In this prospective phase III trial, afatinib combined with paclitaxel improved progression-free survival and objective response, compared with single-agent chemotherapy, in patients with NSCLC who were clinically enriched for ErbB dependency having failed platinum-based chemotherapy, gefitinib/erlotinib and afatinib monotherapy after initial benefit on each tyrosine kinase inhibitor.

The interpretation of pulmonary function tests (PFTs) to diagnose respiratory diseases is built on expert opinion that relies on the recognition of patterns and the clinical context for detection of specific diseases. In this study, we aimed to explore the accuracy and interrater variability of pulmonologists when interpreting PFTs compared with artificial intelligence (AI)-based software that was developed and validated in more than 1500 historical patient cases.120 pulmonologists from 16 European hospitals evaluated 50 cases with PFT and clinical information, resulting in 6000 independent interpretations. The AI software examined the same data. American Thoracic Society/European Respiratory Society guidelines were used as the gold standard for PFT pattern interpretation. The gold standard for diagnosis was derived from clinical history, PFT and all additional tests.The pattern recognition of PFTs by pulmonologists (senior 73%, junior 27%) matched the guidelines in 74.4±5.9% of the cases (range 56–88%). The interrater variability of κ=0.67 pointed to a common agreement. Pulmonologists made correct diagnoses in 44.6±8.7% of the cases (range 24–62%) with a large interrater variability (κ=0.35). The AI-based software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all cases (p<0.0001 for both measures).The interpretation of PFTs by pulmonologists leads to marked variations and errors. AI-based software provides more accurate interpretations and may serve as a powerful decision support tool to improve clinical practice.

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Lung cancer is the number one cause of cancer‐related death worldwide with cigarette smoking as its major risk factor. Although the incidence of lung cancer in never smokers is rising, this subgroup of patients is underrepresented in genomic studies of lung cancer. Here, we assembled a prospective cohort of 46 never‐smoking, nonsmall cell lung cancer (NSCLC) patients and performed whole‐exome and low‐coverage whole‐genome sequencing on tumors and matched germline DNA. We observed fewer somatic mutations, genomic breakpoints and a smaller fraction of the genome with chromosomal instability in lung tumors from never smokers compared to smokers. The lower number of mutations, enabled us to identify TSC22D1 as a potential driver gene in NSCLC. On the other hand, the frequency of mutations in actionable genes such as EGFR and ERBB2 and of amplifications in MET were higher, while the mutation rate of TP53, which is a negative prognostic factor, was lower in never smokers compared to smokers. Together, these observations suggest a more favorable prognosis for never smokers with NSCLC. Classification of somatic mutations into six‐substitution type patterns or into 96‐substitution type signatures revealed distinct clusters between smokers and never smokers. Particularly, we identified in never smokers signatures related to aging, homologous recombination damage and APOBEC/AID activity as the most important underlying processes of NSCLC. This further indicates that second‐hand smoking is not driving NSCLC pathogenesis in never smokers.

Background: In patients with locally advanced lung cancer treated with concurrent chemoradiation, outcome measurements have been mostly limited to survival. Objectives: We aimed to measure outcomes that matter to these patients beyond survival in a general clinical practice. Methods: In a prospective single-centre study, consecutive patients with locally advanced non-small cell lung cancer reported their own outcomes using the EORTC Quality of Life Questionnaire Core 30 at baseline, during therapy, at therapy stop and till 1 year after therapy end every 3 months. Survival, complications, quality of death and case-mix variables were measured. Results: There were 32 consecutive patients included prospectively from June 2013 until September 2016. Median overall survival was 24.3 months (95% CI 12.7–35.9). Severe toxicity (grade III–IV) was frequent (haematologic toxicity III–IV in 59%). Patient-reported outcomes (PROs) documented the burden on global health status and on functional domains (physical, role, social, emotional and cognitive functioning). Deterioration was pronounced during and after treatment with drops over 20 up to 40% points from baseline for physical, role and social functioning. Clinically meaningful negative effects did persist up to 6 and 9 months for physical and role functioning. Fifty-six percent of the deceased patients died in hospital. Conclusions: The assault on health-related quality of life during concurrent chemoradiation for locally advanced lung cancer is considerable. Loss of physical and role functioning persists up to 6 and 9 months after therapy end, respectively. Measuring PROs can help to identify issues for improvement of the value of care delivered.