ArticleEuropean journal of radiology open2022
Clinical and CT patterns to predict EGFR mutation in patients with non-small cell lung cancer: A systematic literature review and meta-analysis.
Article in European journal of radiology open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Distinguishing EGFR mutant subtypes in stage IA non-small cell lung cancer using the presence status of ground glass opacity and final histologic classification: a systematic review and meta-analysis.Frontiers in medicine · 2023Pooled it
- Preoperative PET/CT phenotype of gastric-type endocervical adenocarcinoma: integrated morphological, metabolic, serological, and explainable machine-learning analysis.European journal of nuclear medicine and molecular imaging · 2026Article
- Predictive modeling of peripheral blood EGFR positivity in patients with advanced primary non-small cell lung cancer.Translational lung cancer research · 2026Article
- Habitat model based on CEUS for noninvasive prediction of EGFR mutation status in peripheral NSCLC.BMC cancer · 2026Article
- Article
- Research progress in computer-aided diagnosis systems for lung cancer.NPJ digital medicine · 2025Review
- NSCLC EGFR Mutation Prediction via Random Forest Model: A Clinical-CT-Radiomics Integration Approach.Advances in respiratory medicine · 2025Article
- The Prevalence, Distribution, and Clinicopathological Features of Seven Lung Cancer Actionable Driver Mutations in Taiwan.Thoracic cancer · 2025Article
- Construction of an imaging diagnostic model based on computed tomograph signs for peripheral small cell lung cancer.Pakistan journal of medical sciences · 2025Article
- Pleural metastasis of pulmonary adenocarcinoma mimicking diffuse mesothelioma: A case report and literature study.Radiology case reports · 2023Article
- Association between squamous cell carcinoma antigen level and EGFR mutation status in Chinese lung adenocarcinoma patients.Journal of clinical laboratory analysis · 2022Article
- Review
- A commentary on the "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
- Response to: A commentary on "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
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aims to determine if the presence of specific clinical and computed tomography (CT) patterns are associated with epidermal growth factor receptor (EGFR) mutation in patients with non-small cell lung cancer.
methodsA systematic literature review and meta-analysis was carried out in 6 databases between January 2002 and July 2021. The relationship between clinical and CT patterns to detect EGFR mutation was measured and pooled using odds ratios (OR). These results were used to build several mathematical models to predict EGFR mutation.
results34 retrospective diagnostic accuracy studies met the inclusion and exclusion criteria. The results showed that ground-glass opacities (GGO) have an OR of 1.86 (95%CI 1.34 -2.57), air bronchogram OR 1.60 (95%CI 1.38 - 1.85), vascular convergence OR 1.39 (95%CI 1.12 - 1.74), pleural retraction OR 1.99 (95%CI 1.72 - 2.31), spiculation OR 1.42 (95%CI 1.19 - 1.70), cavitation OR 0.70 (95%CI 0.57 - 0.86), early disease stage OR 1.58 (95%CI 1.14 - 2.18), non-smoker status OR 2.79 (95%CI 2.34 - 3.31), female gender OR 2.33 (95%CI 1.97 - 2.75). A mathematical model was built, including all clinical and CT patterns assessed, showing an area under the curve (AUC) of 0.81.
conclusionsGGO, air bronchogram, vascular convergence, pleural retraction, spiculated margins, early disease stage, female gender, and non-smoking status are significant risk factors for EGFR mutation. At the same time, cavitation is a protective factor for EGFR mutation. The mathematical model built acts as a good predictor for EGFR mutation in patients with lung adenocarcinoma.
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