Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

Comparing policy advisory systems beyond the OECD: models,dynamics and the second-generation research agenda

ABSTRACT

The concept of “policy advisory systems” was introduced by Halligan in 1995 as a way to characterize and analyze the multiple sources of policy advice utilized by governments in policy-making processes. The concept has proved useful and has influenced thinking about both the nature of policy work in different advisory venues as well as how these systems change over time. However, to date this work has examined mainly cases of developed countries and its application to developing and transitional countries is less certain. This paper sets out existing models of policy advisory systems based on Halligan’s original thinking on the subject and assesses the findings of many existing studies into OECD countries that advisory systems have been changing as a result of the dual effects of increased use of external consultants and others sources of advice – “externalization” – and the increased use of partisan advice inside government itself – “politicization”. Determining whether or not such changes have also characterized the situations found in developing and transitional countries and at the international-domestic and state-sub-state levels is the subject of the papers in this Special Issue.     

Security branding and digital narrations. Security issues representation on Twitter

In the contemporary multicentric world, sovereign states have to manage carefully the construction of their image, defining their role and aspirations. With the re-definition of the state centric politics, stories become relevant: communication is a form of power, and networked forms of communication are becoming progressively a way to conquer the transnational public spheres. Through strategic narratives of foreign politics, states try to set up the ‘tales’ of international affairs and foreign strategies, to suggest a world vision, a causal interpretation, determining frames that affect transnational actors’ position in the international environment. Sovereign states develop these kind of frame using tools and theories referred to the commercial branding tradition to promote and support their own policies and identity. We decided to investigate how that process is made through information diffusion on digital platforms.

In this work, it has been analyzed the content presented through Twitter posts by the Foreign Ministries accounts of four different States dissimilar for geopolitical positioning and security concerns (USA; Israel; France; Sweden), for a period of three months (9/1/2015-11/30/2015); leading to the identification of different models and characteristic patterns of self-representation.

The thematic content analysis, based on the identification of macrocategories and micro-issues, has led to the identification of different models and characteristic patterns of self-representation, determined by domestic vicissitudes, and has shown some regularities, caused by the branding vocation of autobiographical online contents.     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

三种运营模式下O2O外卖服务供应链质量努力策略研究

O2O外卖作为"互联网+"时代下的新型餐饮模式，日益受到人们的关注。本文研究的O2O外卖服务供应链由一个O2O外卖平台、一个餐饮商家和一个配送骑手构成。O2O外卖平台决策平台的服务质量努力和服务费用，餐饮商家决策产品价格，骑手决策配送服务质量努力程度，同时会受到来自平台或商家的服务质量激励。通过分析商家配送、平台配送和商家自建平台+配送三种运营模式，分别构建O2O外卖服务供应链成员的利润函数，运用博弈理论，优化得到不同模式下O2O外卖服务供应链成员的最优质量控制策略和最优利润。利用公式推导和对比分析，分别探讨了骑手激励金额上限和市场规模对服务供应链最优策略和最优利润的影响。通过数值仿真，可得结论：服务供应链各成员利润均随着市场规模的增大而增大，随着骑手激励金额上限的增加而先增大后减少。当市场规模较小时，平台配送模式下商家最优利润最大。而当市场规模较大时，商家自建平台+配送模式下商家最优利润最大。     

No Mind Reading Necessary: Conducting Evidence-Based Electronic Resource Marketing and Outreach Using Marketing Research Assessment

Abstract

In her presentation entitled “No Mind Reading Necessary: Conducting Evidence-Based Electronic Resource Marketing and Outreach” at the North Carolina Serials Conference April 2019, Kate Hill discussed marketing research strategies and outreach tools used to increase online users’ access to electronic resources and primary resources. In an effort to connect users to seldom-used resources, Jackson Library collaborated with university partners to develop surveys to identify the information-seeking behavior of its users and apply the gathered marketing research to strategically plan outreach activities.     

Unaddressed problems and research perspectives in scheduling blood collection from donors

Many optimisation problems arise in managing the Blood Donation (BD) supply chain. Most of them have been addressed in the literature, while other problems, e.g. donation scheduling, have not been sufficiently addressed so far. However, blood collection from donors may have a disruptive impact on the entire BD supply chain if not properly managed. For example, scheduling donation appointments based on some system metrics may improve the flow of blood units through the BD supply chain and increase the quality of service perceived by donors. In this short communication, we present the donation scheduling problem and highlight the lack of work in the literature that deals with this problem. Then, we analyse the impact of an unbalanced flow of blood units on the BD system and the benefits that may derive from a suitable appointment scheduling. Finally, we propose suggestions for future research in BD collection scheduling that may improve the BD process.     

基于消费者效用的生鲜农产品供应链生鲜度激励机制研究

生鲜供应链整体生鲜度的提升对减少浪费、提高供应链整体盈利水平及社会福利有重要意义。本文基于消费者效用理论研究了两供应商和单一零售商组成的供应链系统，构建了单周期下生鲜农产品生鲜度激励模型，模型以供应商为领导者，采用Stackelberg博弈方法求解得到了均衡状态下供应商、零售商的最优定价策略及供应商新鲜度努力选择。研究结果表明，供应商和零售商利润与消费者价格敏感系数呈反向变化，与新鲜度敏感系数呈同向变化。在价格竞争市场，供应商保鲜努力程度和利润与价格替代率呈反向变化；在生鲜度竞争市场，供应商保鲜努力程度和利润与新鲜度替代率呈同向变化。基于研究结论，厂商及政府应当联手引导消费者的消费观念，尽可能减少由于信息不对称引致的道德风险，在市场价格替代率不变甚至降低的情形下，提高生鲜度替代率，使得消费者的意愿支付价格上升，提高自身讨价还价能力，获取更多利润。     

产品服务供应链的“双重收益共享”合作机制

产品与服务融合缓解了"供需错位"矛盾，使得产品服务供应链探索成为"供给侧结构性改革"下供需结构性匹配的重要路径。本文刻画产品服务视角下供应链组织结构的本质特征，构建产品服务供应链合作模型，探讨合作机制下"帕累托改进"区间存在性，揭示合作机制对产品服务供应链效率的作用机理。核心研究发现：供应链多元化组织结构加剧收益分配冲突，并导致服务规模与供应链效率"倒挂"现象，而合作机制下"双重收益共享"合作模型能提升产品服务供应链效率。