Nivolumab was not associated with significantly longer progression-free survival than chemotherapy among patients with previously untreated stage IV or recurrent NSCLC with a PD-L1 expression level of 5% or more. Overall survival was similar between groups. Nivolumab had a favorable safety profile, as compared with chemotherapy, with no new or unexpected safety signals. (Funded by Bristol-Myers Squibb and others; CheckMate 026 ClinicalTrials.gov number, NCT02041533 .).

IMPORTANCECheckpoint inhibitors targeting programmed cell death 1 or its ligand (PD-L1) as monotherapies or in combination with anti-cytotoxic T-lymphocyte-associated antigen 4 have shown clinical activity in patients with metastatic non-small cell lung cancer.OBJECTIVE To compare durvalumab, with or without tremelimumab, with chemotherapy as a first-line treatment for patients with metastatic non-small cell lung cancer. DESIGN, SETTING, AND PARTICIPANTSThis open-label, phase 3 randomized clinical trial (MYSTIC) was conducted at 203 cancer treatment centers in 17 countries. Patients with treatment-naive, metastatic non-small cell lung cancer who had no sensitizing EGFR or ALK genetic alterations were randomized to receive treatment with durvalumab, durvalumab plus tremelimumab, or chemotherapy. Data were collected from July 21, 2015, to October 30, 2018.INTERVENTIONS Patients were randomized (1:1:1) to receive treatment with durvalumab (20 mg/kg every 4 weeks), durvalumab (20 mg/kg every 4 weeks) plus tremelimumab (1 mg/kg every 4 weeks, up to 4 doses), or platinum-based doublet chemotherapy. MAIN OUTCOMES AND MEASURESThe primary end points, assessed in patients with Ն25% of tumor cells expressing PD-L1, were overall survival (OS) for durvalumab vs chemotherapy, and OS and progression-free survival (PFS) for durvalumab plus tremelimumab vs chemotherapy. Analysis of blood tumor mutational burden (bTMB) was exploratory.

BackgroundMalignant pleural effusion (MPE) causes debilitating breathlessness and predicting survival is challenging. This study aimed to obtain contemporary data on survival by underlying tumour type in patients with MPE, identify prognostic indicators of overall survival and develop and validate a prognostic scoring system.MethodsThree large international cohorts of patients with MPE were used to calculate survival by cell type (univariable Cox model). The prognostic value of 14 predefined variables was evaluated in the most complete data set (multivariable Cox model). A clinical prognostic scoring system was then developed and validated.ResultsBased on the results of the international data and the multivariable survival analysis, the LENT prognostic score (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group (ECOG) performance score (PS), neutrophil-to-lymphocyte ratio and tumour type) was developed and subsequently validated using an independent data set. Risk stratifying patients into low-risk, moderate-risk and high-risk groups gave median (IQR) survivals of 319 days (228–549; n=43), 130 days (47–467; n=129) and 44 days (22–77; n=31), respectively. Only 65% (20/31) of patients with a high-risk LENT score survived 1 month from diagnosis and just 3% (1/31) survived 6 months. Analysis of the area under the receiver operating curve revealed the LENT score to be superior at predicting survival compared with ECOG PS at 1 month (0.77 vs 0.66, p<0.01), 3 months (0.84 vs 0.75, p<0.01) and 6 months (0.85 vs 0.76, p<0.01).ConclusionsThe LENT scoring system is the first validated prognostic score in MPE, which predicts survival with significantly better accuracy than ECOG PS alone. This may aid clinical decision making in this diverse patient population.

Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.