Literature DB >> 29607142

Value of combining serum carcinoembryonic antigen and PET/CT in predicting EGFR mutation in non-small cell lung cancer.

Jincui Gu1, Siqi Xu1, Lixia Huang1, Shaoli Li1, Jian Wu1, Junwen Xu1, Jinlun Feng1, Baomo Liu1, Yanbin Zhou1.   

Abstract

BACKGROUND: We sought to investigate the associations between pretreatment serum Carcinoembryonic antigen (CEA) level, 18F-Fluoro-2-deoxyglucose (18F-FDG) uptake value of primary tumor and epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC).
METHODS: We retrospectively reviewed medical records of 210 NSCLC patients who underwent EGFR mutation test and 18F-FDG positron emission tomography/computed tomography (PET/CT) scan before anti-tumor therapy. The associations between EGFR mutations and patients' characteristics, serum CEA, PET/CT imaging characteristics maximal standard uptake value (SUVmax) of the primary tumor were analyzed. Receiver-operating characteristic (ROC) curve was used to assess the predictive value of these factors.
RESULTS: EGFR mutations were found in 70 patients (33.3%). EGFR mutations were more common in high CEA group (CEA ≥7.0 ng/mL) than in low CEA group (CEA <7.0 ng/mL) (40.4% vs. 27.6%; P=0.05). Females (P<0.001), non-smokers (P<0.001), patients with adenocarcinoma (P<0.001) and SUVmax <9.0 (P=0.001) were more likely to be EGFR mutation-positive. Multivariate analysis revealed that gender, tumor histology, pretreatment serum CEA level, and SUVmax were the most significant predictors for EGFR mutations. The ROC curve revealed that combining these four factors yielded a higher calculated AUC (0.80).
CONCLUSIONS: Gender, histology, pretreatment serum CEA level and SUVmax are significant predictors for EGFR mutations in NSCLC. Combining these factors in predicting EGFR mutations has a moderate diagnostic accuracy, and is helpful in guiding anti-tumor treatment.

Entities:  

Keywords:  Non-small cell lung cancer (NSCLC); carcinoembryonic antigen; epidermal growth factor receptor (EGFR); maximal standard uptake value; positron emission tomography/computed tomography (PET/CT)

Year:  2018        PMID: 29607142      PMCID: PMC5864650          DOI: 10.21037/jtd.2017.12.143

Source DB:  PubMed          Journal:  J Thorac Dis        ISSN: 2072-1439            Impact factor:   2.895


  34 in total

1.  Glucose transporters and FDG uptake in untreated primary human non-small cell lung cancer.

Authors:  R S Brown; J Y Leung; P V Kison; K R Zasadny; A Flint; R L Wahl
Journal:  J Nucl Med       Date:  1999-04       Impact factor: 10.057

2.  Serum carcinoembryonic antigen as a predictive marker for sensitivity to gefitinib in advanced non-small cell lung cancer.

Authors:  Tatsuro Okamoto; Tomomi Nakamura; Jiro Ikeda; Riichiroh Maruyama; Fumihiro Shoji; Tetsuro Miyake; Hiroshi Wataya; Yukito Ichinose
Journal:  Eur J Cancer       Date:  2005-06       Impact factor: 9.162

3.  Assessment of factors influencing FDG uptake in non-small cell lung cancer on PET/CT by investigating histological differences in expression of glucose transporters 1 and 3 and tumour size.

Authors:  Naohisa Suzawa; Morihiro Ito; Shanlou Qiao; Katsunori Uchida; Motoshi Takao; Tomomi Yamada; Kan Takeda; Shuichi Murashima
Journal:  Lung Cancer       Date:  2010-09-29       Impact factor: 5.705

Review 4.  Molecular predictors of response to epidermal growth factor receptor antagonists in non-small-cell lung cancer.

Authors:  Lecia V Sequist; Daphne W Bell; Thomas J Lynch; Daniel A Haber
Journal:  J Clin Oncol       Date:  2007-02-10       Impact factor: 44.544

5.  Role of [¹⁸F]FDG PET in prediction of KRAS and EGFR mutation status in patients with advanced non-small-cell lung cancer.

Authors:  Carlos Caicedo; Maria Jose Garcia-Velloso; Maria Dolores Lozano; Tania Labiano; Carmen Vigil Diaz; Jose Maria Lopez-Picazo; Alfonso Gurpide; Javier J Zulueta; Javier Zulueta; Jose Angel Richter Echevarria; Jose Luis Perez Gracia
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-07-03       Impact factor: 9.236

6.  Correlation of F-18 fluorodeoxyglucose-positron emission tomography maximal standardized uptake value and EGFR mutations in advanced lung adenocarcinoma.

Authors:  Chun-Ta Huang; Rouh-Fang Yen; Mei-Fang Cheng; Ya-Chieh Hsu; Pin-Fei Wei; Yi-Ju Tsai; Meng-Feng Tsai; Jin-Yuan Shih; Chih-Hsin Yang; Pan-Chyr Yang
Journal:  Med Oncol       Date:  2009-01-07       Impact factor: 3.064

7.  Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations.

Authors:  Lecia V Sequist; James Chih-Hsin Yang; Nobuyuki Yamamoto; Kenneth O'Byrne; Vera Hirsh; Tony Mok; Sarayut Lucien Geater; Sergey Orlov; Chun-Ming Tsai; Michael Boyer; Wu-Chou Su; Jaafar Bennouna; Terufumi Kato; Vera Gorbunova; Ki Hyeong Lee; Riyaz Shah; Dan Massey; Victoria Zazulina; Mehdi Shahidi; Martin Schuler
Journal:  J Clin Oncol       Date:  2013-07-01       Impact factor: 44.544

8.  Serum tumor markers as predictors for survival in advanced non-small cell lung cancer patients treated with gefitinib.

Authors:  Chao-Hua Chiu; Yu-Ning Shih; Chun-Ming Tsai; Jia-Ling Liou; Yuh-Min Chen; Reury-Perng Perng
Journal:  Lung Cancer       Date:  2007-04-20       Impact factor: 5.705

9.  Tumor vascularity and glucose metabolism correlated in adenocarcinoma, but not in squamous cell carcinoma of the lung.

Authors:  Jiuquan Zhang; Lihua Chen; Yongfeng Chen; Wenwei Wang; Lin Cheng; Xiangdong Zhou; Jian Wang
Journal:  PLoS One       Date:  2014-03-10       Impact factor: 3.240

10.  Erlotinib-cisplatin combination inhibits growth and angiogenesis through c-MYC and HIF-1α in EGFR-mutated lung cancer in vitro and in vivo.

Authors:  Jasmine G Lee; Reen Wu
Journal:  Neoplasia       Date:  2015-02       Impact factor: 5.715

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  6 in total

1.  Predictive models for patients with lung carcinomas to identify EGFR mutation status via an artificial neural network based on multiple clinical information.

Authors:  Xiaoyi Qin; Hailong Wang; Xiang Hu; Xiaolong Gu; Wei Zhou
Journal:  J Cancer Res Clin Oncol       Date:  2019-12-05       Impact factor: 4.553

2.  The Prognostic Value of 18F-FDG PET/CT Metabolic Parameters in Predicting Treatment Response Before EGFR TKI Treatment in Patients with Advanced Lung Adenocarcinoma.

Authors:  Nurşin Agüloğlu; Murat Akyol; Halil Kömek; Nuran Katgı
Journal:  Mol Imaging Radionucl Ther       Date:  2022-06-27

3.  Machine Learning-Based Radiomics for Prediction of Epidermal Growth Factor Receptor Mutations in Lung Adenocarcinoma.

Authors:  Jiameng Lu; Xiaoqing Ji; Lixia Wang; Yunxiu Jiang; Xinyi Liu; Zhenshen Ma; Yafei Ning; Jie Dong; Haiying Peng; Fei Sun; Zihan Guo; Yanbo Ji; Jianping Xing; Yue Lu; Degan Lu
Journal:  Dis Markers       Date:  2022-05-07       Impact factor: 3.464

4.  The predictive value of 18F-FDG PET/CT in an EGFR-mutated lung adenocarcinoma population.

Authors:  Jian Wang; Xiaolian Wen; Guirong Yang; Yong Cui; Mingyan Hao; Xiaoyuan Qiao; Baoli Jin; Bo Li; Jing Wu; Xiaomin Li; Xiaolu Ren
Journal:  Transl Cancer Res       Date:  2022-07       Impact factor: 0.496

5.  Carcinoembryonic antigen in pleural effusion of patients with lung adenocarcinoma: a predictive marker for EGFR mutation.

Authors:  Yan-Ling Lv; Hong-Bing Liu; Dong-Mei Yuan; Li Zhou; Shu-Xian Jin; Yong Song
Journal:  Transl Cancer Res       Date:  2019-08       Impact factor: 1.241

Review 6.  Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients.

Authors:  Lanlan Liu; Xianzhi Xiong
Journal:  Curr Oncol       Date:  2021-12-24       Impact factor: 3.677

  6 in total

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