Risk factors and a new nomogram for predicting brain metastasis from lung cancer: a retrospective study - Wu, Bo; Zhou, Yujun; Yang, Yong; Zhou, Dong (Frontiers in Oncology, 2023)
Objective: This study aims to establish and validate a new nomogram for predicting Lung Cancer Patients with Brain Metastases by integrating data Methods: 266 patients diagnosed with lung cancer between 2016 and 2018 were collected from Guangdong Academy of Medical Sciences. The top 70% of patients were assigned as the primary cohort and the bottom 30% of patients were identified as an internal validation cohort. Patients were stratified by different variables. Univariate and multivariable logistics regression were applied to analyze the risk factors of brain metastases among lung cancer patients. Independent risk factors were used to construct nomogram. C-index was used to evaluate the prediction effect of nomogram.100 patients diagnosed with lung cancer between 2018 and 2019 were collected for external validation cohorts. The assessment of nomogram was carried out by the discrimination and calibration in the internal validation cohort and external validation cohort. Results: Among the 266 patients diagnosed with lung cancer, 166 patients have brain metastases. The gender, pathological type (PAT), leukocyte count (LCC) and Fibrinogen stage (FibS) were independent risk factors of brain metastases. And our newly established nomogram showed an effective discriminative ability to predict the probability of lung cancer patients with brain metastases, the C-index was 0.811. Conclusion: Our study provided a novel model that could be used for predicting brain metastases in lung cancer patients, thus providing more reliable evidence for clinical decision-making.