Prognostic model for brain metastases from lung adenocarcinoma identified with epidermal growth factor receptor mutation status. Issue 5 (9th June 2017)

• Record Type: Journal Article
• Authors: Li, Hongwei; Wang, Weili; Jia, Haixia; Lian, Jianhong; Cao, Jianzhong; Zhang, Xiaqin; Song, Xing; Jia, Sufang; Li, Zhengran; Cao, Xing; Zhou, Wei; Han, Songye; Yang, Weihua; Xi, Yanfen; Lian, Shenming
• Is Part Of: Thoracic cancer. Volume 8:Issue 5(2017)
• Page Start: 436
• Page End: 442
• Publication Date: 2017-06-09
• Subjects: Brain metastases -- EGFR mutations -- lung adenocarcinoma -- prognostic; Chest -- Cancer -- Periodicals; Chest -- Cancer -- Treatment -- Periodicals; Chest -- Surgery -- Periodicals; 616.99494005
• DOI: 10.1111/1759-7714.12460
• Languages: English
• ISSNs: 1759-7706

Abstract

Abstract : Background: Several indices have been developed to predict survival of brain metastases (BM) based on prognostic factors. However, such models were designed for general brain metastases from different kinds of cancers, and prognostic factors vary between cancers and histological subtypes. Recently, studies have indicated that epidermal growth factor receptor (EGFR) mutation status may be a potential prognostic biological factor in BM from lung adenocarcinoma. Thus, we sought to define the role of EGFR mutation in prognoses and introduce a prognostic model specific for BM from lung adenocarcinoma. Methods: Data of 256 patients with BM from lung adenocarcinoma identified with EGFR mutations were collected. Independent prognostic factors were confirmed using a Cox regression model. The new prognostic model was developed based on the results of multivariable analyses. The score of each factor was calculated by six‐month survival. Prognostic groups were divided into low, medium, and high risk based on the total scores. The prediction ability of the new model was compared to the three existing models. Results: EGFR mutation and Karnofsky performance status were independent prognostic factors and were thus integrated into the new prognostic model. The new model was superior to the three other scoring systems regarding the prediction of three, six, and 12‐month survival by pairwise comparison of the area under the curve. Conclusion: Our proposed prognostic model specific for BM from lung adenocarcinoma incorporating EGFR mutation status was valid in predicting patient survival. Further verification is warranted, with prospective testing using large sample sizes.