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, Alexander Hulsbergen Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Departments of Neurosurgery, Haaglanden Medical Center and Leiden University Medical Center , The Hague, Netherlands Search for other works by this author on: Oxford Academic Marco Mammi Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Neurosurgery Unit, Department of Neuroscience, University of Turin , Turin, Italy Search for other works by this author on: Oxford Academic Steven Nagtegaal Department of Radiation Oncology, University Medical Center Utrecht , Utrecht, Netherlands Search for other works by this author on: Oxford Academic Asad Malk Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Search for other works by this author on: Oxford Academic Vasileios Kavouridis Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Search for other works by this author on: Oxford Academic Timothy Smith Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Search for other works by this author on: Oxford Academic Bryan Iorgulescu Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Search for other works by this author on: Oxford Academic Rania Mekary Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women’s Hospital , Boston, MA, USA Search for other works by this author on: Oxford Academic Joost Verhoeff Department of Radiation Oncology, University Medical Center Utrecht , Utrecht, Netherlands Search for other works by this author on: Oxford Academic Marike Broekman Departments of Neurosurgery, Haaglanden Medical Center and Leiden University Medical Center , The Hague, Netherlands Search for other works by this author on: Oxford Academic
John Phillips Department of Radiation Oncology, Brigham and Women’s Hospital , Boston, MA, USA Search for other works by this author on: Oxford Academic
Neuro-Oncology Advances, Volume 2, Issue Supplement_2, August 2020, Page ii16, https://doi.org/10.1093/noajnl/vdaa073.062
Published:
04 August 2020
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Alexander Hulsbergen, Marco Mammi, Steven Nagtegaal, Asad Malk, Vasileios Kavouridis, Timothy Smith, Bryan Iorgulescu, Rania Mekary, Joost Verhoeff, Marike Broekman, John Phillips, 75. PROGRAMMED DEATH RECEPTOR LIGAND ONE EXPRESSION MAY INDEPENDENTLY PREDICT SURVIVAL IN NON-SMALL CELL LUNG CARCINOMA BRAIN METASTASES PATIENTS RECEIVING IMMUNOTHERAPY, Neuro-Oncology Advances, Volume 2, Issue Supplement_2, August 2020, Page ii16, https://doi.org/10.1093/noajnl/vdaa073.062
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Abstract
BACKGROUND
Programmed death receptor ligand one (PD-L1) expression is known to predict response to PD-1/PD-L1 inhibitors in non-small cell lung cancer (NSCLC). However, the predictive role of this biomarker in brain metastases (BMs) is unknown. The aim of this study was to assess whether PD-L1 expression predicts survival in patients with NSCLC BMs treated with PD-1/PD-L1 inhibitors, after adjusting for established prognostic models.
METHODS
In this multi-institutional retrospective cohort study, we identified NSCLC-BM patients treated with PD-1/PD-L1 inhibitors after local BM treatment (radiotherapy or neurosurgery) but before intracranial progression. Cox proportional hazards models were used to assess predictive value PD-L1 expression for overall survival (OS) and intracranial progression free survival (IC-PFS).
RESULTS
Forty-eight BM patients with available PD-L1 expression were identified. PD-L1 expression was positive in 33 patients (69%). Median survival was 26 months. In univariable analysis, PD-L1 predicted favorable OS (HR = 0.44; 95% CI 0.19 – 1.02; p = 0.055). This effect persisted after correcting for lung-graded prognostic assessment (lung-GPA) and other identified potential confounders (HR = 0.24; 95% CI = 0.10 – 0.61; p = 0.002). Moreover, when modeled as a continuous variable, there appeared to be a proportional relationship between percentage of PD-L1 expression and survival (HR = 0.86 per 10% expression, 95% CI 0.77 – 0.98, p = 0.02). In contrast, PD-L1 expression did not predict IC-PFS in uni- or multivariable analysis (adjusted HR = 0.54, 95% CI 0.26 – 1.14, p = 0.11).
CONCLUSIONS
In patients with NSCLC-BMs treated with PD-1/PD-L1 checkpoint inhibitors and local treatment, PD-L1 expression may predict OS independent of lung-GPA. IC-PFS did not show association with PD-L1 expression, although the present analysis may lack power to assess this. Larger studies are required to validate these findings.
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© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
Topic:
- radiation therapy
- wegener granulomatosis
- lung
- metastatic malignant neoplasm to brain
- biological markers
- non-small-cell lung carcinoma
- immunotherapy
- ligands
- neurosurgery specialty
- neurosurgical procedures
- patient prognosis
- metallic stents
- interval data
- death domain receptors
- progression-free survival
- immune checkpoint inhibitors
- programmed cell death 1 ligand 1
Issue Section:
Supplement Abstracts > Society for Neuro-Oncology Virtual Conference on Brain Metastases, August 14, 2020, held in association with the AANS/CNS Section on Tumors
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