An anomogram to predict brain metastasis of non-small cell lung cancer after surgery
10.16571/j.cnki.1008-8199.2017.08.013
- VernacularTitle:非小细胞肺癌术后患者脑转移风险预测列线图的构建
- Author:
Fangbo CUI
;
Xiangming CAO
;
Min LI
;
Eryun GAO
;
Wei WANG
;
Fenglin ZHANG
- Keywords:
Non-small cell lung cancer;
Brain metastasis;
Risk factors;
Nomogram
- From:
Journal of Medical Postgraduates
2017;30(8):849-853
- CountryChina
- Language:Chinese
-
Abstract:
Objective Brain metastasis of non-small cell lung cancer (NSCLC) significantly reduces the survival time of the patients, and no effective tool is yet available for the prediction of the risk.This study aimed to develop an effective and feasible nomogram for predicting brain metastasis of NSCLC after radical surgery.Methods This retrospective study included 636 cases of NSCLC treated by radical resection of the tumor in our hospitals between January 2010 and January 2014.Based on the analysis of the risk factors for brain metastasis, we developed a nomogram using logistic regression with the R-language, calculated the confidence interval (CI) of the C-index using the bootstrap, and then internally verified the overfitting degree of the model to evaluate its stability.Results Brain metastasis developed in 94 of the 636 patients.According to the results logistic regression analysis, the risk factors for brain metastasis included history of cigarette smoking (OR=1.783, 95% CI: 1.037-3.066), pathological types (OR=0.453, 95% CI: 0.275-0.744), the T stage (OR=2.047, 95% CI: 1.511-2.774), and the N stage (OR=1.588, 95% CI: 1.154-2.184).The nomogram showed a coefficient of coincidence of 0.73 (0.71-0.82) and a mean absolute error rate of 0.012, which indicated an excellent stability.Conclusion The nomogram we developed can be used to predict the risk of brain metastasis in individual NSCLC patients after surgery, contributing to follow-up programs and preventive strategies for brain metastasis.
