Essential pre-treatment imaging examinations in patients with endoscopically-diagnosed early gastric cancer

<p>Abstract</p> <p>Background</p> <p>There have been no reports discussing which imaging procedures are truly necessary before treatment of endoscopically-diagnosed early gastric cancer (eEGC). The aim of this pilot study was to show which imaging examinations are essential to select indicated treatment or appropriate strategy in patients with eEGC.</p> <p>Methods</p> <p>In 140 consecutive patients (95 men, 45 women; age, 66.4 +/- 11.3 years [mean +/- standard deviation], range, 33-90) with eEGC which were diagnosed during two years, the pre-treatment results of ultrasonography (US) and contrast-enhanced computed tomography (CT) of the abdomen, barium enema (BE) and chest radiography (CR) were retrospectively reviewed. Useful findings that might affect indication or strategy were evaluated.</p> <p>Results</p> <p>US demonstrated useful findings in 13 of 140 patients (9.3%): biliary tract stones (n = 11) and other malignant tumors (n = 2). Only one useful finding was demonstrated on CT (pancreatic intraductal papillary mucinous tumor) but not on US (0.7%; 95% confidential interval [CI], 2.1%). BE demonstrated colorectal carcinomas in six patients and polyps in 10 patients, altering treatment strategy (11.4%; 95%CI, 6.1-16.7%). Of these, only two colorectal carcinomas were detected on CT. CR showed three relevant findings (2.1%): pulmonary carcinoma (n = 1) and cardiomegaly (n = 2). Seventy-nine patients (56%) were treated surgically and 56 patients were treated by endoscopic intervention. The remaining five patients received no treatment due to various reasons.</p> <p>Conclusions</p> <p>US, BE and CR may be essential as pre-treatment imaging examinations because they occasionally detect findings which affect treatment indication and strategy, although abdominal contrast-enhanced CT rarely provide additional information.</p

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe

The CHEMDNER corpus of chemicals and drugs and its annotation principles

The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of different approaches that detect chemicals in documents. We present the CHEMDNER corpus, a collection of 10,000 PubMed abstracts that contain a total of 84,355 chemical entity mentions labeled manually by expert chemistry literature curators, following annotation guidelines specifically defined for this task. The abstracts of the CHEMDNER corpus were selected to be representative for all major chemical disciplines. Each of the chemical entity mentions was manually labeled according to its structure-associated chemical entity mention (SACEM) class: abbreviation, family, formula, identifier, multiple, systematic and trivial. The difficulty and consistency of tagging chemicals in text was measured using an agreement study between annotators, obtaining a percentage agreement of 91. For a subset of the CHEMDNER corpus (the test set of 3,000 abstracts) we provide not only the Gold Standard manual annotations, but also mentions automatically detected by the 26 teams that participated in the BioCreative IV CHEMDNER chemical mention recognition task. In addition, we release the CHEMDNER silver standard corpus of automatically extracted mentions from 17,000 randomly selected PubMed abstracts. A version of the CHEMDNER corpus in the BioC format has been generated as well. We propose a standard for required minimum information about entity annotations for the construction of domain specific corpora on chemical and drug entities. The CHEMDNER corpus and annotation guidelines are available at: http://www.biocreative.org/resources/biocreative-iv/chemdner-corpus