A Nomogram to Predict Brain Metastases of Resected Non-Small Cell Lung Cancer Patients

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.