Backgroud: The biopsy samples might be the only tumor material available for testing the EGFR mutation status in some cases, but these samples are often composed of variable ratios of tumor to normal cells. In this study, we sought to build a scoring system to predict Epidermal growth factor receptor (EGFR) exon 19 mutation in lung adenocarcinoma by clinical and radiological features.
Methods: Enrolled in this study were 601 patients with lung adenocarcinoma. Qualitative evaluation of the clinical and radiological features included 25 aspects. Statistical analysis was used to assess the association of these features between the EGFR wild type and exon 19 mutation, based on a clinical scoring system built by the statistical model and the experience of the radiologists.
Results: EGRF-exon-19-mutation was associated with the female gender [odds ratios (OR), 2.573; 95% confidence intervals (CI), 1.689-3.920], tumor maximum diameter (OR, 0.357; 95% CI, 0.235-0.542), the absence of emphysema (OR, 0.202; 95% CI, 0.110-0.368), the absence of fibrosis (OR, 0.168; 95% CI, 0.083-0.339), and pleural retraction (OR, 2.170; 95% CI, 1.434-3.285). The clinical scoring model assigned 3 points to the female gender, 2 points to small tumor maximum diameter (≤34.5 mm), 2 to the absence of emphysema, 2 to the absence of fibrosis, and 1 to the presence of pleural retraction.
Conclusions: The scoring system based on the statistical analysis of clinical and radiological features may be a new alternative to the prediction of EGFR mutation subtypes.