Abstract
Purpose: Programmed death receptor ligand 1 (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 and Materials: In this multi-institutional retrospective cohort study, we identified patients with NSCLC-BM treated with PD-1/PD-L1 inhibitors after local BM treatment (radiation therapy or neurosurgery) but before intracranial progression. Cox proportional hazards models were used to assess the predictive value of PD-L1 expression for overall survival (OS) and intracranial progression–free survival (IC-PFS). Results: Forty-eight patients with BM 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 (hazard ratio [HR], 0.44; 95% confidence interval [CI], 0.19-1.02; P =.055). This effect persisted after correcting for lung-graded prognostic assessment and other identified potential confounders (HR, 0.24; 95% CI, 0.10-0.61; P =.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 =.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 =.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-graded prognostic assessment. 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.
| Original language | English |
|---|---|
| Pages (from-to) | 258-267 |
| Number of pages | 10 |
| Journal | International Journal of Radiation Oncology Biology Physics |
| Volume | 108 |
| Issue number | 1 |
| Early online date | 23 Apr 2020 |
| DOIs | |
| Publication status | Published - 1 Sept 2020 |
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