Value of combining PET/CT and clinicopathological features in predicting EGFR mutation in Lung Adenocarcinoma with Bone Metastasis

Yao, Guangyu; Zhou, Yunyun; Gu, Yu; Wang, Zhiyu; Yang, Mei; Sun, Jing; Luo, Quan‐Yong; Zhao, Hui

doi:10.7150/jca.46414

Cited by 12 publications

(9 citation statements)

References 42 publications

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“…The results of this study suggest that patients with stage IV disease according to the TNM staging guidelines have a higher mutation rate, which is inconsistent with previous research [26], but the number of cases was small, and there may have been selection bias. Finally, univariate analysis showed that the EGFR mutation rate in non-smokers was higher than that in smokers which is consistent with another study [27,28].…”

Section: Discussionsupporting

confidence: 90%

A Predictive Model of EGFR Mutation Status in Patients with Lung Adenocarcinoma Based on PET/CT Metabolic Indexes and Clinicopathological Variables

Yang¹,

Shi²,

Huang³

et al. 2020

Preprint

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PurposeThe purpose of this study was to create a mathematical model based on the metabolic parameters of PET/CT with clinicopathological characteristics to predict the EGFR mutation status of patients with lung adenocarcinoma.MethodsThis study retrospectively enrolled patients with lung adenocarcinoma who underwent surgical treatment at two centres in China between January 2012 and December 2015. PET/CT metabolic parameters and Classical EGFR mutation status detection by molecular pathology were performed before and after surgery, and we analysed the associations of EGFR mutation status with patient sex, age, smoking history, maximum primary lesion diameter, carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cytokeratin 19 fragment (CYFRA21-1), TNM stage and histopathological subtype of lung adenocarcinoma.ResultsA total of 310 patients were included, comprising 161 with EGFR mutations (51.9%) and 149 with wild-type EGFR (48.1%). EGFR mutations were more common in females, non-smokers, and those with stage IV disease, a low SUVmax, and ≤35 mm nodules, whereas wild-type EGFR was more common in males, smokers, and those with a solid growth pattern. Multivariate analysis suggested that liver SUVratio, smoking history, tumour size, TNM stage, and solid growth pattern can predict EGFR mutation status, and these factors were used to construct a mathematical model.ConclusionThe prediction model constructed in this study based on clinicopathological characteristics and PET/CT parameters might offer a basis by which to predict Classical EGFR status and provide a certain reference value for guiding the use of EGFR-tyrosine kinase inhibitor (EGFR-TKI) treatment in patients with lung adenocarcinoma.

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Section: Discussionsupporting

confidence: 90%

A Predictive Model of EGFR Mutation Status in Patients with Lung Adenocarcinoma Based on PET/CT Metabolic Indexes and Clinicopathological Variables

Yang¹,

Shi²,

Huang³

et al. 2020

Preprint

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“…as found in a previous study [24]. Some studies have shown that smoking is an independent predictor of EGFR mutations [14], whereas others have different results [23].…”

Section: Discussionsupporting

confidence: 65%

“…The TTF-1 positivity rate of those with the EGFR mutant was higher than that of those with the wild-type, as found in a previous study [24]. Some studies have shown that smoking is an independent predictor of EGFR mutations [14], whereas others have different results [23].…”

Section: Discussionmentioning

confidence: 55%

Lung adenocarcinoma: development of nomograms based on PET/CT images for prediction of epidermal growth factor receptor mutation status and subtypes

Huang

Cao

Zhou

et al. 2021

Nuclear Medicine Communications

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Objective To develop nomograms that combine clinical characteristics, computed tomographic (CT) features and 18F-fluorodeoxyglucose PET (18F-FDG PET) metabolic parameters for individual prediction of epidermal growth factor receptor (EGFR) mutation status and exon 19 deletion mutation and exon 21 point mutation (21 L858R) subtypes in lung adenocarcinoma. Methods In total 124 lung adenocarcinoma patients who underwent EGFR mutation testing and whole-body 18F-FDG PET/CT were enrolled. Each patient’s clinical characteristics (age, sex, smoking history, etc.), CT features (size, location, margins, etc.) and four metabolic parameters (SUVmax, SUVmean, MTV and TLG) were recorded and analyzed. Logistic regression analyses were performed to screen for significant predictors of EGFR mutation status and subtypes, and these predictors were presented as easy-to-use nomograms. Results According to the results of multiple regression analysis, three nomograms for individualized prediction of EGFR mutation status and subtypes were constructed. The area under curve values of three nomograms were 0.852 (95% CI, 0.783–0.920), 0.857 (95% CI, 0.778–0.937) and 0.893 (95% CI, 0.819–0.968) of EGFR mutation vs. wild-type, 19 deletion mutation vs. wild-type and 21 L858R vs. wild-type, respectively. Only calcification showed significant differences between the EGFR 19 deletion and 21 L858R mutations. Conclusion EGFR 21 L858R mutation was more likely to be nonsolid texture with air bronchograms and pleural retraction on CT images. And they were more likely to be associated with lower FDG metabolic activity compared with those wild-types. The sex difference was mainly caused by the 19 deletion mutation, and calcification was more frequent in them.

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“…Most of the EGFR mutations are measured by tumor tissue immunohistochemistry through wounded puncture or surgery. Yao et al (125) found a correlation between EGFR mutations and 18 F-fluorodeoxyglucose positron emission tomographycomputed tomography imaging, and attempted to use this non-invasive inspection as an independent predictor. It was also verified that circulating tumor DNA (ctDNA) in the plasma can be used to detect EGFR mutations in patients with NSCLC, providing information similar to that obtained from biopsies (126).…”

Section: Epidermal Growth Factor Receptor/ Kirsten Rat Sarcoma/anaplastic Lymphoma Kinase (Egfr/kras/alk) Axismentioning

confidence: 99%

Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value

et al. 2021

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Lung cancer is the leading cause of cancer-related death worldwide. Bone metastasis, which usually accompanies severe skeletal-related events, is the most common site for tumor distant dissemination and detected in more than one-third of patients with advanced lung cancer. Biopsy and imaging play critical roles in the diagnosis of bone metastasis; however, these approaches are characterized by evident limitations. Recently, studies regarding potential biomarkers in the serum, urine, and tumor tissue, were performed to predict the bone metastases and prognosis in patients with lung cancer. In this review, we summarize the findings of recent clinical research studies on biomarkers detected in samples obtained from patients with lung cancer bone metastasis. These markers include the following: (1) bone resorption-associated markers, such as N-terminal telopeptide (NTx)/C-terminal telopeptide (CTx), C-terminal telopeptide of type I collagen (CTx-I), tartrate-resistant acid phosphatase isoform 5b (TRACP-5b), pyridinoline (PYD), and parathyroid hormone related peptide (PTHrP); (2) bone formation-associated markers, including total serum alkaline phosphatase (ALP)/bone specific alkaline phosphatase(BAP), osteopontin (OP), osteocalcin (OS), amino-terminal extension propeptide of type I procollagen/carboxy-terminal extension propeptide of type I procollagen (PICP/PINP); (3) signaling markers, including epidermal growth factor receptor/Kirsten rat sarcoma/anaplastic lymphoma kinase (EGFR/KRAS/ALK), receptor activator of nuclear factor κB ligand/receptor activator of nuclear factor κB/osteoprotegerin (RANKL/RANK/OPG), C-X-C motif chemokine ligand 12/C-X-C motif chemokine receptor 4 (CXCL12/CXCR4), complement component 5a receptor (C5AR); and (4) other potential markers, such as calcium sensing receptor (CASR), bone sialoprotein (BSP), bone morphogenetic protein 2 (BMP2), cytokeratin 19 fragment/carcinoembryonic antigen (CYFRA/CEA), tissue factor, cell-free DNA, long non-coding RNA, and microRNA. The prognostic value of these markers is also investigated. Furthermore, we listed some clinical trials targeting hotspot biomarkers in advanced lung cancer referring for their therapeutic effects.

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Value of combining PET/CT and clinicopathological features in predicting EGFR mutation in Lung Adenocarcinoma with Bone Metastasis

Cited by 12 publications

References 42 publications

A Predictive Model of EGFR Mutation Status in Patients with Lung Adenocarcinoma Based on PET/CT Metabolic Indexes and Clinicopathological Variables

A Predictive Model of EGFR Mutation Status in Patients with Lung Adenocarcinoma Based on PET/CT Metabolic Indexes and Clinicopathological Variables

Lung adenocarcinoma: development of nomograms based on PET/CT images for prediction of epidermal growth factor receptor mutation status and subtypes

Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value

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