03, p value = 0.002) and the CT model (AUC = 0.74, Delong test: Z = 1.66, p value = 0.098). Also, the PET/CT radiomics-clinical combined model has a better performance (AUC = 0.84) to predict EGFR mutation than the PET/CT radiomics model (AUC = 0.76, Delong test: D = 2.70, df = 790.81, p value < 0.001) or the clinical model (AUC = 0.81, Delong test: Z = 3.46, p value < 0.001). Conclusions We demonstrated that the combined PET/CT radiomics-clinical model has an advantage to predict EGFR mutation in lung adenocarcinoma. Key Points • Radiomics from lung tumor increase the efficiency of the prediction for EGFR mutation in clinical lung adenocarcinoma on PET/CT. • A radiomic nomogram was developed to predict EGFR mutation. • Combining PET/CT radiomics-clinical model has an advantage to predict EGFR mutation.Keywords
Funding Information
- Natural Science Foundation of Shanghai (18ZR1435200)
- Special project of integrated traditional Chinese and Western medicine in general hospital of Shanghai Health Committee (ZHYY-ZXYJHZX-202023)
- Shanghai Sailing Program (20YF1444500)
- National Natural Science Foundation of China (81602415, 81773007, 81871353, 81671679)
- Shanghai Municipal Population and Family Planning Commission (20174Y0077)
This publication has 31 references indexed in Scilit:
- Overcoming EGFR(T790M) and EGFR(C797S) resistance with mutant-selective allosteric inhibitorsNature, 2016
- Combined EGFR/MEK Inhibition Prevents the Emergence of Resistance in EGFR-Mutant Lung CancerCancer Discovery, 2015
- Targeting EGFR in lung cancer: Lessons learned and future perspectivesMolecular Aspects of Medicine, 2015
- AZD9291 in EGFR Inhibitor–Resistant Non–Small-Cell Lung CancerThe New England Journal of Medicine, 2015
- International trends in lung cancer incidence by histological subtype: Adenocarcinoma stabilizing in men but still increasing in womenLung Cancer, 2014
- ALK Rearrangements Are Mutually Exclusive with Mutations in EGFR or KRAS: An Analysis of 1,683 Patients with Non–Small Cell Lung CancerClinical Cancer Research, 2013
- Gefitinib in Advanced Non-Small Cell Lung Cancer: Does It Deserve a Second Chance?The Oncologist, 2008
- Epidermal growth factor receptor gene amplification and gefitinib sensitivity in patients with recurrent lung cancerZeitschrift für Krebsforschung und Klinische Onkologie, 2007
- Clinical Course of Patients with Non–Small Cell Lung Cancer and Epidermal Growth Factor Receptor Exon 19 and Exon 21 Mutations Treated with Gefitinib or ErlotinibClinical Cancer Research, 2006
- Gefitinib plus best supportive care in previously treated patients with refractory advanced non-small-cell lung cancer: results from a randomised, placebo-controlled, multicentre study (Iressa Survival Evaluation in Lung Cancer)The Lancet, 2005