The diagnostic and predictive efficacy of 18F-FDG PET/CT metabolic parameters for EGFR mutation status in non-small-cell lung cancer: A meta-analysis

Abstract

PurposeTo investigate the predictive performance of the maximum standardized uptake value (SUVmax) and mean standardized uptake value (SUVmean) of primary lesions based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for EGFR mutation status in patients with non-small cell lung cancer (NSCLC). MethodsThe PubMed/Medline, Embase, Cochrane Library and Web of Science databases were searched as of January 1, 2021. Studies whose reported data could be used to construct contingency tables were included. Study characteristics were extracted, and methodological quality assessment was conducted by two separate reviewers using the Quality Assessment of Diagnostic Accuracy Studies. The pooled sensitivity, specificity and area under the summary receiver operating characteristic curve (AUROC) were calculated. The possible causes of heterogeneity were analysed by meta-regression. ResultsThe 18 included studies had a total of 4024 patients. The majority of the studies showed a low to unclear risk of bias and concerns of applicability. For differentiating EGFR-mutant NSCLC from wild-type NSCLC, the pooled sensitivity and specificity were 71 % and 60 % for SUVmax and 64 % and 63 % for SUVmean, respectively. The summary AUROCs of SUVmax and SUVmean were 0.69 (95 % CI, 0.65–0.73) and 0.68 (95 % CI, 0.64–0.72), respectively. The meta-regression analysis indicated that blindness to EGFR mutation test results, the number of readers and the number of PET/CT scanners were possible causes of heterogeneity. ConclusionsOur meta-analysis implied that SUVmax and SUVmean of primary lesions from 18F-FDG PET/CT harboured moderate predictive efficacy for the EGFR mutation status of NSCLC.