Seok Mo Lee1, Sang Kyun Bae, Soo Jin Jung, Chun K Kim. 1. From the *Department of Nuclear Medicine, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea; †Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and ‡Department of Pathology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea.
Abstract
PURPOSE: Data in the literature regarding the use of F-FDG avidity of non-small cell lung cancer (NSCLC) as an imaging biomarker to predict the status of epidermal growth factor receptor (EGFR) mutation are conflicting. Association between KRAS mutation and FDG avidity of NSCLC on PET/CT is not well known. We assessed whether the EGFR or KRAS mutation status in NSCLC can be predicted by FDG avidity by performing several different subgroup analyses to better compare with various published results. PATIENTS AND METHODS: After obtaining institutional review board approval, we enrolled patients (1) who had FDG PET/CT performed for staging of NSCLC, (2) with EGFR and KRAS mutational status of tumor identified, and (3) without uncontrolled diabetes. Univariate and multivariate regression analyses were performed to assess the relationship between the independent clinical variables (sex, age, smoking history, tumor histology, tumor size, stage, and SUV-derived variables) and the EGFR and KRAS mutation status. Separate analyses were performed for patients with adenocarcinomas. RESULTS: There were 206 patients (age, 33-88 years; 148 male/58 female; 71 ever-smokers/135 never-smokers; 135 adenocarcinoma/71 squamous cell carcinoma; 22 stage I-II/184 stage III-IV; tumor size, 1.2-15.0 cm; SUVmax, 2.9-36.4; EGFR mutations present in 47; KRAS mutations present in 20). In multivariate analysis, sex, smoking history, histology, and tumor size were significantly associated with EGFR mutation but none of the SUV-derived variables was. Likewise, no correlation was found between the SUV-derived variables and KRAS mutation. CONCLUSIONS: Our results suggest that FDG avidity of NSCLC has no significant clinical value in predicting the EGFR or KRAS mutation status.
PURPOSE: Data in the literature regarding the use of F-FDG avidity of non-small cell lung cancer (NSCLC) as an imaging biomarker to predict the status of epidermal growth factor receptor (EGFR) mutation are conflicting. Association between KRAS mutation and FDG avidity of NSCLC on PET/CT is not well known. We assessed whether the EGFR or KRAS mutation status in NSCLC can be predicted by FDG avidity by performing several different subgroup analyses to better compare with various published results. PATIENTS AND METHODS: After obtaining institutional review board approval, we enrolled patients (1) who had FDG PET/CT performed for staging of NSCLC, (2) with EGFR and KRAS mutational status of tumor identified, and (3) without uncontrolled diabetes. Univariate and multivariate regression analyses were performed to assess the relationship between the independent clinical variables (sex, age, smoking history, tumor histology, tumor size, stage, and SUV-derived variables) and the EGFR and KRAS mutation status. Separate analyses were performed for patients with adenocarcinomas. RESULTS: There were 206 patients (age, 33-88 years; 148 male/58 female; 71 ever-smokers/135 never-smokers; 135 adenocarcinoma/71 squamous cell carcinoma; 22 stage I-II/184 stage III-IV; tumor size, 1.2-15.0 cm; SUVmax, 2.9-36.4; EGFR mutations present in 47; KRAS mutations present in 20). In multivariate analysis, sex, smoking history, histology, and tumor size were significantly associated with EGFR mutation but none of the SUV-derived variables was. Likewise, no correlation was found between the SUV-derived variables and KRAS mutation. CONCLUSIONS: Our results suggest that FDG avidity of NSCLC has no significant clinical value in predicting the EGFR or KRAS mutation status.
Authors: Jian Guan; Nan J Xiao; Min Chen; Wen L Zhou; Yao W Zhang; Shuang Wang; Yong M Dai; Lu Li; Yue Zhang; Qin Y Li; Xiang Z Li; Mi Yang; Hu B Wu; Long H Chen; Lai Y Liu Journal: Medicine (Baltimore) Date: 2016-07 Impact factor: 1.889
Authors: Stephen S F Yip; John Kim; Thibaud P Coroller; Chintan Parmar; Emmanuel Rios Velazquez; Elizabeth Huynh; Raymond H Mak; Hugo J W L Aerts Journal: J Nucl Med Date: 2016-09-29 Impact factor: 10.057