Evidence-based sizing of non-inferiority trials using decision models

Abstract Background There are significant challenges to the successful conduct of non-inferiority trials because they require large numbers to demonstrate that an alternative intervention is “not too much worse” than the standard. In this paper, we present a novel strategy for designing non-inferiority trials using an approach for determining the appropriate non-inferiority margin (δ), which explicitly balances the benefits of interventions in the two arms of the study (e.g. lower recurrence rate or better survival) with the burden of interventions (e.g. toxicity, pain), and early and late-term morbidity. Methods We use a decision analytic approach to simulate a trial using a fixed value for the trial outcome of interest (e.g. cancer incidence or recurrence) under the standard intervention (pS) and systematically varying the incidence of the outcome in the alternative intervention (pA). The non-inferiority margin, pA – pS = δ, is reached when the lower event rate of the standard therapy counterbalances the higher event rate but improved morbidity burden of the alternative. We consider the appropriate non-inferiority margin as the tipping point at which the quality-adjusted life-years saved in the two arms are equal. Results Using the European Polyp Surveillance non-inferiority trial as an example, our decision analytic approach suggests an appropriate non-inferiority margin, defined here as the difference between the two study arms in the 10-year risk of being diagnosed with colorectal cancer, of 0.42% rather than the 0.50% used to design the trial. The size of the non-inferiority margin was smaller for higher assumed burden of colonoscopies. Conclusions The example demonstrates that applying our proposed method appears feasible in real-world settings and offers the benefits of more explicit and rigorous quantification of the various considerations relevant for determining a non-inferiority margin and associated trial sample size.https://deepblue.lib.umich.edu/bitstream/2027.42/146777/1/12874_2018_Article_643.pd

Coxsackievirus B3 Inhibits Antigen Presentation In Vivo, Exerting a Profound and Selective Effect on the MHC Class I Pathway

Many viruses encode proteins whose major function is to evade or disable the host T cell response. Nevertheless, most viruses are readily detected by host T cells, and induce relatively strong T cell responses. Herein, we employ transgenic CD4+ and CD8+ T cells as sensors to evaluate in vitro and in vivo antigen presentation by coxsackievirus B3 (CVB3), and we show that this virus almost completely inhibits antigen presentation via the MHC class I pathway, thereby evading CD8+ T cell immunity. In contrast, the presentation of CVB3-encoded MHC class II epitopes is relatively unencumbered, and CVB3 induces in vivo CD4+ T cell responses that are, by several criteria, phenotypically normal. The cells display an effector phenotype and mature into multi-functional CVB3-specific memory CD4+ T cells that expand dramatically following challenge infection and rapidly differentiate into secondary effector cells capable of secreting multiple cytokines. Our findings have implications for the efficiency of antigen cross-presentation during coxsackievirus infection

The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models

The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models

(G)hosting television: Ghostwatch and its medium

This article’s subject is Ghostwatch (BBC, 1992), a drama broadcast on Halloween night of 1992 which adopted the rhetoric of live non-fiction programming, and attracted controversy and ultimately censure from the Broadcasting Standards Council. In what follows, we argue that Ghostwatch must be understood as a televisually-specific artwork and artefact. We discuss the programme’s ludic relationship with some key features of television during what Ellis (2000) has termed its era of ‘availability’, principally liveness, mass simultaneous viewing, and the flow of the television super-text. We trace the programme’s television-specific historicity whilst acknowledging its allusions and debts to other media (most notably film and radio). We explore the sophisticated ways in which Ghostwatch’s visual grammar and vocabulary and deployment of ‘broadcast talk’ (Scannell 1991) variously ape, comment upon and subvert the rhetoric of factual programming, and the ends to which these strategies are put. We hope that these arguments collectively demonstrate the aesthetic and historical significance of Ghostwatch and identify its relationship to its medium and that medium’s history. We offer the programme as an historically-reflexive artefact, and as an exemplary instance of the work of art in television’s age of broadcasting, liveness and co-presence

The need for early referral to palliative care especially for Black, Asian and minority ethnic groups in a COVID-19 pandemic:Findings from a service evaluation

Background: Palliative care services face challenges in adapting and responding to the COVID-19 pandemic. Understanding how palliative care needs and outcomes have changed during the pandemic compared to before the pandemic is crucial to inform service planning and research initiatives. Aim: To evaluate the impact of COVID-19 on symptoms, clinical characteristics, and outcomes for patients referred to a hospital-based palliative care service in a district general hospital in London, UK. Design: A retrospective service evaluation. Data were extracted from the electronic patient records. Setting/participants: The first 60 inpatients with confirmed COVID-19 infection, referred to the hospital palliative care service between 1 March 2020 and 23 April 2020, and another 60 inpatients, referred to the hospital palliative care service between 11 March 2019 and 23 April 2019, were included from a district general hospital in East London, UK. Results: Patients with COVID-19 have lower comorbidity scores, poorer performance status, and a shorter time from referral to death compared to patients without COVID-19. Breathlessness, drowsiness, agitation, and fever are the most prevalent symptoms during COVID-19 compared to pain and drowsiness pre-COVID-19. Time from admission to referral to palliative care is longer for Black, Asian and minority ethnic patients, especially during COVID-19. Conclusion: Early referral to palliative care is essential in COVID-19, especially for Black, Asian and minority ethnic groups. There is urgent need to research why Black, Asian and minority ethnic patients are referred late; how palliative care services have changed; and possible solutions to setting up responsive, flexible, and integrated services