Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
International Journal of Clinical Oncology
Published in: International Journal of Clinical Oncology 6/2019

01-06-2019 | NSCLC | Original Article

CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis

Authors: Hanfei Zhang, Weiguo Cai, Yanfan Wang, Meiyan Liao, Sufang Tian

Published in: International Journal of Clinical Oncology | Issue 6/2019

Login to get access

Abstract

Introduction

To 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 methods

PubMed, 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.

Results

Seventeen 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.

Conclusion

Based 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.
Appendix
Available only for authorised users
Literature
1.
Ettinger DS, Akerley W, Borghaei H et al (2012) Non-small cell lung cancer. J Natl Compr Cancer Netw 10(10):1236–1271CrossRef
2.
Detterbeck FC, Boffa DJ, Tanoue LT (2009) The new lung cancer staging system. Chest 136(1):260–271PubMedCrossRef
3.
Goldstraw P, Chansky K, Crowley J et al (2016) The IASLC lung cancer staging project: proposals for revision of the TNM stage groupings in the forthcoming (eighth) edition of the TNM classification for lung cancer. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 11(1):39–51
4.
Buettner R, Wolf J, Thomas RK (2013) Lessons learned from lung cancer genomics: the emerging concept of individualized diagnostics and treatment. J Clin Oncol Off J Am Soc Clin Oncol 31(15):1858–1865CrossRef
5.
Abdallah SM, Hirsh V (2018) Irreversible tyrosine kinase inhibition of epidermal growth factor receptor with afatinib in EGFR activating mutation-positive advanced non-small-cell lung cancer. Curr Oncol 25(Suppl 1):S9–S17PubMedPubMedCentralCrossRef
6.
Diaz-Serrano A, Gella P, Jimenez E et al (2018) Targeting EGFR in lung cancer: current standards and developments. Drugs 78(9):893–911PubMedCrossRef
7.
Rizzo S, Petrella F, Buscarino V et al (2016) CT radiogenomic characterization of EGFR, K-RAS, and ALK mutations in non-small cell lung cancer. Eur Radiol 26(1):32–42PubMedCrossRef
8.
Taniguchi K, Okami J, Kodama K et al (2008) Intratumor heterogeneity of epidermal growth factor receptor mutations in lung cancer and its correlation to the response to gefitinib. Cancer Sci 99(5):929–935PubMedCrossRef
9.
Tomonaga N, Nakamura Y, Yamaguchi H et al (2013) Analysis of intratumor heterogeneity of EGFR mutations in mixed type lung adenocarcinoma. Clin Lung Cancer 14(5):521–526PubMedCrossRef
10.
Tang ER, Schreiner AM, Pua BB (2014) Advances in lung adenocarcinoma classification: a summary of the new international multidisciplinary classification system (IASLC/ATS/ERS). J Thorac Dis 6(Suppl 5):S489–S501PubMedPubMedCentral
11.
Cheng Z, Shan F, Yang Y et al (2017) CT characteristics of non-small cell lung cancer with epidermal growth factor receptor mutation: a systematic review and meta-analysis. BMC Med Imaging 17(1):1–10CrossRef
12.
Liu Y, Kim J, Balagurunathan Y et al (2016) Radiomic features are associated with EGFR mutation status in lung adenocarcinomas. Clin Lung Cancer 17(5):441–448e6PubMedPubMedCentralCrossRef
13.
Moher D, Liberati A, Tetzlaff J et al (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6(7):e1–e7CrossRef
14.
15.
16.
Usuda K, Sagawa M, Motono N et al (2014) Relationships between EGFR mutation status of lung cancer and preoperative factors—are they predictive? Asian Pac J Cancer Prev 15(2):657–662PubMedCrossRef
17.
Sabri A, Batool M, Xu Z et al (2016) Predicting EGFR mutation status in lung cancer: proposal for a scoring model using imaging and demographic characteristics. Eur Radiol 26(11):4141–4147PubMedCrossRef
18.
Kim T, Lee C, Jheon S et al (2016) Radiologic characteristics of surgically resected non-small cell lung cancer with ALK rearrangement or EGFR mutations. Ann Thorac Surg 101(2):473–480PubMedCrossRef
19.
Yano M, Sasaki H, Kobayashi Y et al (2006) Epidermal growth factor receptor gene mutation and computed tomographic findings in peripheral pulmonary adenocarcinoma. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 1(5):413–416
20.
Sugano M, Shimizu K, Nakano T et al (2011) Correlation between computed tomography findings and epidermal growth factor receptor and Kras gene mutations in patients with pulmonary adenocarcinoma. Oncol Rep 26:1205–1211PubMed
21.
Cao Y, Xu H, Liao M et al (2018) Associations between clinical data and computed tomography features in patients with epidermal growth factor receptor mutations in lung adenocarcinoma. Int J Clin Oncol 23(2):249–257PubMedCrossRef
22.
Hsu KH, Chen KC, Yang TY et al (2011) Epidermal growth factor receptor mutation status in stage I lung adenocarcinoma with different image patterns. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 6(6):1066–1072
23.
Hsu JS, Huang MS, Chen CY et al (2014) Correlation between EGFR mutation status and computed tomography features in patients with advanced pulmonary adenocarcinoma. J Thorac Imaging 29(6):357–363PubMedCrossRef
24.
Sacconi B, Anzidei M, Leonardi A et al (2017) Analysis of CT features and quantitative texture analysis in patients with lung adenocarcinoma: a correlation with EGFR mutations and survival rates. Clin Radiol 72(6):443–450PubMedCrossRef
25.
Yang Y, Yang Y, Zhou X et al (2015) EGFR L858R mutation is associated with lung adenocarcinoma patients with dominant ground-glass opacity. Lung Cancer 87(3):272–277PubMedCrossRef
26.
Zou J, Lv T, Zhu S et al (2017) Computed tomography and clinical features associated with epidermal growth factor receptor mutation status in stage I/II lung adenocarcinoma. Thorac Cancer 8(3):260–270PubMedPubMedCentralCrossRef
27.
Hasegawa M, Sakai F, Ishikawa R et al (2016) CT features of epidermal growth factor receptor-mutated adenocarcinoma of the lung: comparison with nonmutated adenocarcinoma. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 11(6):819–826
28.
Liu Y, Kim J, Qu F et al (2016) CT features associated with epidermal growth factor receptor mutation status in patients with lung adenocarcinoma. Radiology 280(1):271–280PubMedPubMedCentralCrossRef
29.
Zhou JY, Zheng J, Yu ZF et al (2015) Comparative analysis of clinicoradiologic characteristics of lung adenocarcinomas with ALK rearrangements or EGFR mutations. Eur Radiol 25(5):1257–1266PubMedCrossRef
30.
Dai J, Shi J, Soodeen-Lalloo AK et al (2016) Air bronchogram: a potential indicator of epidermal growth factor receptor mutation in pulmonary subsolid nodules. Lung Cancer 98:22–28PubMedCrossRef
31.
Zhao J, Dinkel J, Warth A et al (2017) CT characteristics in pulmonary adenocarcinoma with epidermal growth factor receptor mutation. PLoS One 12(9):e0182741PubMedPubMedCentralCrossRef
32.
Suzuki S, Sakurai H, Yotsukura M et al (2018) Clinical features of ground glass opacity-dominant lung cancer exceeding 3.0 cm in the whole tumor size. Ann Thorac Surg 105(5):1499–1506PubMedCrossRef
33.
Lee HJ, Kim YT, Kang CH et al (2013) Epidermal growth factor receptor mutation in lung adenocarcinomas: relationship with CT characteristics and histologic subtypes. Radiology 268(1):254–264PubMedCrossRef
34.
Haneda H, Sasaki H, Shimizu S et al (2006) Epidermal growth factor receptor gene mutation defines distinct subsets among. Lung Cancer 52(1):47–52PubMedCrossRef
35.
Lederlin M, Puderbach M, Muley T et al (2013) Correlation of radio- and histomorphological pattern of pulmonary adenocarcinoma. Eur Respir J 41(4):943–951PubMedCrossRef
Metadata
Title
CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis
Authors
Hanfei Zhang
Weiguo Cai
Yanfan Wang
Meiyan Liao
Sufang Tian
Publication date
01-06-2019
Publisher
Springer Singapore
Published in
International Journal of Clinical Oncology / Issue 6/2019
Print ISSN: 1341-9625
Electronic ISSN: 1437-7772
DOI
https://doi.org/10.1007/s10147-019-01403-3

Other articles of this Issue 6/2019

International Journal of Clinical Oncology 6/2019 Go to the issue

Original Article

Control of intracranial disease is associated with improved survival in patients with brain metastasis from hepatocellular carcinoma

Review Article

Efficacy and safety of oxaliplatin-based regimen versus cisplatin-based regimen in the treatment of gastric cancer: a meta-analysis of randomized controlled trials

Original Article

Patterns of lymph node metastasis and the management of neck dissection for parotid carcinomas: a single-institute experience

Invited Review Article

RFA experiences, indications and clinical outcomes

Original Article

Optimal treatment strategy for rectal cancer based on the risk factors for recurrence patterns

Original Article

Squamous cell carcinoma of the bladder: poor response to neoadjuvant chemotherapy
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits