Lung adenocarcinoma size as a predictor of distant metastasis: A CT scan-based measurement - Soewondo, Widiastuti; Adzhani, Fityay; Hanafi, Muchtar; Firdaus, Zaka J. (Narra Sains Indonesia, 2024)
Previous studies have associated tumor size with metastasis and prognosis in lung carcinoma; however, a precise cut-off for predicting distant metastasis in lung adenocarcinoma remains unclear. The aim of this study was to determine the cut-off point for predicting distant metastasis in lung adenocarcinoma. A cross-sectional study was conducted at Dr. Moewardi Hospital, Surakarta, Indonesia from January 2022 to September 2023. Total sampling was employed, involving patients over 18 years old with a confirmed diagnosis of lung adenocarcinoma based on lung computed tomography (CT) scan findings, who had not yet received chemotherapy and had confirmed metastasis outside the lung. The study's dependent variable was the incidence of distant metastasis, while the independent variable was lung adenocarcinoma size. Two experienced thoracic radiologists measured lung adenocarcinoma size by assessing the longest axis using chest multi-slice computed tomography (MSCT) in the lung window setting. Receiver operating characteristic (ROC) curve analysis determined the optimal tumor size cut-off for predicting distant metastasis. From a total of 956 thoracic cancer patients, 108 were diagnosed with lung adenocarcinoma. After applying the inclusion and exclusion criteria, 89 patients were eligible. In the present study, tumor size predicted 68.1% of distant metastasis cases, with a cut-off point of 7.25 cm, yielding a sensitivity of 61.9% and a specificity of 61.5%. Tumors >7.25 cm had a 2.60-fold higher risk of distant metastasis compared to smaller tumors, with larger tumors more likely to spread to various sites. In conclusion, lung adenocarcinomas larger than 7.25 cm have a 2.60-fold increased risk of distant metastasis, making tumor size a crucial predictive factor. The study provides valuable insights for radiologists and can improve diagnosis accuracy and treatment planning by emphasizing tumor size as a key factor in managing lung adenocarcinoma.