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Prognostic factors for non-small cell lung cancer patients with driver mutation negative and brain metastases (HOT 1701)
- Source :
- Annals of Oncology. 30:v650-v651
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Background Non-small cell lung cancer (NSCLC) is characterized by a high incidence of brain metastasis (BM) and the prognosis of NSCLC patients with BM is poor. Previous study demonstrated four prognostic factors, which were age, poor PS, presence of extracranial metastases (ECM), and number of BM, in NSCLC patients with BM. This study aimed to identify prognostic factors and clarify the survival in NSCLC patients with BM at the time of a diagnosis. Methods A total of 566 NSCLC patients with BM from 15 institutions between January 2008 and December 2014. Among them, 176 patients had driver mutation, such as EGFR mutation and ALK-rearrangement, and 390 patients did not. This retrospective study focused on the 390 NSCLC patients without driver mutation, and identified clinical prognostic factors using Cox proportional hazards model. Moreover, we validated the disease specific Graded prognostic assessment (DS-GPA) in this cohort. Results Median OS was 7.6 months, respectively (95% confidence interval [CI]; 6.5-8.7, data cut-off; December 2018). Multivariate analyses demonstrated the following independent prognostic factors; gender male (P = 0.001), age > 64 years (P = 0.009), poor PS (P Conclusions Prognosis of NSCLC patients with EGFR, ALK negative and BM is poor. In addition to the known prognostic factors such as DS-GPA, this study shown that male, T factor, N factor, and histological type of non-adenocarcinoma, had a prognostic role in NSCLC patients with driver mutation negative and BM. Clinical trial identification UMIN000030313, 08/12/2017. Legal entity responsible for the study Hokkaido Lung Cancer Clinical Study Group Trial: HOT. Funding Has not received any funding. Disclosure All authors have declared no conflicts of interest.
Details
- ISSN :
- 09237534
- Volume :
- 30
- Database :
- OpenAIRE
- Journal :
- Annals of Oncology
- Accession number :
- edsair.doi...........13bd84f1a40c187624b78b235c48e010
- Full Text :
- https://doi.org/10.1093/annonc/mdz260.101