Fanrong Zhang1, Weihui Zheng1, Lisha Ying1, Junzhou Wu1, Shaoyuan Wu2, Shenglin Ma3, Dan Su4. 1. Cancer Research Institute, Zhejiang Cancer Hospital and Key Laboratory Diagnosis and Treatment Technology on Thoracic Oncology of Zhejiang Province, Hangzhou, China. 2. School of Life Sciences, Jiangsu Normal University, Xuzhou, China. 3. Nanjing Medical University Affiliated Hangzhou Hospital (Hangzhou First People's Hospital), Hangzhou, China. mashenglin@medmail.com.cn. 4. Cancer Research Institute, Zhejiang Cancer Hospital and Key Laboratory Diagnosis and Treatment Technology on Thoracic Oncology of Zhejiang Province, Hangzhou, China. sudan@zjcc.org.cn.
Abstract
PURPOSE: Brain metastasis is a major cause leading to the failure of treatment management for non-small cell lung cancer (NSCLC) patients. The goal of this study was to establish an effective nomogram for prediction of brain metastases of resected NSCLC patients. METHODS: We retrospectively investigated 637 operable NSCLC patients who received treatment at Zhejiang Cancer Hospital, China. A Cox proportional hazards regression model was performed to identify significant risk factors, and a nomogram was developed for predicting 3- and 5-year brain metastases rates. RESULTS: Multivariate analysis identified four independent risk factors: neuron-specific enolase, histological type, number of metastatic lymph nodes, and tumor grade, and a nomogram was developed based on these factors. The effectiveness of the nomogram was validated using an internal bootstrap resampling approach, showing that the nomogram exhibited a sufficient level of discrimination according to the C-index (0.74, 95 % confidence interval 0.67-0.82). CONCLUSIONS: The nomogram developed in this study demonstrated its discrimination capability for predicting 3- and 5-year occurrence of brain metastases, and can be used to identify high-risk patients.
PURPOSE: Brain metastasis is a major cause leading to the failure of treatment management for non-small cell lung cancer (NSCLC) patients. The goal of this study was to establish an effective nomogram for prediction of brain metastases of resected NSCLCpatients. METHODS: We retrospectively investigated 637 operable NSCLCpatients who received treatment at Zhejiang Cancer Hospital, China. A Cox proportional hazards regression model was performed to identify significant risk factors, and a nomogram was developed for predicting 3- and 5-year brain metastases rates. RESULTS: Multivariate analysis identified four independent risk factors: neuron-specific enolase, histological type, number of metastatic lymph nodes, and tumor grade, and a nomogram was developed based on these factors. The effectiveness of the nomogram was validated using an internal bootstrap resampling approach, showing that the nomogram exhibited a sufficient level of discrimination according to the C-index (0.74, 95 % confidence interval 0.67-0.82). CONCLUSIONS: The nomogram developed in this study demonstrated its discrimination capability for predicting 3- and 5-year occurrence of brain metastases, and can be used to identify high-risk patients.
Authors: Whitney S Brandt; Ilies Bouabdallah; Kay See Tan; Bernard J Park; Prasad S Adusumilli; Daniela Molena; Manjit S Bains; James Huang; James M Isbell; Matthew J Bott; David R Jones Journal: J Thorac Cardiovasc Surg Date: 2017-11-13 Impact factor: 5.209
Authors: George D Wilson; Matthew D Johnson; Samreen Ahmed; Paola Yumpo Cardenas; Inga S Grills; Bryan J Thibodeau Journal: Oncotarget Date: 2018-05-25