Can 18F-FDG PET/CT predict EGFR status in patients with non-small cell lung cancer? A systematic review and meta-analysis

Objectives This study aimed to explore the diagnostic significance of F-18-fluorodeoxyglucose (F-18-FDG) positron emission tomography (PET)/CT for predicting the presence of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC). Design A systematic review and meta-analysis. Data sources The PubMed, EMBASE and Cochrane library databases were searched from the earliest available date to December 2020. Eligibility criteria for selecting studies The review included primary studies that compared the mean maximum of standard uptake value (SUVmax) between wild-type and mutant EGFR, and evaluated the diagnostic value of F-18-FDG PET/CT using SUVmax for prediction of EGFR status in patients with NSCLC. Data extraction and synthesis The main analysis was to assess the sensitivity and specificity, the positive diagnostic likelihood ratio (DLR+) and DLR-, as well as the diagnostic OR (DOR) of SUVmax in prediction of EGFR mutations. Each data point of the summary receiver operator characteristic (SROC) graph was derived from a separate study. A random effects model was used for statistical analysis of the data, and then diagnostic performance for prediction was further assessed. Results Across 15 studies (3574 patients), the pooled sensitivity for F-18-FDG PET/CT was 0.70 (95% CI 0.60 to 0.79) with a pooled specificity of 0.59 (95% CI 0.52 to 0.66). The overall DLR+ was 1.74 (95% CI 1.49 to 2.03) and DLR- was 0.50 (95% CI 0.38 to 0.65). The pooled DOR was 3.50 (95% CI 2.37 to 5.17). The area under the SROC curve was 0.68 (95% CI 0.64 to 0.72). The likelihood ratio scatter plot based on average sensitivity and specificity was in the lower right quadrant. Conclusion Meta-analysis results showed F-18-FDG PET/CT had low pooled sensitivity and specificity. The low DOR and the likelihood ratio scatter plot indicated that F-18-FDG PET/CT should be used with caution when predicting EGFR mutations in patients with NSCLC.