Abstract 1580
Background
Brain metastases (BMs) account for a relatively large proportion of patients with metastatic non-small cell lung cancer (NSCLC) both at the time of diagnosis and during the course of disease, which is a major cause leading to a significant increase in cancer-related mortality for NSCLC patients. We aimed to build a novel risk classification system to predict overall survival (OS) of patients presenting with BMs at the first diagnosis of NSCLC.
Methods
Data on NSCLC patients with BMs was extracted from the SEER database between 2010 and 2013. All cases were randomly divided into the training cohort and validation cohort (7:3). Cox regression was performed to select the independent predictors of OS. A nomogram was established for predicting 6-, 12- and 18-month OS. The prognostic performance of nomogram was evaluated using concordance indexes (C-indexes), calibration curves, and decision curve analyses (DCAs). All statistical analysis was performed with R software.
Results
According to the multivariate Cox regression of the training set, the following variables were contained in the nomogram prognostic model: age, marital status, sex, race, primary site, histological type, T stage, N stage, metastatic pattern, whether received radiotherapy and chemotherapy. The nomogram displayed good accuracy in predicting 6, 12 and 18 months OS. The C-indexes of training set and validation set were 0.729 and 0.723, respectively. The calibration curves showed excellent consistency between the actual results and the nomogram prediction, and the DCAs exhibited great clinical utility of the model. A new risk classification system based on nomogram scores was introduced to classify NSCLC patients with BMs into three subgroups. In the training cohort, the median OS of patients in the low-, intermediate- and high-risk groups was 11.0 months (95% confidence interval [CI] 10.3–11.7), 5.0 months (95% CI 4.6–5.4), and 2.0 months (95% CI 1.9–2.1), respectively.
Conclusions
We established a risk stratification system based on nomogram scores to predict the OS of patients presenting with BMs at initial diagnosis of NSCLC. These predictive models can act as auxiliary tools to guide treatment strategies and prognostic evaluation.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
2041 - Efficacy results of selective AXL inhibitor bemcentinib with pembrolizumab following chemo in patients with NSCLC
Presenter: Jose Trigo Perez
Session: Poster Display session 1
Resources:
Abstract
5444 - Analysis of the tumor microenvironment and tumor genotype through different stages of lung adenocarcinoma
Presenter: Peter Zink
Session: Poster Display session 1
Resources:
Abstract
3124 - Does Progress achieved in the Treatment of Patients with Metastatic Non-Small-Cell Lung Cancer (NSCLC) reach the Elderly Population?
Presenter: Jorune Suipyte
Session: Poster Display session 1
Resources:
Abstract
5142 - Prognostic factors for non-small cell lung cancer patients with driver mutation negative and brain metastases (HOT 1701)
Presenter: Yoshihito Ohhara
Session: Poster Display session 1
Resources:
Abstract
4442 - Comparison of real-world response rate (rwRR) to RECIST-based response rate in patients with advanced non-small cell lung cancer (aNSCLC)
Presenter: Xinran Ma
Session: Poster Display session 1
Resources:
Abstract
5405 - Estimating the cost and survival impact of new aNSCLC therapies in Canada with the iTEN model
Presenter: Parneet Kaur Cheema
Session: Poster Display session 1
Resources:
Abstract
1893 - SMARCA4 Deficient Non-Small Cell Lung Cancer (NSCLC): A Comprehensive Genomic Profiling (CGP) Study
Presenter: Stephen Graziano
Session: Poster Display session 1
Resources:
Abstract
5582 - Exploring Resistance to Nivolumab [NIV] applying an Immune Genomic Signature (IGS) in advanced pretreated NSCLC [PRINCiPe study]
Presenter: Sara Pilotto
Session: Poster Display session 1
Resources:
Abstract
1408 - DNA damage repair deficiency is associated with early resistance to crizotinib: whole-genome analysis in non-small cell lung cancer patients with ALK-fusion
Presenter: Dongyun He
Session: Poster Display session 1
Resources:
Abstract
5751 - Phase 3 ALTA-3 study of brigatinib (BRG) vs alectinib (ALC) in patients (pts) with advanced anaplastic lymphoma kinase (ALK)−positive non–small cell lung cancer (NSCLC) that progressed on crizotinib (CRZ)
Presenter: Sanjay Popat
Session: Poster Display session 1
Resources:
Abstract