Abstract

BackgroundBrain metastasis (BM) is one of the most common failure patterns of pIIIA-N2 non-small cell lung cancer (NSCLC) after complete resection. Prophylactic cranial irradiation (PCI) can improve intracranial control but not overall survival. Thus, it is particularly important to identify the risk factors that are associated with BM and subsequently provide instructions for selecting patients who will optimally benefit from PCI.Methods and MaterialsBetween 2011 and 2014, patients with pIIIA-N2 NSCLC who underwent complete resection in our institution were reviewed and enrolled in the study. Clinical characteristics, pathological parameters, treatment mode, BM time, and overall survival were analyzed. A nomogram was built based on the corresponding parameters by Fine and Gray’s competing risk analysis to predict the 1-, 3-, and 5-year probabilities of BM. Receiver operating characteristic curves and calibration curves were chosen for validation. A statistically significant difference was set as P <0.05.ResultsA total of 517 patients were enrolled in our retrospective study. The median follow-up time for surviving patients was 53.2 months (range, 0.50–123.17 months). The median age was 57 (range, 25–80) years. Of the 517 patients, 122 (23.6%) had squamous cell carcinoma, 391 (75.6%) received adjuvant chemotherapy, and 144 (27.3%) received post-operative radiotherapy. The 1-, 3-, and 5-year survival rates were 94.0, 72.9, and 66.0%, respectively. The 1-, 3-, and 5-year BM rates were 5.4, 15.7, and 22.2%, respectively. According to the univariate analysis, female, non-smokers, patients with non-squamous cell carcinoma, bronchial invasion, perineural invasion, and patients who received adjuvant chemotherapy were more likely to develop BM. In a multivariate analysis, non-squamous cell carcinoma (subdistribution hazard ratios, SHR: 3.968; 95% confidence interval, CI: 1.743–9.040; P = 0.0010), bronchial invasion (SHR: 2.039, 95% CI: 1.325–3.139; P = 0.0012), perineural invasion (SHR: 2.514, 95% CI: 1.058–5.976; P = 0.0370), and adjuvant chemotherapy (SHR: 2.821, 95% CI: 1.424–5.589; P = 0.0030) were independent risk factors for BM. A nomogram model was established based on the final multivariable analysis result. The area under the curve was 0.767 (95% CI, 0.758–0.777).ConclusionsFor patients with IIIA-N2 NSCLC after complete resection, a nomogram was established based on clinicopathological factors and treatment patterns for predicting the BM. Based on this nomogram, patients with a high risk of BM who may benefit from PCI can be screened.

Highlights

  • Compared with early-stage non-small cell lung cancer (NSCLC), locally advanced NSCLC patients are more likely to develop brain metastasis (BM), nearly 30% of whom have BM within 2 years [1]

  • Eight randomized controlled trials of prophylactic cranial irradiation (PCI) in NSCLC suggested that PCI was associated with a decrease in the risk of BM but that its performance was still unsatisfactory in improving survival [2,3,4,5,6,7,8,9]

  • To the best of our knowledge, this study was the first and largest population-based study to develop a nomogram model for predicting the occurrence of BM in pIIIA-N2 NSCLC by competing risk analysis, in which the bias that is caused by death is considered

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Summary

Introduction

Compared with early-stage non-small cell lung cancer (NSCLC), locally advanced NSCLC patients are more likely to develop brain metastasis (BM), nearly 30% of whom have BM within 2 years [1]. A randomized phase III study [4] with fully resected stage IIIA-N2 NSCLC patients showed that PCI can lengthen the disease-free survival. It demonstrated a positive effect of screening patients with BM high-risk metastasis, which merits further study. A competing risk models is a combination of two or more distributions that represent failure modes that are “competing” to be the end event of the system that is being modeled. This model considers the effects of the other competed risks, so it can estimate the probability of the primary endpoint event concurrence more accurately.

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