Gui Hong Zhang1, Yue Jiao Liu1, Ming De Ji2. 1. Department of Clinical Laboratory, Affiliated Hospital of Nanjing University of Traditional Chinese Medicine, No.155, Han'Zhong Road, Qinhuai, Nanjing, 210029, China. 2. Department of Clinical Laboratory, Affiliated Hospital of Nanjing University of Traditional Chinese Medicine, No.155, Han'Zhong Road, Qinhuai, Nanjing, 210029, China. mingdej1982@163.com.
Abstract
PURPOSE: To make a comprehensive population-based study on risk and prognostic factors of brain metastasis from lung cancer. METHODS: A total of 91,643 patients diagnosed with lung cancer from 2010 to 2018 were collected from the Surveillance, Epidemiology and End results (SEER) database. To analyze the risk and prognostic factors of brain metastasis among lung cancer patients, both Logistic and Cox regression methods were applied, respectively. Also, the competing risk regression model was performed to establish a new nomogram to predict cancer-specific survival (CSS). RESULTS: Among the 91,643 lung cancer patients, 10,855 were found to have brain metastasis, with the incidence of 11.84%. The residence, age, race, income, primary site, histological type, extracranial metastasis, T stage, and N stage were all found to be independent risk factors of brain metastasis. The median overall survival (OS) of brain metastasis patients was limited to 6.08 months. By dividing patients randomly into a primary cohort with 7237 patients and a validation cohort with 3618 patients, a conclusion that the income, race, gender, age, histological type, extracranial metastasis, T stage, and N stage were all associated with the prognosis of brain metastasis was drawn. Our established primary-cohort-based new nomogram showed a good discriminative ability in predicting the probability of CSS among patients with brain metastasis, and the C-index was 0.62. Besides, the calibration curves for CSS also showed that the predicted survival by nomogram was consistent with the actual survival in the validation cohort. CONCLUSION: Our study shall provide a deeper insight into the risk factors and prognosis of brain metastasis among lung cancer patients.
PURPOSE: To make a comprehensive population-based study on risk and prognostic factors of brain metastasis from lung cancer. METHODS: A total of 91,643 patients diagnosed with lung cancer from 2010 to 2018 were collected from the Surveillance, Epidemiology and End results (SEER) database. To analyze the risk and prognostic factors of brain metastasis among lung cancer patients, both Logistic and Cox regression methods were applied, respectively. Also, the competing risk regression model was performed to establish a new nomogram to predict cancer-specific survival (CSS). RESULTS: Among the 91,643 lung cancer patients, 10,855 were found to have brain metastasis, with the incidence of 11.84%. The residence, age, race, income, primary site, histological type, extracranial metastasis, T stage, and N stage were all found to be independent risk factors of brain metastasis. The median overall survival (OS) of brain metastasis patients was limited to 6.08 months. By dividing patients randomly into a primary cohort with 7237 patients and a validation cohort with 3618 patients, a conclusion that the income, race, gender, age, histological type, extracranial metastasis, T stage, and N stage were all associated with the prognosis of brain metastasis was drawn. Our established primary-cohort-based new nomogram showed a good discriminative ability in predicting the probability of CSS among patients with brain metastasis, and the C-index was 0.62. Besides, the calibration curves for CSS also showed that the predicted survival by nomogram was consistent with the actual survival in the validation cohort. CONCLUSION: Our study shall provide a deeper insight into the risk factors and prognosis of brain metastasis among lung cancer patients.
Authors: J L Ruiz-Cerdá; A Soto-Poveda; S Luján-Marco; A Loras-Monfort; M Trassierra-Villa; R Rogel-Bertó; F Boronat-Tormo Journal: Actas Urol Esp Date: 2016-03-22 Impact factor: 0.994
Authors: Paul W Sperduto; T Jonathan Yang; Kathryn Beal; Hubert Pan; Paul D Brown; Ananta Bangdiwala; Ryan Shanley; Norman Yeh; Laurie E Gaspar; Steve Braunstein; Penny Sneed; John Boyle; John P Kirkpatrick; Kimberley S Mak; Helen A Shih; Alex Engelman; David Roberge; Nils D Arvold; Brian Alexander; Mark M Awad; Joseph Contessa; Veronica Chiang; John Hardie; Daniel Ma; Emil Lou; William Sperduto; Minesh P Mehta Journal: JAMA Oncol Date: 2017-06-01 Impact factor: 31.777
Authors: Allison M Martin; Daniel N Cagney; Paul J Catalano; Laura E Warren; Jennifer R Bellon; Rinaa S Punglia; Elizabeth B Claus; Eudocia Q Lee; Patrick Y Wen; Daphne A Haas-Kogan; Brian M Alexander; Nancy U Lin; Ayal A Aizer Journal: JAMA Oncol Date: 2017-08-01 Impact factor: 31.777