ArticleEuropean radiology2016
Predicting EGFR mutation status in lung cancer:Proposal for a scoring model using imaging and demographic characteristics.
Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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19 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis.International journal of clinical oncology · 2019Pooled it
- Correlation analysis between EGFR gene mutation status, ALK positivity and demographic data, tumor biomarkers, radiological and pathological features in patients with lung adenocarcinoma.Frontiers in oncology · 2025Article
- Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study.Insights into imaging · 2024Article
- Establishment and Evaluation of EGFR Mutation Prediction Model Based on Tumor Markers and CT Features in NSCLC.Journal of healthcare engineering · 2022Article
- Clinical and CT patterns to predict EGFR mutation in patients with non-small cell lung cancer: A systematic literature review and meta-analysis.European journal of radiology open · 2022Article
- Clinical and radiological predictors of epidermal growth factor receptor mutation in nonsmall cell lung cancer.Journal of applied clinical medical physics · 2021Article
- Computed Tomography Morphological Classification of Lung Adenocarcinoma and Its Correlation with Epidermal Growth Factor Receptor Mutation Status: A Report of 1075 Cases.International journal of general medicine · 2021Article
- Clinicoradiopathological features and prognosis according to genomic alterations in patients with resected lung adenocarcinoma.Journal of thoracic disease · 2020Article
- Article
- Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas.Thoracic cancer · 2020Article
- Is there any correlation between spectral CT imaging parameters and PD-L1 expression of lung adenocarcinoma?Thoracic cancer · 2020Article
- Relationship between EGFR mutation and computed tomography characteristics of the lung in patients with lung adenocarcinoma.Thoracic cancer · 2019Article
- The Potential of Radiomics Nomogram in Non-invasively Prediction of Epidermal Growth Factor Receptor Mutation Status and Subtypes in Lung Adenocarcinoma.Frontiers in oncology · 2019Article
- Article
- Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis.Oncotarget · 2018Review
- A new predictive scoring system based on clinical data and computed tomography features for diagnosingCurrent oncology (Toronto, Ont.) · 2018Article
- Radiological and Clinical Features associated with Epidermal Growth Factor Receptor Mutation Status of Exon 19 and 21 in Lung Adenocarcinoma.Scientific reports · 2017Article
- Imaging Characteristics of Driver Mutations in EGFR, KRAS, and ALK among Treatment-Naïve Patients with Advanced Lung Adenocarcinoma.PloS one · 2016Article
- Development and Validation of a Concise Prediction Scoring System for Asian Lung Cancer Patients withTechnology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine if a combination of CT and demographic features can predict EGFR mutation status in bronchogenic carcinoma.
methodsWe reviewed demographic and CT features for patients with molecular profiling for resected non-small cell lung carcinoma. Using multivariate logistic regression, we identified features predictive of EGFR mutation. Prognostic factors identified from the logistic regression model were then used to build a more practical scoring system.
resultsA scoring system awarding 5 points for no or minimal smoking history, 3 points for tumours with ground glass component, 3 points for airbronchograms, 2 points for absence of preoperative evidence of nodal enlargement or metastases and 1 point for doubling time of more than a year, resulted in an AUROC of 0.861. A total score of at least 8 yielded a specificity of 95 %. On multivariate analysis sex was not found to be predictor of EGFR status.
conclusionsA weighted scoring system combining imaging and demographic data holds promise as a predictor of EGFR status. Further studies are necessary to determine reproducibility in other patient groups. A predictive score may help determine which patients would benefit from molecular profiling and may help inform treatment decisions when molecular profiling is not possible. KEY POINTS: • EGFR mutation-targeted chemotherapy for bronchogenic carcinoma has a high success rate. • Mutation testing is not possible in all patients. • EGFR associations include subsolid density, slow tumour growth and minimal/no smoking history. • Demographic or imaging features alone are weak predictors of EGFR status. • A scoring system, using imaging and demographic features, is more predictive.
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