Utilizing Bayesian predictive power in clinical trial design

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.     

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.     

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.     

考虑异质性行为的灾后应急物资动态调度优化

在以人道主义为本的应急救援活动中，不可忽视被救灾民和施救决策者们异质性行为的影响。一方面，将各灾民因救援物资需求未被及时满足而呈现的差异化心理痛苦度量成经济损失，并纳入应急救援调度的社会成本这一决策目标中；另一方面，在灾后物资调度决策中，关注具有异质性偏好的各应急决策者所展现出的不同救援态度。结合面向联合机会约束规划的动态供需平衡限制，最终构建一个考虑灾民和决策者们异质性行为的多阶段灾后救援物资分配和应急路径优化模型。采用2008年汶川地震为案例背景，应用遗传算法对模型求解和参数分析，将仿真结果与不考虑异质性行为的传统救援调度方案进行比较，得出一些结论为构建高效的应急救援体系提供有益参考。     

Changes in the Factors Influencing Public Acceptance of Nuclear Power Generation in Japan Since the 2011 Fukushima Daiichi Nuclear Disaster

Public support for nuclear power generation has decreased in Japan since the Fukushima Daiichi nuclear accident in March 2011. This study examines how the factors influencing public acceptance of nuclear power changed after this event. The influence factors examined are perceived benefit, perceived risk, trust in the managing bodies, and pro‐environmental orientation (i.e., new ecological paradigm). This study is based on cross‐sectional data collected from two online nationwide surveys: one conducted in November 2009, before the nuclear accident, and the other in October 2011, after the accident. This study's target respondents were residents of Aomori, Miyagi, and Fukushima prefectures in the Tohoku region of Japan, as these areas were the epicenters of the Great East Japan Earthquake and the locations of nuclear power stations. After the accident, trust in the managing bodies was found to have a stronger influence on perceived risk, and pro‐environmental orientation was found to have a stronger influence on trust in the managing bodies; however, perceived benefit had a weaker positive influence on public acceptance. We also discuss the theoretical and practical implications of these findings.     

Bayesian blinded sample size re-estimation

Information before unblinding regarding the success of confirmatory clinical trials is highly uncertain. Current techniques using point estimates of auxiliary parameters for estimating expected blinded sample size: (i) fail to describe the range of likely sample sizes obtained after the anticipated data are observed, and (ii) fail to adjust to the changing patient population. Sequential MCMC-based algorithms are implemented for purposes of sample size adjustments. The uncertainty arising from clinical trials is characterized by filtering later auxiliary parameters through their earlier counterparts and employing posterior distributions to estimate sample size and power. The use of approximate expected power estimates to determine the required additional sample size are closely related to techniques employing Simple Adjustments or the EM algorithm. By contrast with these, our proposed methodology provides intervals for the expected sample size using the posterior distribution of auxiliary parameters. Future decisions about additional subjects are better informed due to our ability to account for subject response heterogeneity over time. We apply the proposed methodologies to a depression trial. Our proposed blinded procedures should be considered for most studies due to ease of implementation.     

Turkey’s Twitter public diplomacy: Towards a “new” cult of personality

This study examined how Turkey uses social media as a tool for public diplomacy and how the state’s soft-power efforts have recently changed on the global stage. The researchers constructed a dataset of 2769 Twitter posts by the Turkish government’s most influential public diplomacy accounts. The analyses revealed that the focus of Turkey’s Twitter public diplomacy has become concentrated on the Middle East and North Africa (MENA) region and is thematically focused on the political values embodied by the Turkish president. The findings suggest that public diplomacy remains to be the diplomacy of the government, not of the public, and social media is used as just another tool for propaganda, not as a means of engagement with foreign publics. Further, the findings indicate the emergence of a “new” cult of personality in public diplomacy and point out the instrumental role of social media in changing the dynamics of leader-follower relationship. The study contributes to public relations theory and practice by advancing the burgeoning public diplomacy scholarship at the intersection of social media and relational approaches.     

Revanchist Masculinity: Gender Attitudes in Sex Work Management

Pimps, or male managers of female sex workers, are commonly represented in popular culture as hypermasculine and as a ubiquitous part of sex work. However, there is little empirical scholarship on pimps or the construction of their masculinity. Drawing on ethnographic and interview data, this article demonstrates how pimps produce a “revanchist masculinity” that seeks to reclaim power from women and establish status over other men. Pimps are suspicious of sex workers’ motives and deny them decision‐making power and profit sharing—processes that highlight how work practices can structure gender identity construction.