Prevalence and characteristics of nutritional depletion were established by body composition measurements in 255 COPD patients in stable clinical condition admitted to a pulmonary rehabilitation center. Depletion of body weight, fat-free mass (using bioelectrical resistance measurements), and muscle mass [from creatinine height index (CHI) and midarm muscle circumference] was most pronounced (40 to 50%) in patients suffering from chronic hypoxemia and in normoxemic patients with severe airflow obstruction (FEV1 < 35%) but also occurred in +/- 25% of patients with moderate airflow obstruction. Classification of the patients in four groups by body weight and fat-free mass revealed that depletion of fat-free mass may occur in normal-weight COPD patients (Group 3). These patients also exhibit a decreased CHI (61 +/- 21%, mean +/- SD) and suffer from physical impairment (12-min walking distance, WD, 532 +/- 152 m) to an even greater degree than underweight patients with relative preservation of fat-free mass (Group 2) (CHI = 73 +/- 16%; WD = 744 +/- 233 m). No systematic differences were established between the four groups in serum protein concentrations or medication use. We conclude that fat-free mass is a better indicator of body mass depletion than body weight. Classification of COPD patients by body weight and fat-free mass may have consequences for planning and interpretation of intervention strategies, particularly in Group 2 and 3 patients.

The worldwide incidence of pulmonary carcinoids is increasing, but little is known about their molecular characteristics. Through machine learning and multi-omics factor analysis, we compare and contrast the genomic profiles of 116 pulmonary carcinoids (including 35 atypical), 75 large-cell neuroendocrine carcinomas (LCNEC), and 66 small-cell lung cancers. Here we report that the integrative analyses on 257 lung neuroendocrine neoplasms stratify atypical carcinoids into two prognostic groups with a 10-year overall survival of 88% and 27%, respectively. We identify therapeutically relevant molecular groups of pulmonary carcinoids, suggesting DLL3 and the immune system as candidate therapeutic targets; we confirm the value of OTP expression levels for the prognosis and diagnosis of these diseases, and we unveil the group of supra-carcinoids. This group comprises samples with carcinoid-like morphology yet the molecular and clinical features of the deadly LCNEC, further supporting the previously proposed molecular link between the low- and high-grade lung neuroendocrine neoplasms.

Disclosure: Dr. Hendriks reports research funding from Roche and Boehringer Ingelheim (both to her institution), fees for participation in advisory boards of Boehringer Ingelheim (to her institution) and BMS (to her institution and to her personally), travel/conference reimbursement from Roche and BMS (to her personally), participation in a mentorship program with key opinion leaders that was funded by AstraZeneca, and fees for educational webinars from Quadia outside of the submitted work. Dr. Audigier-Valette reports fees for being the principal investigator of industry trials for AstraZeneca, Boehringer Ingelheim, BMS, Novartis, and Roche; fees for service on advisory boards of AstraZeneca,

Background Decision Support Systems, based on statistical prediction models, have the potential to change the way medicine is being practiced, but their application is currently hampered by the astonishing lack of impact studies. Showing the theoretical benefit of using these models could stimulate conductance of such studies. In addition, it would pave the way for developing more advanced models, based on genomics, proteomics and imaging information, to further improve the performance of the models. Purpose In this prospective single-center study, previously developed and validated statistical models were used to predict the two-year survival (2yrS), dyspnea (DPN), and dysphagia (DPH) outcomes for lung cancer patients treated with chemo radiation. These predictions were compared to probabilities provided by doctors and guideline-based recommendations currently used. We hypothesized that model predictions would significantly outperform predictions from doctors. Materials and Methods Experienced radiation oncologists (ROs) predicted all outcomes at two timepoints: 1) after the first consultation of the patient, and 2) after the radiation treatment plan was made. Differences in the performances of doctors and models were assessed using Area under the Curve (AUC) analysis. Results A total number of 155 patients were included. At timepoint #1 the differences in AUCs between the ROs and the models were 0.15, 0.17, and 0.20 (for 2yrS, DPN, and DPH respectively), with p-values of 0.02, 0.07, and 0.03. Comparable differences at timepoint #2 were not statistically significant due to the limited number of patients. Comparison to guideline-based recommendations also favored the models. Conclusions The models substantially outperformed ROs’ predictions and guideline-based recommendations currently used in clinical practice. Identification of risk groups on the basis of the models facilitates individualized treatment, and should be further investigated in clinical impact studies.

NSCLC molecular status was associated with metastatic pattern at diagnosis. 54% of stage IV EGFR+ ns-NSCLC patients had bone metastases at diagnosis. These observational results are hypothesis generating, and call for a prospective study where EGFR+ patients are screened for bone metastases, and treated to prevent skeletal related events.