A visualization method measuring the performance of biomarkers for guiding treatment decisions

Biomarkers that predict efficacy and safety for a given drug therapy become increasingly important for treatment strategy and drug evaluation in personalized medicine. Methodology for appropriately identifying and validating such biomarkers is critically needed, although it is very challenging to develop, especially in trials of terminal diseases with survival endpoints. The marker‐by‐treatment predictiveness curve serves this need by visualizing the treatment effect on survival as a function of biomarker for each treatment. In this article, we propose the weighted predictiveness curve (WPC). Based on the nature of the data, it generates predictiveness curves by utilizing either parametric or nonparametric approaches. Especially for nonparametric predictiveness curves, by incorporating local assessment techniques, it requires minimum model assumptions and provides great flexibility to visualize the marker‐by‐treatment relationship. WPC can be used to compare biomarkers and identify the one with the highest potential impact. Equally important, by simultaneously viewing several treatment‐specific predictiveness curves across the biomarker range, WPC can also guide the biomarker‐based treatment regimens. Simulations representing various scenarios are employed to evaluate the performance of WPC. Application on a well‐known liver cirrhosis trial sheds new light on the data and leads to discovery of novel patterns of treatment biomarker interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

Group sequential monitoring based on the weighted log‐rank test statistic with the Fleming–Harrington class of weights in cancer vaccine studies

In recent years, immunological science has evolved, and cancer vaccines are now approved and available for treating existing cancers. Because cancer vaccines require time to elicit an immune response, a delayed treatment effect is expected and is actually observed in drug approval studies. Accordingly, we propose the evaluation of survival endpoints by weighted log‐rank tests with the Fleming–Harrington class of weights. We consider group sequential monitoring, which allows early efficacy stopping, and determine a semiparametric information fraction for the Fleming–Harrington family of weights, which is necessary for the error spending function. Moreover, we give a flexible survival model in cancer vaccine studies that considers not only the delayed treatment effect but also the long‐term survivors. In a Monte Carlo simulation study, we illustrate that when the primary analysis is a weighted log‐rank test emphasizing the late differences, the proposed information fraction can be a useful alternative to the surrogate information fraction, which is proportional to the number of events. Copyright © 2016 John Wiley & Sons, Ltd.     

大型音乐舞蹈史诗《中国革命之歌》的艺术处理

大型音乐舞蹈史诗《中国革命之歌》在进行创作时既要确保艺术创作真实反映历史事实,又要防止与《东方红》重复,需要创作人员精心设计框架,选择材料进行加工改编,具有一定的难度。创作者和表演者通过艺术框架的搭建、艺术素材的加工、艺术演出的处理,使大型音乐舞蹈史诗《中国革命之歌》既具有政治内容又具有极高的艺术美。     

WTO争端解决机制中对发展中国家的特殊和差别待遇探析

在WTO争端解决机制中有一些针对发展中国家的特殊与差别待遇条款,但这些条款有其局限性,发展中国家很少利用,发展中国家应当努力促进特殊和差别待遇条款的完善,同时充分利用好现存的特殊和差别待遇.     

试论治理腐败的逻辑

为了选择有效治理腐败的方法,首先要解决针对有效治理腐败的逻辑思维问题。目前各国普遍使用的“治理腐败逻辑”有三种:一是减少介入腐败的机会;二是提高介入腐败的代价;三是增强腐败免疫力。这三种逻辑及其策略均具有各自的局限性,只有综合运用三种逻辑及其策略,才能有效治理腐败。     

国外教师差别行为的研究现状与展望

近年来国外对教师差别行为的研究取得了较大的成就。文章从差别行为的研究范式、结构与测量及研究内容三个方面对该领域的现状进行描述,并在此基础上对该现象的未来发展趋势进行展望,以期人们能更好地把握该领域的发展轮廓,推动该领域的研究与发展。     

Heterogeneous treatment effects on Children's cognitive/non-cognitive skills: A reevaluation of an influential early childhood intervention

The 1962–67 High/Scope Perry Preschool Program, a well-known experimental early childhood intervention study that provided quality preschool education to disadvantaged children, has been shown to have had positive impacts on early child development and on a variety of adulthood outcomes. However, most previous analyses have only examined average treatment effects across all program participants without exploring possible effect heterogeneity by children's background characteristics. We investigated this question by first using the 1964–65 Current Population Survey data in combination with the Perry data to construct a scale of child socioeconomic status based on the estimated propensity for inclusion in the Perry program, then analyzing effect heterogeneity within the Perry sample by strata of our socioeconomic scale. We found that the treatment effects of enrollment in the Perry preschool on cognitive and non-cognitive skills were much larger and more persistent among the most disadvantaged children than among others in the Perry program. Furthermore, among the most disadvantaged children, the treatment (i.e., preschool enrollment) affects later outcomes through a reinforcement mechanism of skill development (i.e., early cognitive gain leads to a non-cognitive gain, which in turn leads to later cognitive gain) and a sequential improvement of cognitive skills over time. These findings have important implications for the evaluation of policy interventions in early child development using experimental data.     

人工智能背景下医疗法律责任的现实困境与完善路径

医疗人工智能利用深度学习和计算机算法等现代化技术,实现辅助诊疗、医学影像、药物发掘、健康诊疗等功能,是人工智能应用最具前景的领域之一。随着人工智能技术发展,具备自主思维和决策能力的智能机器人医生等人工智能将对现有的医疗法律责任制度带来颠覆性影响。在人工智能背景下,医疗人工智能是否具有独立法律主体地位、传统的医疗过错责任归责能否适用、因果关系如何认定等成为现代民事法律责任制度的严峻挑战,也成为实践中的必答之问。因此,在借鉴欧美人工智能领域的探索经验的基础上,在当前阶段通过修正和完善我国民事法律责任制度,提出针对不同的人工智能侵权情形适用差别化归责原则,并尝试建立人工智能强制保险或储备金制度,设置人工智能监管机构及行业标准,以实现既保障患者合法公平权益,又鼓励人工智能技术有效发展之间的平衡。     

多边贸易体制下中国发展中国家地位问题研究——基于历史、现实与规范的多维考察

当前,发展中国家地位问题受到国际社会的高度关注,已成为世界贸易组织改革中的主要讨论议题。然而,现行世界贸易组织多边规则体系中并没有关于“发展中国家地位”的清晰界定,“自我认定”的方式正遭受一些国家的挑战。发展中国家地位和特殊与差别待遇条款密切相关,世界贸易组织规则体系中涵盖的155项特殊与差别待遇条款为发展中国家的国内政策提供了一定的灵活性,尽管多数为“最佳努力条款”。中国的发展中国家地位兼具身份和契约的双重属性,部分发达国家迫使中国放弃发展中国家地位,本质上旨在继续维持其在国际经济秩序中的主导地位。虽然中国的发展正处于“强起来”的第三阶段,但仍须坚持发展中国家地位不动摇。放弃发展中国家地位并不等于将获得发达国家的自动接纳,相反,还会影响到在其他国际组织和国际事务中的角色扮演,中国的发展离不开广大发展中国家的支持。当然,坚持发展中国家地位并不等于需要和其他发展中成员享受完全一致的差别待遇,在后续谈判中,中国可以保持一定的灵活性。在国际治理中,中国也将继续为国际社会的发展提供解决方案,树立负责任大国形象。     

Double robust estimator in general treatment regimes based on Covariate-balancing

Double robust estimators have double the chance of being a consistent estimator of a causal effect in binary treatments cases. In this paper, we proposed an estimator of a causal effect for general treatment regimes based on covariate-balancing. Under parametrical situation, our estimator has double robustness.