@article{Song2024, 
author = {Lijun Song and Yu Wang and Xue Li and Yi Liu and Bingyi Yin and Daorui Li and Hongsheng Lin and Yuqi Zhang},
title = {Random forests to predict survival of octogenarians with brain metastases from nonsmall-cell lung cancer},
year = {2024},
journal = {Brain Science Advances},
volume = {10},
number = {1},
pages = {38-55},
keywords = {octogenarian, NSCLC, brain metastases, random forests, nomogram},
url = {https://www.sciopen.com/article/10.26599/BSA.2024.9050021},
doi = {10.26599/BSA.2024.9050021},
abstract = {Background:To create and validate nomograms for the personalized prediction of survival in octogenarians with newly diagnosed nonsmall-cell lung cancer (NSCLC) with sole brain metastases (BMs).Methods:Random forests (RF) were applied to identify independent prognostic factors for building nomogram models. The predictive accuracy of the model was evaluated based on the receiver operating characteristic (ROC) curve, C-index, and calibration plots.Results:The area under the curve (AUC) values for overall survival at 6, 12, and 18 months in the validation cohort were 0.837, 0.867, and 0.849, respectively; the AUC values for cancer-specific survival prediction were 0.819, 0.835, and 0.818, respectively. The calibration curves visualized the accuracy of the model.Conclusion:The new nomograms have good predictive power for survival among octogenarians with sole BMs related to NSCLC.}
}