SynthesisInternational journal of clinical oncology2019
CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis.
Synthesis in International journal of clinical oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- CanBMJ open · 2021Pooled it
- Predictive modeling of lung cancer subtype with integration of clinical and thoracic imaging features to guide early brain metastasis management.Journal of neuro-oncology · 2026Article
- Article
- CT-based nomogram for predicting EGFR mutation status in ground-glass nodules of lung adenocarcinoma.Frontiers in immunology · 2025Article
- Enhanced prediction of gene mutation and risk stratification in non-small-cell lung cancer through dual-pathway fusion of radiomics and pathomics.Frontiers in oncology · 2025Article
- Prediction of EGFR mutations in non-small cell lung cancer: a nomogram based onFrontiers in oncology · 2025Article
- Predicting EGFR gene mutation in lung adenocarcinoma using spectral CT combined with AI parameters: a diagnostic accuracy study.Frontiers in oncology · 2025Article
- Multimodal ultrasonography for predicting epidermal growth factor receptor mutation in subpleural non-small cell lung carcinoma.Frontiers in oncology · 2025Article
- ExplainableJournal of cancer research and clinical oncology · 2024Article
- Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024Article
- Article
- Transfer learning-based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma.BMC medical imaging · 2024Article
- The differential prognostic implications of PD-L1 expression in the outcomes of Filipinos withTranslational lung cancer research · 2023Article
- Predicting EGFR Mutation in Lung Adenocarcinoma: Development and Validation of the EGFR Mutation Predictive Score (EMPS) in Bali, Indonesia.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- The predictive value of [EJNMMI research · 2023Article
- CT-based decision tree model for predicting EGFR mutation status in synchronous multiple primary lung cancers.Journal of thoracic disease · 2023Article
- Association Analysis of Maximum Standardized Uptake Values Based onJournal of personalized medicine · 2023Article
- Role of intratumoral and peritumoral CT radiomics for the prediction of EGFR gene mutation in primary lung cancer.The British journal of radiology · 2022Article
- A nomogram based onQuantitative imaging in medicine and surgery · 2022Article
- Article
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Authors and funding
5 authors.
Funding
Abstract
introductionTo systematically analyze CT and clinical characteristics to find out the risk factors of epidermal growth factor receptor (EGFR) mutation in non-small cell lung cancer (NSCLC). Then the significant characteristics were used to set up a mathematic model to predict EGFR mutation in NSCLC. MATERIALS AND
methodsPubMed, Web of Knowledge and EMBASE up to August 17, 2018 were systematically searched for relevant studies that investigated the evidence of association between CT and clinical characteristics and EGFR mutation in NSCLC. After study selection, data extraction, and quality assessment, the pooled odds ratios (ORs) were calculated. Then from May 2017 to August 2018, all NSCLC received EGFR mutation examination and CT examination in our hospital were chosen to test the prediction model by receiver operating characteristic (ROC) curves.
resultsSeventeen original studies met the inclusion criteria. The results showed that the ORs of ground-glass opacity (GGO), air bronchogram, pleural retraction, vascular convergence, smoking history, female gender were, respectively, 1.93 (P = 0.003), 2.09 (P = 0.03), 1.59 (P < 0.01), 1.61 (P = 0.001), 0.28 (P < 0.01), 0.35 (P < 0.01). The result of speculation, cavitation/bubble-like lucency, lesion shape, margin, pathological stage were, respectively, 1.19 (P = 0.32), 0.99 (P = 0.97), 0.82 (P = 0.42), 1.02 (P = 0.90), 0.77 (P = 0.30). 121 NSCLC received EGFR mutation test were included to test the prediction model. The mathematical model based on the results of meta-analysis was: 0.74 × air bronchogram + 0.46 × pleural retraction + 0.48 × vascular convergence - 1.27 × non-smoking history - 1.05 × female. The area under the ROC curve was 0.68.
conclusionBased on the current evidence, GGO presence, air bronchogram, pleural retraction, vascular convergence were significant risk factors of EGFR mutation in NSCLC. And the prediction model can help to predict EGFR mutation status.
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