Prediction of distant organ metastasis and overall survival of lung cancer patients: a SEER population−based cohort study - Hao, Yongping; Li, Guang (Frontiers in Oncology, 2023)
Background Distant organ metastasis is a common event in lung cancer (LC). However, the preferential metastatic pattern of different pathological types of LC and its effect on prognosis have not been comprehensively elucidated. This study aimed to explore the distant metastasis pattern and construct nomograms predicting the metastasis and survival of LC patients using the Surveillance, Epidemiology, and End Results (SEER) database. Methods LC data were downloaded from the SEER database to conduct logistic regression and investigate risk factors for developing organ metastasis. A Cox regression analysis was conducted to investigate prognostic factors of LC. A Kaplan–Meier analysis was used to estimate overall survival outcomes. Nomograms were constructed to predict the probability of organ metastasis and the 1-, 3- and 5-year survival probability of LC patients. Receiver operating characteristic curves were used to evaluate the diagnostic accuracy of the nomograms. All statistical analyses were conducted within R software. Results The liver is the most common metastatic organ of small cell carcinoma. The brain is the most likely metastasis site of large cell carcinoma, and bone is the most likely metastasis site for squamous cell carcinoma and adenocarcinoma. Patients with triple metastases (brain-bone-liver) have the worst prognosis, and for nonsquamous carcinoma with single organ metastasis, liver metastases conferred the worst prognosis. Our nomograms based on clinical factors could predict the metastasis and prognosis of LC patients. Conclusion Different pathological types of LC have different preferential metastatic sites. Our nomograms showed good performance in predicting distant metastasis and overall survival. These results will provide a reference for clinicians and contribute to clinical evaluations and individualized therapeutic strategies.