Purpose: Treatment with programmed cell death-1 or programmed death ligand 1 (PD-(L)1) inhibitors is now standard therapy for patients with lung cancer. The immunosuppressive effect of corticosteroids may reduce efficacy of PD-(L)1 blockade. On-treatment corticosteroids for treatment of immune-related adverse events do not seem to affect efficacy, but the potential impact of baseline corticosteroids at the time of treatment initiation is unknown. Clinical trials typically excluded patients who received baseline corticosteroids, which led us to use real-world data to examine the effect of corticosteroids at treatment initiation. Methods: We identified patients who were PD-(L)1–naïve with advanced non–small-cell lung cancer from two institutions—Memorial Sloan Kettering Cancer Center and Gustave Roussy Cancer Center—who were treated with single-agent PD-(L)1 blockade. Clinical and pharmacy records were reviewed to identify corticosteroid use at the time of beginning anti–PD-(L)1 therapy. We performed multivariable analyses using Cox proportional hazards regression model and logistic regression. Results: Ninety (14%) of 640 patients treated with single-agent PD-(L)1 blockade received corticosteroids of ≥ 10 mg of prednisone equivalent daily at the start of the PD-(L)1 blockade. Common indications for corticosteroids were dyspnea (33%), fatigue (21%), and brain metastases (19%). In both independent cohorts, Memorial Sloan Kettering Cancer Center (n = 455) and Gustave Roussy Cancer Center (n = 185), baseline corticosteroids were associated with decreased overall response rate, progression-free survival, and overall survival with PD-(L)1 blockade. In a multivariable analysis of the pooled population, adjusting for smoking history, performance status, and history of brain metastases, baseline corticosteroids remained significantly associated with decreased progression-free survival (hazard ratio, 1.3; P = .03), and overall survival (hazard ratio, 1.7; P < .001). Conclusion: Baseline corticosteroid use of ≥ 10 mg of prednisone equivalent was associated with poorer outcome in patients with non–small-cell lung cancer who were treated with PD-(L)1 blockade. Prudent use of corticosteroids at the time of initiating PD-(L)1 blockade is recommended.

Purpose: CD28, CD57, and KLRG1 have been previously identified as markers of T-cell immunosenescence. The impact of immunosenescence on anti-PD(L)-1 (ICI) or platinum-based chemotherapy (PCT) in patients with advanced non–small cell lung cancer (aNSCLC) is unknown. Experimental Design: The percentage of CD28−, CD57+, KLRG1+ among CD8+ T cells [senescent immune phenotype (SIP)] was assessed by flow cytometry on blood from patients with aNSCLC before single-agent ICI (discovery cohort). A SIP cut-off was identified by log-rank maximization method and patients with aNSCLC treated with ICI (validation cohort) or PCT were classified accordingly. Proliferation and functional properties of SIP+ CD8+ T cells were assessed in vitro. Results: In the ICI discovery cohort (N = 37), SIP cut-off was 39.5%, 27% of patients were SIP+. In the ICI validation cohort (N = 46), SIP+ status was found in 28% of patients and significantly correlated with worse objective response rate (ORR; 0% vs. 30%, P = 0.04), median progression-free survival (PFS) [1.8 (95% confidence interval (CI), 1.3-NR) vs. 6.4 (95% CI, 2–19) months, P = 0.009] and median overall survival, OS [2.8 (95% CI, 2.0-NR) vs. 20.8 (95% CI, 6.0-NR) months, P = 0.02]. SIP+ status was significantly associated with circulating specific immunephenotypes, in vitro lower CD8+ T cells proliferation, lower IL2 and higher TNFα and IFNγ production. In the ICI-pooled population (N = 83), SIP+ status did not correlate with any clinical characteristics and it was associated with significantly worse ORR, PFS, and OS. In PCT cohort (N = 61), 11% of patients were SIP+. SIP status did not correlate with outcomes upon PCT. Conclusions: Circulating T-cell immunosenescence is observed in up to 28% of patients with aNSCLC and correlates with lack of benefit from ICI but not from PCT. See related commentary by Salas-Benito et al., p. 374

Detection and segmentation of abnormalities on medical images is highly important for patient management including diagnosis, radiotherapy, response evaluation, as well as for quantitative image research. We present a fully automated pipeline for the detection and volumetric segmentation of non-small cell lung cancer (NSCLC) developed and validated on 1328 thoracic CT scans from 8 institutions. Along with quantitative performance detailed by image slice thickness, tumor size, image interpretation difficulty, and tumor location, we report an in-silico prospective clinical trial, where we show that the proposed method is faster and more reproducible compared to the experts. Moreover, we demonstrate that on average, radiologists & radiation oncologists preferred automatic segmentations in 56% of the cases. Additionally, we evaluate the prognostic power of the automatic contours by applying RECIST criteria and measuring the tumor volumes. Segmentations by our method stratified patients into low and high survival groups with higher significance compared to those methods based on manual contours.