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Due to increasing medical costs and yet limited financial resources, medical treatment and economic analyses can no longer be separated; therefore, direct costing and cost unit accounting become more and more relevant as controlling tools in hospital management. Transthoracic esophagectomy is an integral part of the current treatment concept in patients with esophageal carcinoma. The question of the present study was whether the present diagnosis-related groups (DRG) system is a cost-effective tool to represent transthoracic esophagectomy. In this retrospective study at a high-volume center, 161 consecutive patients with esophageal carcinoma were included. All patients were surgically treated according to the current S3 guidelines by a transthoracic esophagectomy. Detailed and standardized documentation of the postoperative complications was made according to the classification of Clavien-Dindo and the guidelines of the Esophagectomy Complications Consensus Group (ECCG). For each individual patient, the respective actual costs were analyzed according to the Institute for the Remuneration System in Hospitals (InEK) cost accounting approach comparing DRG payments (DRG G03A) on a case level including all extra fees per DRG catalogue. The mean costs per case of all included 161 patients were 24,338. (median: 19,210., range: 12,149-127,376.), while mean payments per case of 22,591. were recorded. For the entire study population, the profit margin was -281,330. (mean: -1747.). Only patients with an uncomplicated course (Clavien-Dindo 0) yielded a slightly positive profit margin of 2514.. With increasing complication score the profit margin became increasingly negative (Clavien-Dindo I: -2878., Clavien-Dindo IVb: -58,543.). Within the analysis of the InEK target cost matrix, main cost drivers can be identified as medical services (22.3%) and non-medical infrastructure (18.7%). Surgical treatment according to the existing guidelines of patients with esophageal carcinoma is

Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic (n = 60) and transcriptomic (n = 69) analysis of 75 LCNECs and identify two molecular subgroups: "type I LCNECs" with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and "type II LCNECs" enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh, and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.

Electroencephalography (EEG) is a popular method to monitor brain activity, but it can be difficult to evaluate EEG-based analysis methods because no ground-truth brain activity is available for comparison. Therefore, in order to test and evaluate such methods, researchers often use simulated EEG data instead of actual EEG recordings, ensuring that it is known beforehand which e ects are present in the data. As such, simulated data can be used, among other things, to assess or compare signal processing and machine learn-ing algorithms, to model EEG variabilities, and to design source reconstruction methods. In this paper, we present SEREEGA, short for Simulating Event-Related EEG Activity . SEREEGA is a MATLAB-based open-source toolbox dedicated to the generation of sim-ulated epochs of EEG data. It is modular and extensible, at initial release supporting ve different publicly available head models and capable of simulating multiple different types of signals mimicking brain activity. This paper presents the architecture and general work ow of this toolbox, as well as a simulated data set demonstrating some of its functions. Highlights Simulated EEG data has a known ground truth, which can be used to validate methods. We present a general-purpose open-source toolbox to simulate EEG data. It provides a single framework to simulate many different types of EEG recordings. It is modular, extensible, and already includes a number of head models and signals. It supports noise, oscillations, event-related potentials, connectivity, and more.

A newly developed high-pressure rheometer for in situ X-ray scattering experiments is described. A commercial rheometer was modified in such a way that X-ray scattering experiments can be performed under different pressures and shear. First experiments were carried out on hyaluronan, a ubiquitous biopolymer that is important for different functions in the body such as articular joint lubrication. The data hint at a decreased electrostatic interaction at higher pressure, presumably due to the increase of the dielectric constant of water by 3% and the decrease of the free volume at 300bar., QC 20170602

Objectives: The recent success of individualized lung cancer therapy has triggered fundamental changes in clinical research strategies. To date there is a strong focus on early proof of concept trials in genetically preselected small patient subgroups. This analysis focuses on the economic burden caused by such trials for advanced lung cancer patients in a German Comprehensive Cancer Center (CCC). Methods: The profit margins between recruiting groups with <= 3 and >3 patients were compared. Clinical and economic data from clinical trials for advanced lung cancer (LC), pharma-sponsored trials (PhST) as well as investigator initiated trials (IIT), conducted between 2011 and 2015 at the Center for Integrated Oncology (CIO) Cologne, were analyzed using a profit-center calculation model. Results: 161 patients were enrolled in 27 clinical trials. The key economic parameter determining costs and payments was the 'trial visits'. In comparison of the two groups (A <= 3; B>3 patients enrolled) we found negative profit margins for the low recruiting group (sic -1444). Concerning the number of visits significant differences were found between PhST and IIT (p= 0.009). Additionally, sub-analysis show structural differences in cost composition by conducting PhST and IIT. Conclusion: Trials with low patient numbers and IIT, do not cover the cost. To ensure adequate, cost covering compensation by pharmaceutical companies CCCs have to thoroughly calculate the cost of early proof of concept trials. The findings of this study also underline the need for novel structures in public funding for investigator-initiated clinical trials in precision medicine. (C) 2017 Elsevier B.V. All rights reserved.