Embedding a COVID-19 group sequential clinical trial within an ongoing trial: lessons from an unusual experience.
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ABSTRACT:
SUBMITTER: Dequin PF
PROVIDER: S-EPMC8008347 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2n. In this paper, we consider the more practically useful setting of sample sizes in a the finite set {n1, n2, …, nL }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.
| S-EPMC4603757 | biostudies-literature
Project description:The first cluster of COVID-19 cases was reported in Wuhan, China on December 29th, 2019. Since then, China has experienced a pandemic of COVID-19.ObjectiveThis study aims to present the context in which the pandemic has evolved, the government's response and the pandemic's impact on public health and national economy.MethodsA review was conducted to collect relevant data from press releases and government reports.ResultsCOVID-19 poses a major public health threat on China with a cumulative number of cases over 89,000 (data cut-off date: August 9th, 2020). Between January and February 2020, China implemented a series of escalating policies (including a stringent nation-wide lockdown) to combat the pandemic. Therefore, it has been to a large extent limited to the Wuhan region. Social media such as WeChat and SinaWeibo played a crucial role in disseminating government information and public campaigns during the pandemic. Technologies were adopted to enable contact tracing and population travel patterns. The Chinese central government mobilized healthcare resources including healthcare personnel and medical materials to Wuhan in a highly effective way. Both central and regional governments launched financial policies to stimulate the economy, including special loans, tax extension, reduction or waiver. Nevertheless, the economy in China was significantly impacted especially during the lockdown period.ConclusionsChina has responded to the COVID-19 epidemic in a highly centralized and effective way. Balancing the needs to prevent a future pandemic and to boost economic recovery remains a challenge.
| S-EPMC7451009 | biostudies-literature
Project description:Ovarian cancer is the most lethal gynecological cancer, and despite years of research, with the exception of a BRCA mutation driving the use of PARP inhibitors, no new prognostic/predictive biomarkers are clinically available. Improvement in biomarker selection and validation may derive from the systematic inclusion of translational analyses into the design of clinical trials. In the era of personalized medicine, the prospective centralized collection of high-quality biological material, expert pathological revision, and association to well-controlled clinical data are important or even essential added values to clinical trials. Here, we present the academic experience of the MITO (Multicenter Italian Trial in Ovarian Cancer) group, including gynecologists, pathologists, oncologists, biostatisticians, and translational researchers, whose effort is dedicated to the care and basic/translational research of gynecologic cancer. In our ten years of experience, we have been able to collect and process, for translational analyses, formalin-fixed, paraffin-embedded blocks from more than one thousand ovarian cancer patients. Standard operating procedures for collection, shipping, and processing were developed and made available to MITO researchers through the coordinating center's web-based platform. Clinical data were collected through dedicated electronic case report forms hosted in a web-based electronic platform and stored in a central database at the trial's coordinating center, which performed all the analyses related to the proposed translational researches. During this time, we improved our strategies of block management from retrospective to prospective collection, up to the design of a prospective collection with a quality check for sample eligibility before patients' accrual. The final aim of our work is to share our experience by suggesting a guideline for the process of centralized collection, revision processing, and storing of formalin-fixed, paraffin-embedded blocks for translational purposes.
| S-EPMC7226822 | biostudies-literature
Project description:BackgroundElectronic medical record (EMR) chronic disease measurement can help direct primary care prevention and treatment strategies and plan health services resource management. Incomplete data and poor consistency of coded disease values within EMR problem lists are widespread issues that limit primary and secondary uses of these data. These issues were shared by the McMaster University Sentinel and Information Collaboration (MUSIC), a primary care practice-based research network (PBRN) located in Hamilton, Ontario, Canada.ObjectiveWe sought to develop and evaluate the effectiveness of new EMR interface tools aimed at improving the quantity and the consistency of disease codes recorded within the disease registry across the MUSIC PBRN.MethodsWe used a single-arm prospective trial design with preintervention and postintervention data analysis to assess the effect of the intervention on disease recording volume and quality. The MUSIC network holds data on over 75,080 patients, 37,212 currently rostered. There were 4 MUSIC network clinician champions involved in gap analysis of the disease coding process and in the iterative design of new interface tools. We leveraged terminology standards and factored EMR workflow and usability into a new interface solution that aimed to optimize code selection volume and quality while minimizing physician time burden. The intervention was integrated as part of usual clinical workflow during routine billing activities.ResultsAfter implementation of the new interface (June 25, 2017), we assessed the disease registry codes at 3 and 6 months (intervention period) to compare their volume and quality to preintervention levels (baseline period). A total of 17,496 International Classification of Diseases, 9th Revision (ICD9) code values were recorded in the disease registry during the 11.5-year (2006 to mid-2017) baseline period. A large gain in disease recording occurred in the intervention period (8516/17,496, 48.67% over baseline), resulting in a total of 26,774 codes. The coding rate increased by a factor of 11.2, averaging 1419 codes per month over the baseline average rate of 127 codes per month. The proportion of preferred ICD9 codes increased by 17.03% in the intervention period (11,007/17,496, 62.91% vs 7417/9278, 79.94%; χ21=819.4; P<.001). A total of 45.03% (4178/9278) of disease codes were entered by way of the new screen prompt tools, with significant increases between quarters (Jul-Sep: 2507/6140, 40.83% vs Oct-Dec: 1671/3148, 53.08%; χ21=126.2; P<.001).ConclusionsThe introduction of clinician co-designed, workflow-embedded disease coding tools is a very effective solution to the issues of poor disease coding and quality in EMRs. The substantial effectiveness in a routine care environment demonstrates usability, and the intervention detail described here should be generalizable to any setting. Significant improvements in problem list coding within primary care EMRs can be realized with minimal disruption to routine clinical workflow.
| S-EPMC7418012 | biostudies-literature
Project description:ObjectiveTo explore the experiences and lessons learnt by the study team and participants of the Workplace-based HIV self-testing among Men trial during the COVID-19 pandemic in Uganda.DesignAn explorative qualitative study comprising two virtual focus group discussions (FGDs) with 12 trial team members and 32 in-depth participant interviews (N=44). Data were collected via telephone calls for in-depth interviews or Zoom for FGDs and manually analysed by inductive content analysis.SettingFourteen private security companies in two Uganda districts.ParticipantsMembers of the clinical trial study team, and men working in private security companies who undertook workplace-based HIV testing.ResultsThe key themes for participants experiences were: 'challenges in accessing HIV treatment and care, and prevention services', 'misinformation' and 'difficulty participating in research activities'. The effects on HIV treatment and prevention resulted from; repercussions of the COVID-19 restrictions, participants fear of coinfection and negative experiences at health facilities. The difficulty in participating in research activities arose from: fear of infection with COVID-19 for the participants who tested HIV negative, transport difficulties, limited post-test psychosocial support and lack of support to initiate pre-exposure prophylaxis. The key study team reflections focused on the management of the clinical trial, effects of the local regulations and government policies and the need to adhere to ethical principles of research.ConclusionsFindings highlight the need to organise different forms of HIV support for persons living with HIV during a pandemic. Additionally, the national research regulators and ethics committees or review boards are strongly urged to develop policies and guidelines for the continuity of research and clinical trials in the event of future shocks. Furthermore, this study calls on the appropriate government agencies to ensure public and researchers' preparedness through continuing education and support.Trial registration numberClinicaltrials.gov NCT04164433; Pre-results.
| S-EPMC8061567 | biostudies-literature
Project description:Biological embedding occurs when life experience alters biological processes to affect later life health and well-being. Although extensive correlative data exist supporting the notion that epigenetic mechanisms such as DNA methylation underlie biological embedding, causal data are lacking. We describe specific epigenetic mechanisms and their potential roles in the biological embedding of experience. We also consider the nuanced relationships between the genome, the epigenome, and gene expression. Our ability to connect biological embedding to the epigenetic landscape in its complexity is challenging and complicated by the influence of multiple factors. These include cell type, age, the timing of experience, sex, and DNA sequence. Recent advances in molecular profiling and epigenome editing, combined with the use of comparative animal and human longitudinal studies, should enable this field to transition from correlative to causal analyses.
| S-EPMC7519272 | biostudies-literature
Project description:Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in our previous study.
| S-EPMC3591288 | biostudies-literature
Project description:IntroductionTobacco use is detrimental at any time. However, it is proving to be more dangerous during the COVID-19 pandemic. Tobacco use may increase the risk of being infected, increases the chances of complications, and also increases the probability of its spread. We assessed the awareness about this association and the impact of the lockdown on tobacco use among tobacco users registered before the lockdown for LifeFirst, a tobacco dependence treatment program.Methods1016 tobacco users were under active follow-up in their course of the 6-month counselling program. From 14 to 28 May 2020, 650 (64%) of these registered users were contacted by counsellors for follow-up sessions over the telephone. Semi-structured questionnaires were filled in during the calls.ResultsTwo-thirds (67%) of tobacco users were unaware of the association between tobacco and COVID-19. Only 30% of the users felt that the current situation had affected their tobacco use, the commonest impacts being unavailability and increased prices of tobacco products. While this was seen as an opportunity to quit by some users, some reported increased tobacco use due to increased stress. Of the 219 (34%) tobacco users who quit tobacco during the lockdown, 51% quit because of the lockdown and their concern over COVID-19. Abstinence among those who were aware of the association between the coronavirus and tobacco was twice that among those who were not aware.ConclusionsAwareness activities about the harmful effects of tobacco during the coronavirus pandemic have to be strengthened. Measures to motivate and support tobacco users to quit have to be provided through cessation services.
| S-EPMC7552854 | biostudies-literature
Project description:Since its initial recognition in December 2019, Coronavirus disease 19 (COVID-19) has quickly spread to a pandemic infectious disease. The causative agent has been recognized as a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), primarily affecting the respiratory tract. To date, no vaccines are available nor any specific treatment. To limit the number of infections, strict directives have been issued by governments that have been translated into equally rigorous guidelines notably for post-mortem examinations by international and national scientific societies. The recommendations for biosafety control required during specimen collection and handling have strongly limited the practice of autopsies of the COVID-19 patients to a few adequate laboratories. A full pathological examination has always been considered an important tool to better understand the pathophysiology of diseases, especially when the knowledge of an emerging disorder is limited and the impact on the healthcare system is significant. The first evidence of diffuse alveolar damage in the context of an acute respiratory distress syndrome has now been joined by the latest findings that report a more complex scenario in COVID-19, including a vascular involvement and a wide spectrum of associated pathologies. Ancillary tools such as electron microscopy and molecular biology used on autoptic tissue samples from autopsy are also significantly contributing to confirm and/or identify new aspects useful for a deeper knowledge of the pathogenetic mechanisms. This article will review and summarize the pathological findings described in COVID-19 until now, chiefly focusing on the respiratory tract, highlighting the importance of autopsy towards a better knowledge of this disease.
| S-EPMC7343579 | biostudies-literature
Project description:BackgroundIn dealing with community spread of COVID-19, two active interventions have been attempted or advocated-containment, and mitigation. Given the extensive impact of COVID-19 globally, there is international interest to learn from best practices that have been shown to work in controlling community spread to inform future outbreaks. This study explores the trajectory of COVID-19 infection in Singapore had the government intervention not focused on containment, but rather on mitigation. In addition, we estimate the actual COVID-19 infection cases in Singapore, given that confirmed cases are publicly available.Methods and findingsWe developed a COVID-19 infection model, which is a modified SIR model that differentiate between detected (diagnosed) and undetected (undiagnosed) individuals and segments total population into seven health states: susceptible (S), infected asymptomatic undiagnosed (A), infected asymptomatic diagnosed (I), infected symptomatic undiagnosed (U), infected symptomatic diagnosed (E), recovered (R), and dead (D). To account for the infection stages of the asymptomatic and symptomatic infected individuals, the asymptomatic infected individuals were further disaggregated into three infection stages: (a) latent (b) infectious and (c) non-infectious; while the symptomatic infected were disaggregated into two stages: (a) infectious and (b) non-infectious. The simulation result shows that by the end of the current epidemic cycle without considering the possibility of a second wave, under the containment intervention implemented in Singapore, the confirmed number of Singaporeans infected with COVID-19 (diagnosed asymptomatic and symptomatic cases) is projected to be 52,053 (with 95% confidence range of 49,370-54,735) representing 0.87% (0.83%-0.92%) of the total population; while the actual number of Singaporeans infected with COVID-19 (diagnosed and undiagnosed asymptomatic and symptomatic infected cases) is projected to be 86,041 (81,097-90,986), which is 1.65 times the confirmed cases and represents 1.45% (1.36%-1.53%) of the total population. A peak in infected cases is projected to have occurred on around day 125 (27/05/2020) for the confirmed infected cases and around day 115 (17/05/2020) for the actual infected cases. The number of deaths is estimated to be 37 (34-39) among those infected with COVID-19 by the end of the epidemic cycle; consequently, the perceived case fatality rate is projected to be 0.07%, while the actual case fatality rate is estimated to be 0.043%. Importantly, our simulation model results suggest that there about 65% more COVID-19 infection cases in Singapore that have not been captured in the official reported numbers which could be uncovered via a serological study. Compared to the containment intervention, a mitigation intervention would have resulted in early peak infection, and increase both the cumulative confirmed and actual infection cases and deaths.ConclusionEarly public health measures in the context of targeted, aggressive containment including swift and effective contact tracing and quarantine, was likely responsible for suppressing the number of COVID-19 infections in Singapore.
| S-EPMC8009429 | biostudies-literature