Abstract
(1) Background: To investigate the association between maximum standardized uptake value (SUV(max)) based on (18)F-FDG PET/CT and EGFR mutation status in lung adenocarcinoma. (2) Methods: A total of 366 patients were retrospectively collected and divided into the EGFR mutation group (n = 228) and EGFR wild-type group (n = 138) according to their EGFR mutation status. The two groups' general information and PET/CT imaging parameters were compared. A hierarchical binary logistic regression model was used to assess the interaction effect on the relationship between SUV(max) and EGFR mutation in different subgroups. Univariate and multivariate logistic regression was used to analyze the association between SUV(max) and EGFR mutation. After adjusting for confounding factors, a generalized additive model and smooth curve fitting were applied to address possible non-linearities. (3) Results: Smoking status significantly affected the relationship between SUV(max) and EGFR mutation (p for interaction = 0.012), with an interaction effect. After adjusting for age, gender, nodule type, bronchial sign, and CEA grouping, in the smoking subgroup, curve fitting results showed that the relationship between SUV(max) and EGFR mutation was approximately linear (df = 1.000, c(2) = 3.897, p = 0.048); with the increase in SUV(max), the probability of EGFR mutation gradually decreased, and the OR value was 0.952 (95%CI: 0.908-0.999; p = 0.045). (4) Conclusions: Smoking status can affect the relationship between SUV(max) and EGFR mutation status in lung adenocarcinoma, especially in the positive smoking history subgroup. Fully understanding the effect of smoking status will help to improve the accuracy of SUV(max) in predicting EGFR mutations.