Abstract
Purpose: This study assessed the ability of metabolic parameters from 18Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and clinicopathological data to predict epidermal growth factor receptor (EGFR) expression/mutation status in patients with lung adenocarcinoma and to develop a prognostic model based on differences in EGFR expression status, to enable individualized targeted molecular therapy.Patients and Methods: Metabolic parameters and clinicopathological data from 200 patients diagnosed with lung adenocarcinoma between July 2009 and November 2016, who underwent 18F-FDG PET/CT and EGFR mutation testing, were retrospectively evaluated. Multivariate logistic regression was applied to significant variables to establish a prediction model for EGFR mutation status. Overall survival for both mutant and wild-type EGFR was analyzed to establish a multifactor Cox regression model.Results: Of the 200 patients, 115 (58%) exhibited EGFR mutations and 85 (42%) were wild-type. Among selected metabolic parameters, metabolic tumor volume (MTV) demonstrated a significant difference between wild-type and mutant EGFR mutation status, with an area under the receiver operating characteristic curve (AUC) of 0.60, which increased to 0.70 after clinical data (smoking status) were combined. Survival analysis of wild-type and mutant EGFR yielded mean survival times of 34.451 (95% CI 28.654–40.249) and 53.714 (95% CI 44.331–63.098) months, respectively. Multivariate Cox regression revealed that mutation type, tumor stage, and thyroid transcription factor-1 (TTF-1) expression status were the main factors influencing patient prognosis. The hazard ratio for mutant EGFR was 0.511 (95% CI 0.303–0.862) times that of wild-type, and the risk of death was lower for mutant EGFR than for wild-type. The risk of death was lower in TTF-1-positive than in TTF-1-negative patients.Conclusion: 18F-FDG PET/CT metabolic parameters combined with clinicopathological data demonstrated moderate diagnostic efficacy in predicting EGFR mutation status and were associated with prognosis in mutant and wild-type EGFR non-small-cell lung cancer (NSCLC), thus providing a reference for individualized targeted molecular therapy.
Highlights
Lung cancer is one of the most aggressive malignant tumors, with high rates of morbidity and mortality worldwide, and has recently risen to rank first among malignant tumors [1,2,3]
The starting point for Overall survival (OS) was the date of positron emission tomography/computed tomography (PET/CT) examination and the end point was defined as the date of telephonic follow-up or death
We investigated the association between PET/CT metabolic parameters and clinicopathological data and epidermal growth factor (EGFR) mutation status, and found a higher frequency of EGFR mutations in females and non-smokers
Summary
Lung cancer is one of the most aggressive malignant tumors, with high rates of morbidity and mortality worldwide, and has recently risen to rank first among malignant tumors [1,2,3]. Among all pathological categories of lung cancer, non-small cell lung cancer (NSCLC) is the most common, accounting for ∼85% of lung cancers [4,5,6]. Recent advances in the understanding of the molecular biology of NSCLC [7, 8] have attracted attention for molecular-driven targeted therapy. Tyrosine kinase inhibitors (TKIs), such as gefitinib and erlotinib, have been introduced [9] and have become an effective treatment for patients with mutations in the epidermal growth factor (EGFR) gene [10, 11]. Several studies [12,13,14] have described that the EGFR mutation status is the main factor in predicting the therapeutic effect of EGFR- TKIs. it is essential to identify EGFR mutation status before attempts at targeted therapy
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