AbstractBackgroundThis study evaluated the efficacy and safety of the combination chemotherapy of docetaxel plus S‐1 in patients with previously treated non‐small cell lung cancer (NSCLC) compared to docetaxel alone.MethodsPatients with previously treated NSCLC were randomly assigned to docetaxel alone (arm A) or a combination of docetaxel and S‐1 (arm B) for a maximum of four cycles. The primary endpoint was overall survival (OS).ResultsThe study was terminated early because of poor accrual. The number of patients evaluated were 74 and 77 in arm A and arm B, respectively. The median OS was 9.8 months (95% confidence interval [CI]: 6.8–15.2) and 12.3 months (95% CI: 9.2–14.5) in arms A and B, respectively. In arms A and B, the median progression‐free survival was 3.5 months (95% CI: 2.7–4.0) and 4.1 months (95% CI: 3.2–4.7), respectively. No statistically significant difference was observed in OS (hazard ratio [HR]: 0.984, 95% CI: 0.682–1.419, p = 0.4569) or progression‐free survival (HR: 0.823, 95% CI: 0.528–1.282, p = 0.0953). The major toxicity was myelosuppression. The incidence of grade 3 or more neutropenia was higher in arm A than in arm B (44.6% vs. 35.1%). However, the incidence of grade 3 or more febrile neutropenia and infection with neutropenia (12.2% vs. 22.1%) was more frequently observed in arm B.ConclusionsThe prematurely terminated study did not show the benefit of two cytotoxic agents over single‐agent therapy for previously treated NSCLC patients.

BackgroundImmune checkpoint inhibitor (ICI) therapy has substantially improved the overall survival (OS) in patients with non-small-cell lung cancer (NSCLC); however, its response rate is still modest. In this study, we developed a machine learning-based platform, namely the Cytokine-based ICI Response Index (CIRI), to predict the ICI response of patients with NSCLC based on the peripheral blood cytokine profiles. MethodsWe enrolled 123 and 99 patients with NSCLC who received anti-PD-1/PD-L1 monotherapy or combined chemotherapy in the training and validation cohorts, respectively. The plasma concentrations of 93 cytokines were examined in the peripheral blood obtained from patients at baseline (pre) and 6 weeks after treatment (early during treatment: edt). Ensemble learning random survival forest classifiers were developed to select feature cytokines and predict the OS of patients undergoing ICI therapy. ResultsFourteen and 19 cytokines at baseline and on treatment, respectively, were selected to generate CIRI models (namely preCIRI14 and edtCIRI19), both of which successfully identified patients with worse OS in two completely independent cohorts. At the population level, the prediction accuracies of preCIRI14 and edtCIRI19, as indicated by the concordance indices (C-indices), were 0.700 and 0.751 in the validation cohort, respectively. At the individual level, patients with higher CIRI scores demonstrated worse OS [hazard ratio (HR): 0.274 and 0.163, and p<0.0001 and p=0.0044 in preCIRI14 and edtCIRI19, respectively]. By including other circulating and clinical features, improved prediction efficacy was observed in advanced models (preCIRI21 and edtCIRI27). The C-indices in the validation cohort were 0.764 and 0.757, respectively, whereas the HRs of preCIRI21 and edtCIRI27 were 0.141 (p<0.0001) and 0.158 (p=0.038), respectively. ConclusionsThe CIRI model is highly accurate and reproducible in determining the patients with NSCLC who would benefit from anti-PD-1/PD-L1 therapy with prolonged OS and may aid in clinical decision-making before and/or at the early stage of treatment.

Background Anti-programmed death-1 (PD-1) immunotherapy can cause immune-related pneumonitis, also known as checkpoint inhibitor pneumonitis (CIP). CIP that develops early after the initiation of anti-PD-1 immunotherapy is important because it is more severe than CIP that develops later. However, only a few studies have examined the risk factors for early-onset CIP. Previous studies have reported several risk factors for CIP, including imaging findings of airway obstruction adjacent to lung tumors. However, the utility of this factor is debatable. Therefore, we investigated potential risk factors for early-onset CIP, including tumor invasion in the central airway (TICA), in patients with non-small cell lung cancer (NSCLC) receiving anti-PD-1 therapy. Methods We retrospectively analyzed the medical records and chest computed tomography scans of patients with NSCLC treated with anti-PD-1 antibodies at the Kanagawa Cancer Center in Japan between 1 January 2016, and 30 June 2018. The clinical characteristics and imaging findings, including TICA, were compared between patients with and without early-onset CIP. Results Data from 181 eligible patients (114 receiving nivolumab and 67 receiving pembrolizumab) were analyzed. Early-onset CIP occurred in 13 of 79 patients (16.5%) with TICA and 2 of 102 patients (2.0%) without TICA. In multivariate analysis, the odds ratio of early-onset CIP for patients with TICA was 8.2 (95% confidence interval [CI]: 1.98-34.0,P= 0.0037). Conclusions TICA was strongly associated with early-onset CIP in patients with NSCLC. Clinicians should carefully observe patients with TICA, especially within three months of anti-PD-1 antibody administration because of high CIP risk. Key pointsSignificant study findings Tumor invasion in the central airway (TICA) was a predictor of early-onset checkpoint inhibitor pneumonitis (CIP) TICA had good interobserver variability, indicating its utility in clinical practice Patients with TICA might have a higher immune status than patients without What this study adds This is the first study focusing on risk factors for CIP limited to early-onset CIP.