Multiscale quantification of morphological heterogeneity with creation of a predictor of longer survival in glioblastoma

Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.     

The role of endoscopic ultrasound for portal hypertension in liver cirrhosis

Journal of Medical Ultrasonics - Chronic liver disease is still a major problem because disease progression will ultimately lead to liver cirrhosis. Portal hypertension is the hallmark in advanced...     

伏立康唑一级预防急性白血病患者化疗期间并发真菌感染的临床疗效北大核心

目的:探讨初诊急性白血病患者化疗期间应用伏立康唑进行预防侵袭性真菌病(IFD)的临床疗效及安全性。方法:回顾性分析2016年02月至2018年03月期间我院血液科收治的初诊急性白血病行化疗的患者166例,按照是否使用抗真菌药进行预防性治疗分为观察组(应用伏立康唑进行预防治疗,n=103)和对照组(未应用抗真菌药物,n=63),比较两组患者IFD发生率差异,并分析抗真菌药物应用的不良反应。结果:观察组IFD发生率为10.7%,对照组为33.3%,两组患者的IFD发生率有明显差异(P<0.05);所有应用伏立康唑进行预防治疗的患者均未出现严重的不良反应。结论:伏立康唑可以有效减低急性白血病患者化疗期间IFD发生率,并且有着较好的安全性,值得在临床推广应用。     

A systematic review of the methodological quality of economic evaluations in genetic screening and testing for monogenic disorders

PurposeUnderstanding the value of genetic screening and testing for monogenic disorders requires high-quality, methodologically robust economic evaluations. This systematic review sought to assess the methodological quality among such studies and examined opportunities for improvement.MethodsWe searched PubMed, Cochrane, Embase, and Web of Science for economic evaluations of genetic screening/testing (2013-2019). Methodological rigor and adherence to best practices were systematically assessed using the British Medical Journal checklist.ResultsAcross the 47 identified studies, there were substantial variations in modeling approaches, reporting detail, and sophistication. Models ranged from simple decision trees to individual-level microsimulations that compared between 2 and >20 alternative interventions. Many studies failed to report sufficient detail to enable replication or did not justify modeling assumptions, especially for costing methods and utility values. Meta-analyses, systematic reviews, or calibration were rarely used to derive parameter estimates. Nearly all studies conducted some sensitivity analysis, and more sophisticated studies implemented probabilistic sensitivity/uncertainty analysis, threshold analysis, and value of information analysis.ConclusionWe describe a heterogeneous body of work and present recommendations and exemplar studies across the methodological domains of (1) perspective, scope, and parameter selection; (2) use of uncertainty/sensitivity analyses; and (3) reporting transparency for improvement in the economic evaluation of genetic screening/testing.