6种止吐用药方案预防高致吐风险化疗引起恶心呕吐临床效果的网状meta分析

目的：采用网状Meta 分析评价6种止吐用药方案预防高致吐风险化疗所引起恶心呕吐(CINV)的疗效。方法：计算机检索中国知网、万方数据、维普医药、PubMed、Embase和Cochrane Library(2019年第8期)，检索时限至2019年9月1日，收集5-羟色胺3受体抑制剂（包括第一代5-HT3和第二代5-HT3帕洛诺司琼(PAL)）+地塞米松(DEX)、神经激肽1受体抑制剂(NK-1RA)+5-HT3+DEX、奥氮平(OLZ)+5-HT3+DEX、（奈妥吡坦300mg+帕洛诺司琼0.50mg）NEPA+DEX预防高致吐风险CINV的随机对照试验(RCT)，由两名评价员独立筛选文献、提取数据，并按照Cochrane偏倚风险评估工具评价文献质量，采用Stata 15.0统计软件进行网状Meta分析。结果：共纳入18项RCT，合计8076例患者。网状Meta分析结果显示：与5-HT3+DEX比较，NEPA+DEX、NK-1RA+5-HT3+DEX、NK-1RA+PAL+DEX和OLZ+PAL+DEX预防高致吐风险CINV的急性CINV完全缓解率高于5-HT3+DEX组，差异有显著差异，概率排序为OLZ+PAL+DEX＞NK-1RA+PAL+DEX＞NK-1RA+5-HT3+DEX＞NEPA+DEX＞PAL+DEX = 5-HT3+DEX。与5-HT3+DEX比较，NEPA+DEX、NK-1RA+5-HT3+DEX、NK-1RA+PAL+DEX、OLZ+PAL+DEX和PAL+DEX预防高致吐风险CINV的迟发性CINV完全缓解率高于5-HT3+DEX组，差异有显著差异，概率排序为NK-1RA+PAL+DEX＞OLZ+PAL+DEX＞NEPA+DEX＞NK-1RA+5-HT3+DEX = PAL+DEX = 5-HT3+DEX。与5-HT3+DEX比较，NEPA+DEX、NK-1RA+5-HT3+DEX和NK-1RA+PAL+DEX预防高致吐风险CINV的持续期CINV缓解率高于5-HT3+DEX组，差异有显著差异，概率排序为NK-1RA+PAL+DEX＞OLZ+PAL+DEX＞NEPA+DEX＞NK-1RA+5-HT3+DEX)＞PAL+DEX＞5-HT3+DEX。结论：通过网状Meta分析发现，OLZ+PAL+DEX是预防高致吐风险急性CINV最有效方案，而NK-1RA+PAL+DEX是预防迟发性和持续期CINV最有效方案。     

Interrogating the microenvironmental landscape of tumors with computational image analysis approaches

The tumor microenvironment is an interacting heterogeneous collection of cancer cells, resident as well as infiltrating host cells, secreted factors, and extracellular matrix proteins. With the growing importance of immunotherapies, it has become crucial to be able to characterize the composition and the functional orientation of the microenvironment. The development of novel computational image analysis methodologies may enable the robust quantification and localization of immune and related biomarker-expressing cells within the microenvironment. The aim of the review is to concisely highlight a selection of current and significant contributions pertinent to methodological advances coupled with biomedical or translational applications. A further aim is to concisely present computational advances that, to our knowledge, have currently very limited use for the assessment of the microenvironment but have the potential to enhance image analysis pipelines; on this basis, an example is shown for the detection and segmentation of cells of the microenvironment using a published pipeline and a public dataset. Finally, a general proposal is presented on the conceptual design of automation-optimized computational image analysis workflows in the biomedical and clinical domain.     

探析药品注册管理课堂教学内容与方法有机融合

目的：以人民卫生出版社出版的《药事管理学》6版教材为蓝本，以本科阶段教学效果提高为指标，探讨改进课堂教学的方法。方法：以"药品注册管理"一章教学内容为例，筛选、调整和优化教学方法。结果：教学过程中，按照教学内容特点选择适宜教学方法，确定"教学方法与内容相融合"的课堂教学模式，在完成教学大纲基础上，适当增加执业药师及药学时事相关内容。结论：根据现代学生获取知识途径，充分利用高新技术背景下"智慧教室"资源，采取传统与现代教学方法相结合的教学模式，使课堂理论教学相关内容在以教材内容为主的前提下与国家当前药事时事相关联，可以增加学生课堂学习兴趣、培养自主学习习惯，从而提高教师教学能力和教学质量，实现培养具备专业知识、技能和法律、道德素养的药学应用型综合人才的预期目标。     

院方归龙汤加味治疗消渴脱疽探讨

[目的]探讨院方归龙汤加味治疗消渴脱疽的作用及其相关机制。[方法] 查阅分析古今相关文献，并结合临床实践，基于陈实功的《外科正宗》一书中治疗阴疽的四法“疏稼土、通地脉、助根本、回阳气”，对消渴脱疽的病因病机及院方归龙汤加味治疗消渴脱疽进行分析，并列举验案一则加以佐证。[结果] 根据文献研究及实践经验，笔者认为消渴脱疽的病机为阳气亏虚、气血失养、经脉闭阻，故临床上遵从陈实功的阴疽治疗四法“疏稼土、通地脉、助根本、回阳气”，在归龙汤基础上进行加减:加白术、陈皮健脾益气、燥湿利水，此为疏稼土；加黄芪补气升阳、通脉行滞、敛疮生肌，此为助根本；加附子助阳行气，此为回阳气。所举验案，诊断为消渴脱疽，证属阳虚血瘀，符合归龙汤加味方之病机，治之而获良效。[结论]归龙汤加味充分体现了《外科正宗》中脱疽治疗四法，治疗消渴脱疽临床疗效良好，值得临床推广应用。     

情景式营养教育对婴儿喂养状况的影响

目的探讨情景式营养教育，对婴儿监护人的营养知识水平和婴儿喂养状况的影响，以探索婴儿食物转换指导新模式。 方法选择2014年4月至12月，于江苏省淮安市妇幼保健院儿童保健门诊进行健康体检的272例1～2个月龄婴儿为研究对象。采用随机数字表法，将其分别纳入干预组(n＝140)和对照组(n＝132)。干预组婴儿于3～4个月龄时，由儿童营养专科医师和营养师，在营养厨房内，对婴儿监护人以10～15人小组形式，进行情景式营养教育；对照组则由门诊体检医师进行常规营养指导。2组婴儿12个月龄时，对其监护人采用本研究自行设计的《淮安市妇幼保健院婴儿喂养状况调查表》进行调查。采用χ²检验，对2组婴儿喂养状况，如母乳喂养率、食物转换合理率等，进行统计学比较。本研究遵循的程序符合2013年修订的《世界医学协会赫尔辛基宣言》要求，并与受试儿监护人签署临床研究知情同意书。 结果①2组婴儿4个月龄时纯母乳喂养率、混合喂养率及人工喂养率比较，差异均无统计学意义(P>0.05)。干预组婴儿6、12个月龄时，继续母乳喂养率分别为88.6%、37.1%，均显著高于对照组的78.0%、23.5%，并且差异均有统计学意义(χ²＝5.468、P＝0.022，χ²＝5.977、P＝0.018)。②干预组婴儿监护人对食物转换指导模式的满意度、食物转换合理率，以及3类补充食品(谷类、果蔬类、动物性食物)均合理添加率，添加动物性食物合理率及监护人专用料理机使用率分别为90.0%、87.1%、77.1%、82.9%、50.0%，均显著高于对照组的77.3%、60.6%、54.5%、65.2%、25.8%，并且差异均有统计学意义(χ²＝8.116、P＝0.005，χ²＝25.033、P<0.001，χ²＝15.500、P<0.001，χ²＝11.114、P＝0.001，χ²＝16.908、P<0.001)。 结论情景式营养教育的婴儿食物转换指导新模式，可提高婴儿监护人的营养知识水平，改善婴儿喂养状况。     

Innovative Thinking on Endpoint Selection in Clinical Trials

ABSTRACT

In clinical trials, selection of appropriate study endpoints is critical for an accurate and reliable evaluation of safety and effectiveness of a test treatment under investigation. In practice, however, there are usually multiple endpoints available for measurement of disease status and/or therapeutic effect of the test treatment under study. For example, in cancer clinical trials, overall survival, response rate, and/or time to disease progression are usually considered as primary clinical endpoints for evaluation of safety and effectiveness of the test treatment under investigation. Once the study endpoints have been selected, sample size required for achieving a desired power is then determined. It, however, should be noted that different study endpoints may result in different sample sizes. In practice, it is usually not clear which study endpoint can best inform the disease status and measure the treatment effect. Moreover, different study endpoints may not translate one another although they may be highly correlated one another. In this article, we intend to develop an innovative endpoint namely therapeutic index based on a utility function to combine and utilize information collected from all study endpoints. Statistical properties and performances of the proposed therapeutic index are evaluated theoretically. A numerical example concerning a cancer clinical trial is given to illustrate the use of the proposed therapeutic index.     

Bayesian adaptive lasso for additive hazard regression with current status data

Variable selection is a crucial issue in model building and it has received considerable attention in the literature of survival analysis. However, available approaches in this direction have mainly focused on time-to-event data with right censoring. Moreover, a majority of existing variable selection procedures for survival models are developed in a frequentist framework. In this article, we consider additive hazards model in the presence of current status data. We propose a Bayesian adaptive least absolute shrinkage and selection operator procedure to conduct a simultaneous variable selection and parameter estimation. Efficient Markov chain Monte Carlo methods are developed to implement posterior sampling and inference. The empirical performance of the proposed method is demonstrated by simulation studies. An application to a study on the risk factors of heart failure disease for type 2 diabetes patients is presented.     

医学信息管理专业网络技术模拟仿真实验教学

针对网络技术实验,采用模拟仿真的实验环境,将抽象的教学内容变成直观教学,利用基于问题的教学法培养学生科学思维,以任务驱动法激发学习积极性,实现理论与实验交叉教学