首页 > 最新文献

Clinical Trials最新文献

英文 中文
Risk-benefit trade-offs and precision utilities in phase I-II clinical trials. I-II 期临床试验中的风险效益权衡和精确效用。
IF 2.7 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-06-01 Epub Date: 2023-12-18 DOI: 10.1177/17407745231214750
Pavlos Msaouel, Juhee Lee, Peter F Thall

Background: Identifying optimal doses in early-phase clinical trials is critically important. Therapies administered at doses that are either unsafe or biologically ineffective are unlikely to be successful in subsequent clinical trials or to obtain regulatory approval. Identifying appropriate doses for new agents is a complex process that involves balancing the risks and benefits of outcomes such as biological efficacy, toxicity, and patient quality of life.

Purpose: While conventional phase I trials rely solely on toxicity to determine doses, phase I-II trials explicitly account for both efficacy and toxicity, which enables them to identify doses that provide the most favorable risk-benefit trade-offs. It is also important to account for patient covariates, since one-size-fits-all treatment decisions are likely to be suboptimal within subgroups determined by prognostic variables or biomarkers. Notably, the selection of estimands can influence our conclusions based on the prognostic subgroup studied. For example, assuming monotonicity of the probability of response, higher treatment doses may yield more pronounced efficacy in favorable prognosis compared to poor prognosis subgroups when the estimand is mean or median survival. Conversely, when the estimand is the 3-month survival probability, higher treatment doses produce more pronounced efficacy in poor prognosis compared to favorable prognosis subgroups.

Methods and conclusions: Herein, we first describe why it is essential to consider clinical practice when designing a clinical trial and outline a stepwise process for doing this. We then review a precision phase I-II design based on utilities tailored to prognostic subgroups that characterize efficacy-toxicity risk-benefit trade-offs. The design chooses each patient's dose to optimize their expected utility and allows patients in different prognostic subgroups to have different optimal doses. We illustrate the design with a dose-finding trial of a new therapeutic agent for metastatic clear cell renal cell carcinoma.

背景:在早期临床试验中确定最佳剂量至关重要。用不安全或生物无效的剂量进行治疗不太可能在随后的临床试验中取得成功,也不太可能获得监管部门的批准。为新药确定合适的剂量是一个复杂的过程,涉及平衡生物疗效、毒性和患者生活质量等结果的风险和收益。目的:传统的 I 期试验仅依靠毒性来确定剂量,而 I-II 期试验则明确考虑疗效和毒性,这使它们能够确定风险-收益权衡最有利的剂量。考虑患者的协变量也很重要,因为在由预后变量或生物标志物决定的亚组中,"一刀切 "的治疗决策很可能不是最佳的。值得注意的是,根据所研究的预后亚组,估计因子的选择会影响我们的结论。例如,假设反应概率为单调性,当估计指标为平均生存期或中位生存期时,与预后不良亚组相比,较高的治疗剂量可能对预后良好的亚组产生更明显的疗效。相反,当估计指标为 3 个月生存概率时,与预后良好的亚组相比,较高的治疗剂量对预后不良的亚组产生更明显的疗效:在本文中,我们首先阐述了为什么在设计临床试验时必须考虑临床实践,并概述了设计临床试验的步骤。然后,我们回顾了一种基于效用的 I-II 期精准设计,这种效用是针对预后亚组量身定制的,能体现疗效-毒性风险-效益权衡的特点。该设计选择每位患者的剂量,以优化其预期效用,并允许不同预后亚组的患者使用不同的最佳剂量。我们以一种治疗转移性透明细胞肾细胞癌的新疗法的剂量探索试验来说明这种设计。
{"title":"Risk-benefit trade-offs and precision utilities in phase I-II clinical trials.","authors":"Pavlos Msaouel, Juhee Lee, Peter F Thall","doi":"10.1177/17407745231214750","DOIUrl":"10.1177/17407745231214750","url":null,"abstract":"<p><strong>Background: </strong>Identifying optimal doses in early-phase clinical trials is critically important. Therapies administered at doses that are either unsafe or biologically ineffective are unlikely to be successful in subsequent clinical trials or to obtain regulatory approval. Identifying appropriate doses for new agents is a complex process that involves balancing the risks and benefits of outcomes such as biological efficacy, toxicity, and patient quality of life.</p><p><strong>Purpose: </strong>While conventional phase I trials rely solely on toxicity to determine doses, phase I-II trials explicitly account for both efficacy and toxicity, which enables them to identify doses that provide the most favorable risk-benefit trade-offs. It is also important to account for patient covariates, since one-size-fits-all treatment decisions are likely to be suboptimal within subgroups determined by prognostic variables or biomarkers. Notably, the selection of estimands can influence our conclusions based on the prognostic subgroup studied. For example, assuming monotonicity of the probability of response, higher treatment doses may yield more pronounced efficacy in favorable prognosis compared to poor prognosis subgroups when the estimand is mean or median survival. Conversely, when the estimand is the 3-month survival probability, higher treatment doses produce more pronounced efficacy in poor prognosis compared to favorable prognosis subgroups.</p><p><strong>Methods and conclusions: </strong>Herein, we first describe why it is essential to consider clinical practice when designing a clinical trial and outline a stepwise process for doing this. We then review a precision phase I-II design based on utilities tailored to prognostic subgroups that characterize efficacy-toxicity risk-benefit trade-offs. The design chooses each patient's dose to optimize their expected utility and allows patients in different prognostic subgroups to have different optimal doses. We illustrate the design with a dose-finding trial of a new therapeutic agent for metastatic clear cell renal cell carcinoma.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"287-297"},"PeriodicalIF":2.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11132955/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138799238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Statistical and practical considerations in planning and conduct of dose-optimization trials. 规划和进行剂量优化试验的统计和实际考虑因素。
IF 2.2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-06-01 Epub Date: 2024-01-19 DOI: 10.1177/17407745231207085
Ying Yuan, Heng Zhou, Suyu Liu

The U.S. Food and Drug Administration launched Project Optimus with the aim of shifting the paradigm of dose-finding and selection toward identifying the optimal biological dose that offers the best balance between benefit and risk, rather than the maximum tolerated dose. However, achieving dose optimization is a challenging task that involves a variety of factors and is considerably more complicated than identifying the maximum tolerated dose, both in terms of design and implementation. This article provides a comprehensive review of various design strategies for dose-optimization trials, including phase 1/2 and 2/3 designs, and highlights their respective advantages and disadvantages. In addition, practical considerations for selecting an appropriate design and planning and executing the trial are discussed. The article also presents freely available software tools that can be utilized for designing and implementing dose-optimization trials. The approaches and their implementation are illustrated through real-world examples.

美国食品和药物管理局启动 "Optimus 项目 "的目的是将剂量寻找和选择的范式从最大耐受剂量转变为能在效益和风险之间取得最佳平衡的最佳生物剂量。然而,实现剂量优化是一项具有挑战性的任务,涉及多种因素,在设计和实施方面都比确定最大耐受剂量复杂得多。本文全面回顾了剂量优化试验的各种设计策略,包括1/2期和2/3期设计,并强调了它们各自的优缺点。此外,文章还讨论了选择适当设计、规划和执行试验的实际注意事项。文章还介绍了可用于设计和实施剂量优化试验的免费软件工具。文章通过实际案例对这些方法及其实施进行了说明。
{"title":"Statistical and practical considerations in planning and conduct of dose-optimization trials.","authors":"Ying Yuan, Heng Zhou, Suyu Liu","doi":"10.1177/17407745231207085","DOIUrl":"10.1177/17407745231207085","url":null,"abstract":"<p><p>The U.S. Food and Drug Administration launched Project Optimus with the aim of shifting the paradigm of dose-finding and selection toward identifying the optimal biological dose that offers the best balance between benefit and risk, rather than the maximum tolerated dose. However, achieving dose optimization is a challenging task that involves a variety of factors and is considerably more complicated than identifying the maximum tolerated dose, both in terms of design and implementation. This article provides a comprehensive review of various design strategies for dose-optimization trials, including phase 1/2 and 2/3 designs, and highlights their respective advantages and disadvantages. In addition, practical considerations for selecting an appropriate design and planning and executing the trial are discussed. The article also presents freely available software tools that can be utilized for designing and implementing dose-optimization trials. The approaches and their implementation are illustrated through real-world examples.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"273-286"},"PeriodicalIF":2.2,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11134987/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139502342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Leveraging the functionality of Research Electronic Data Capture (REDCap) to enhance data collection and quality in the Opioid Analgesic Reduction Study. 利用研究电子数据捕获(REDCap)的功能来提高阿片类镇痛减少研究的数据收集和质量。
IF 2.7 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-06-01 Epub Date: 2023-11-14 DOI: 10.1177/17407745231212190
Janine Fredericks-Younger, Patricia Greenberg, Tracy Andrews, Pamela B Matheson, Paul J Desjardins, Shou-En Lu, Cecile A Feldman

Background: The Opioid Analgesic Reduction Study is a double-blind, prospective, clinical trial investigating analgesic effectiveness in the management of acute post-surgical pain after impacted third molar extraction across five clinical sites. Specifically, Opioid Analgesic Reduction Study examines a commonly prescribed opioid combination (hydrocodone/acetaminophen) against a non-opioid combination (ibuprofen/acetaminophen). The Opioid Analgesic Reduction Study employs a novel, electronic infrastructure, leveraging the functionality of its data management system, Research Electronic Data Capture, to not only serve as its data reservoir but also provide the framework for its quality management program.

Methods: Within the Opioid Analgesic Reduction Study, Research Electronic Data Capture is expanded into a multi-function management tool, serving as the hub for its clinical data management, project management and credentialing, materials management, and quality management. Research Electronic Data Capture effectively captures data, displays/tracks study progress, triggers follow-up, and supports quality management processes.

Results: At 72% study completion, over 12,000 subject data forms have been executed in Research Electronic Data Capture with minimal missing (0.15%) or incomplete or erroneous forms (0.06%). Five hundred, twenty-three queries were initiated to request clarifications and/or address missing data and data discrepancies.

Conclusion: Research Electronic Data Capture is an effective digital health technology that can be maximized to contribute to the success of a clinical trial. The Research Electronic Data Capture infrastructure and enhanced functionality used in Opioid Analgesic Reduction Study provides the framework and the logic that ensures complete, accurate, data while guiding an effective, efficient workflow that can be followed by team members across sites. This enhanced data reliability and comprehensive quality management processes allow for better preparedness and readiness for clinical monitoring and regulatory reporting.

背景:阿片类药物镇痛减少研究是一项双盲、前瞻性临床试验,研究在五个临床部位对第三磨牙阻生拔牙后急性术后疼痛的镇痛效果。具体来说,阿片类镇痛减少研究检查了常用的阿片类药物组合(氢可酮/对乙酰氨基酚)和非阿片类药物组合(布洛芬/对乙酰氨基酚)。阿片类镇痛药减少研究采用了一种新颖的电子基础设施,利用其数据管理系统的功能,研究电子数据捕获,不仅作为其数据储存库,而且为其质量管理计划提供框架。方法:在阿片类镇痛减少研究中,研究电子数据采集扩展为多功能管理工具,作为临床数据管理、项目管理和认证、材料管理和质量管理的中心。研究电子数据捕获有效地捕获数据,显示/跟踪研究进度,触发后续行动,并支持质量管理流程。结果:在72%的研究完成时,在研究电子数据捕获中执行了超过12,000个受试者数据表格,其中最小的缺失(0.15%)或不完整或错误的表格(0.06%)。提出了523项查询,要求澄清和/或解决丢失的数据和数据差异。结论:研究电子数据采集是一种有效的数字卫生技术,可以最大限度地促进临床试验的成功。在阿片类镇痛减少研究中使用的研究电子数据捕获基础设施和增强功能提供了框架和逻辑,确保数据完整、准确,同时指导团队成员跨站点遵循的有效、高效的工作流程。这种增强的数据可靠性和全面的质量管理过程可以为临床监测和监管报告提供更好的准备和准备。
{"title":"Leveraging the functionality of Research Electronic Data Capture (REDCap) to enhance data collection and quality in the Opioid Analgesic Reduction Study.","authors":"Janine Fredericks-Younger, Patricia Greenberg, Tracy Andrews, Pamela B Matheson, Paul J Desjardins, Shou-En Lu, Cecile A Feldman","doi":"10.1177/17407745231212190","DOIUrl":"10.1177/17407745231212190","url":null,"abstract":"<p><strong>Background: </strong>The Opioid Analgesic Reduction Study is a double-blind, prospective, clinical trial investigating analgesic effectiveness in the management of acute post-surgical pain after impacted third molar extraction across five clinical sites. Specifically, Opioid Analgesic Reduction Study examines a commonly prescribed opioid combination (hydrocodone/acetaminophen) against a non-opioid combination (ibuprofen/acetaminophen). The Opioid Analgesic Reduction Study employs a novel, electronic infrastructure, leveraging the functionality of its data management system, Research Electronic Data Capture, to not only serve as its data reservoir but also provide the framework for its quality management program.</p><p><strong>Methods: </strong>Within the Opioid Analgesic Reduction Study, Research Electronic Data Capture is expanded into a multi-function management tool, serving as the hub for its clinical data management, project management and credentialing, materials management, and quality management. Research Electronic Data Capture effectively captures data, displays/tracks study progress, triggers follow-up, and supports quality management processes.</p><p><strong>Results: </strong>At 72% study completion, over 12,000 subject data forms have been executed in Research Electronic Data Capture with minimal missing (0.15%) or incomplete or erroneous forms (0.06%). Five hundred, twenty-three queries were initiated to request clarifications and/or address missing data and data discrepancies.</p><p><strong>Conclusion: </strong>Research Electronic Data Capture is an effective digital health technology that can be maximized to contribute to the success of a clinical trial. The Research Electronic Data Capture infrastructure and enhanced functionality used in Opioid Analgesic Reduction Study provides the framework and the logic that ensures complete, accurate, data while guiding an effective, efficient workflow that can be followed by team members across sites. This enhanced data reliability and comprehensive quality management processes allow for better preparedness and readiness for clinical monitoring and regulatory reporting.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"381-389"},"PeriodicalIF":2.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11090991/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92153017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A review of patient recruitment in randomised controlled trials of preoperative exercise. 术前锻炼随机对照试验的患者招募回顾。
IF 2.2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-06-01 Epub Date: 2023-12-27 DOI: 10.1177/17407745231219270
Daniel Steffens, Michael Solomon, Jane Young, Paula R Beckenkamp, Jenna Bartyn, Cherry Koh, Mark Hancock

Background: Randomised controlled trials (RCTs) are considered the gold standard design to determine the effectiveness of an intervention, as the only method of decreasing section bias and minimising random error. However, participant recruitment to randomised controlled trials is a major challenge, with many trials failing to recruit the targeted sample size accordingly to the planned protocol. Thus, the aim of this review is to detail the recruitment challenges of preoperative exercise clinical trials.

Methods: A comprehensive search was performed on MEDLINE, Embase, The Cochrane Library, CINAHL, AMED and PsycINFO from inception to July 2021. Randomised controlled trials investigating the effectiveness of preoperative exercise on postoperative complication and/or length of hospital stay in adult cancer patients were included. Main outcomes included recruitment rate, retention rate, number of days needed to screen and recruit one patient and trial recruitment duration. Descriptive statistics were used to summarise outcomes of interest.

Results: A total of 27 trials were identified, including 3656 patients screened (N = 21) and 1414 randomised (median recruitment rate (interquartile range) = 53.6% (25.2%-67.6%), N = 21). The sample size of the included trials ranged from 19 to 270 (median = 48.0; interquartile range = 40.0-85.0) and the duration of trial recruitment ranged from 3 to 50 months (median = 19.0 months; interquartile range = 10.5-34.0). Overall, a median of 3.6 days was needed to screen one patient, whereas 13.7 days were needed to randomise one participant. Over the trials duration, the median dropout rate was 7.9%. Variations in recruitment outcomes were observed across trials of different cancer types but were not statistically significant.

Conclusion: The recruitment of participants to preoperative exercise randomised controlled trials is challenging, but patient retention appears to be less of a problem. Future trials investigating the effectiveness of a preoperative exercise programme following cancer surgery should consider the time taken to recruit patients. Strategies associated with improved recruitment should be investigated in future studies.

背景:随机对照试验(RCT)被认为是确定干预措施有效性的黄金标准设计,是减少部分偏差和最小化随机误差的唯一方法。然而,随机对照试验的参与者招募是一项重大挑战,许多试验未能按照计划方案招募到目标样本量。因此,本综述旨在详细介绍术前运动临床试验的招募挑战:方法:我们在 MEDLINE、Embase、The Cochrane Library、CINAHL、AMED 和 PsycINFO 上进行了全面检索。研究术前锻炼对成年癌症患者术后并发症和/或住院时间的有效性的随机对照试验均被纳入其中。主要结果包括招募率、保留率、筛选和招募一名患者所需的天数以及试验招募持续时间。使用描述性统计来总结相关结果:共确定了 27 项试验,其中筛选了 3656 名患者(N = 21),随机分配了 1414 名患者(中位数招募率(四分位间范围)= 53.6% (25.2%-67.6%),N = 21)。纳入试验的样本量从 19 个到 270 个不等(中位数 = 48.0;四分位数间距 = 40.0-85.0),试验招募持续时间从 3 个月到 50 个月(中位数 = 19.0 个月;四分位数间距 = 10.5-34.0)不等。总体而言,筛选一名患者的时间中位数为 3.6 天,而随机分配一名参与者的时间为 13.7 天。在整个试验期间,中位辍学率为 7.9%。在不同癌症类型的试验中,招募结果存在差异,但无统计学意义:结论:术前运动随机对照试验的参与者招募工作具有挑战性,但患者保留率似乎问题不大。未来研究癌症手术后术前锻炼计划有效性的试验应考虑招募患者所需的时间。在未来的研究中应调查与改善招募相关的策略。
{"title":"A review of patient recruitment in randomised controlled trials of preoperative exercise.","authors":"Daniel Steffens, Michael Solomon, Jane Young, Paula R Beckenkamp, Jenna Bartyn, Cherry Koh, Mark Hancock","doi":"10.1177/17407745231219270","DOIUrl":"10.1177/17407745231219270","url":null,"abstract":"<p><strong>Background: </strong>Randomised controlled trials (RCTs) are considered the gold standard design to determine the effectiveness of an intervention, as the only method of decreasing section bias and minimising random error. However, participant recruitment to randomised controlled trials is a major challenge, with many trials failing to recruit the targeted sample size accordingly to the planned protocol. Thus, the aim of this review is to detail the recruitment challenges of preoperative exercise clinical trials.</p><p><strong>Methods: </strong>A comprehensive search was performed on MEDLINE, Embase, The Cochrane Library, CINAHL, AMED and PsycINFO from inception to July 2021. Randomised controlled trials investigating the effectiveness of preoperative exercise on postoperative complication and/or length of hospital stay in adult cancer patients were included. Main outcomes included recruitment rate, retention rate, number of days needed to screen and recruit one patient and trial recruitment duration. Descriptive statistics were used to summarise outcomes of interest.</p><p><strong>Results: </strong>A total of 27 trials were identified, including 3656 patients screened (N = 21) and 1414 randomised (median recruitment rate (interquartile range) = 53.6% (25.2%-67.6%), N = 21). The sample size of the included trials ranged from 19 to 270 (median = 48.0; interquartile range = 40.0-85.0) and the duration of trial recruitment ranged from 3 to 50 months (median = 19.0 months; interquartile range = 10.5-34.0). Overall, a median of 3.6 days was needed to screen one patient, whereas 13.7 days were needed to randomise one participant. Over the trials duration, the median dropout rate was 7.9%. Variations in recruitment outcomes were observed across trials of different cancer types but were not statistically significant.</p><p><strong>Conclusion: </strong>The recruitment of participants to preoperative exercise randomised controlled trials is challenging, but patient retention appears to be less of a problem. Future trials investigating the effectiveness of a preoperative exercise programme following cancer surgery should consider the time taken to recruit patients. Strategies associated with improved recruitment should be investigated in future studies.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"371-380"},"PeriodicalIF":2.2,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139039630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Applications of the partial-order continual reassessment method in the early development of treatment combinations. 部分阶次持续再评估法在治疗组合早期开发中的应用。
IF 2.2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-06-01 Epub Date: 2024-03-30 DOI: 10.1177/17407745241234634
Nolan A Wages, Patrick M Dillon, Craig A Portell, Craig L Slingluff, Gina R Petroni

Combination therapy is increasingly being explored as a promising approach for improving cancer treatment outcomes. However, identifying effective dose combinations in early oncology drug development is challenging due to limited sample sizes in early-phase clinical trials. This task becomes even more complex when multiple agents are being escalated simultaneously, potentially leading to a loss of monotonic toxicity order with respect to the dose. Traditional single-agent trial designs are insufficient for this multi-dimensional problem, necessitating the development and implementation of dose-finding methods specifically designed for drug combinations. While, in practice, approaches to this problem have focused on preselecting combinations with a known toxicity order and applying single-agent designs, this limits the number of combinations considered and may miss promising dose combinations. In recent years, several novel designs have been proposed for exploring partially ordered drug combination spaces with the goal of identifying a maximum tolerated dose combination, based on safety, or an optimal dose combination, based on toxicity and efficacy. However, their implementation in clinical practice remains limited. In this article, we describe the application of the partial order continual reassessment method and its extensions for combination therapies in early-phase clinical trials. We present completed trials that use safety endpoints to identify maximum tolerated dose combinations and adaptively use both safety and efficacy endpoints to determine optimal treatment strategies. We discuss the effectiveness of the partial-order continual reassessment method and its extensions in identifying optimal treatment strategies and provide our experience with executing these novel adaptive designs in practice. By utilizing innovative dose-finding methods, researchers and clinicians can more effectively navigate the challenges of combination therapy development, ultimately improving patient outcomes in the treatment of cancer.

作为改善癌症治疗效果的一种有前途的方法,联合疗法正被越来越多的人所探索。然而,由于早期临床试验的样本量有限,在早期肿瘤药物开发中确定有效的剂量组合具有挑战性。当多种药物同时升级时,这项任务就变得更加复杂,有可能导致剂量失去单调的毒性顺序。传统的单药试验设计不足以解决这一多维问题,因此有必要开发和实施专为联合用药设计的剂量确定方法。虽然在实践中,解决这一问题的方法主要是预选已知毒性顺序的组合,并应用单剂设计,但这限制了考虑的组合数量,并可能错过有希望的剂量组合。近年来,人们提出了几种探索部分有序药物组合空间的新型设计,目的是根据安全性确定最大耐受剂量组合,或根据毒性和疗效确定最佳剂量组合。然而,它们在临床实践中的应用仍然有限。在本文中,我们介绍了部分阶次持续再评估法及其扩展方法在早期临床试验中联合疗法中的应用。我们介绍了已完成的试验,这些试验使用安全性终点来确定最大耐受剂量组合,并适应性地使用安全性和有效性终点来确定最佳治疗策略。我们讨论了部分阶次持续再评估法及其扩展方法在确定最佳治疗策略方面的有效性,并介绍了我们在实践中执行这些新型适应性设计的经验。通过利用创新的剂量寻找方法,研究人员和临床医生可以更有效地应对联合疗法开发过程中的挑战,最终改善癌症患者的治疗效果。
{"title":"Applications of the partial-order continual reassessment method in the early development of treatment combinations.","authors":"Nolan A Wages, Patrick M Dillon, Craig A Portell, Craig L Slingluff, Gina R Petroni","doi":"10.1177/17407745241234634","DOIUrl":"10.1177/17407745241234634","url":null,"abstract":"<p><p>Combination therapy is increasingly being explored as a promising approach for improving cancer treatment outcomes. However, identifying effective dose combinations in early oncology drug development is challenging due to limited sample sizes in early-phase clinical trials. This task becomes even more complex when multiple agents are being escalated simultaneously, potentially leading to a loss of monotonic toxicity order with respect to the dose. Traditional single-agent trial designs are insufficient for this multi-dimensional problem, necessitating the development and implementation of dose-finding methods specifically designed for drug combinations. While, in practice, approaches to this problem have focused on preselecting combinations with a known toxicity order and applying single-agent designs, this limits the number of combinations considered and may miss promising dose combinations. In recent years, several novel designs have been proposed for exploring partially ordered drug combination spaces with the goal of identifying a maximum tolerated dose combination, based on safety, or an optimal dose combination, based on toxicity and efficacy. However, their implementation in clinical practice remains limited. In this article, we describe the application of the partial order continual reassessment method and its extensions for combination therapies in early-phase clinical trials. We present completed trials that use safety endpoints to identify maximum tolerated dose combinations and adaptively use both safety and efficacy endpoints to determine optimal treatment strategies. We discuss the effectiveness of the partial-order continual reassessment method and its extensions in identifying optimal treatment strategies and provide our experience with executing these novel adaptive designs in practice. By utilizing innovative dose-finding methods, researchers and clinicians can more effectively navigate the challenges of combination therapy development, ultimately improving patient outcomes in the treatment of cancer.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"331-339"},"PeriodicalIF":2.2,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140329661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A comparison of alternative ranking methods in two-stage clinical trials with multiple interventions: An application to the anxiolysis for laceration repair in children trial. 比较具有多种干预措施的两阶段临床试验中的其他排序方法:应用于儿童裂伤修复抗焦虑试验。
IF 2.2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-05-21 DOI: 10.1177/17407745241251812
Nam-Anh Tran, Abigail McGrory, Naveen Poonai, Anna Heath

Background/aims: Multi-arm, multi-stage trials frequently include a standard care to which all interventions are compared. This may increase costs and hinders comparisons among the experimental arms. Furthermore, the standard care may not be evident, particularly when there is a large variation in standard practice. Thus, we aimed to develop an adaptive clinical trial that drops ineffective interventions following an interim analysis before selecting the best intervention at the final stage without requiring a standard care.

Methods: We used Bayesian methods to develop a multi-arm, two-stage adaptive trial and evaluated two different methods for ranking interventions, the probability that each intervention was optimal (Pbest) and using the surface under the cumulative ranking curve (SUCRA), at both the interim and final analysis. The proposed trial design determines the maximum sample size for each intervention using the Average Length Criteria. The interim analysis takes place at approximately half the pre-specified maximum sample size and aims to drop interventions for futility if either Pbest or the SUCRA is below a pre-specified threshold. The final analysis compares all remaining interventions at the maximum sample size to conclude superiority based on either Pbest or the SUCRA. The two ranking methods were compared across 12 scenarios that vary the number of interventions and the assumed differences between the interventions. The thresholds for futility and superiority were chosen to control type 1 error, and then the predictive power and expected sample size were evaluated across scenarios. A trial comparing three interventions that aim to reduce anxiety for children undergoing a laceration repair in the emergency department was then designed, known as the Anxiolysis for Laceration Repair in Children Trial (ALICE) trial.

Results: As the number of interventions increases, the SUCRA results in a higher predictive power compared with Pbest. Using Pbest results in a lower expected sample size when there is an effective intervention. Using the Average Length Criterion, the ALICE trial has a maximum sample size for each arm of 100 patients. This sample size results in a 86% and 85% predictive power using Pbest and the SUCRA, respectively. Thus, we chose Pbest as the ranking method for the ALICE trial.

Conclusion: Bayesian ranking methods can be used in multi-arm, multi-stage trials with no clear control intervention. When more interventions are included, the SUCRA results in a higher power than Pbest. Future work should consider whether other ranking methods may also be relevant for clinical trial design.

背景/目的:多臂、多阶段试验通常包括一种标准护理,所有干预措施都要与之进行比较。这可能会增加成本,并阻碍各试验组之间的比较。此外,标准治疗可能并不明显,尤其是在标准实践差异较大的情况下。因此,我们旨在开发一种适应性临床试验,在进行中期分析后放弃无效干预措施,然后在最后阶段选择最佳干预措施,而不需要标准疗法:我们使用贝叶斯方法开发了一种多臂、两阶段适应性试验,并在中期和最终分析中评估了两种不同的干预措施排序方法,即每种干预措施为最佳的概率(Pbest)和使用累积排序曲线下表面(SUCRA)。拟议的试验设计使用平均长度标准确定每种干预措施的最大样本量。中期分析的样本量约为预先规定的最大样本量的一半,目的是在 Pbest 或 SUCRA 低于预先规定的阈值时以无效为由放弃干预。最终分析在最大样本量下对所有剩余干预措施进行比较,根据 Pbest 或 SUCRA 得出优越性结论。这两种排序方法在 12 种情况下进行了比较,这些情况下干预措施的数量和干预措施之间的假定差异各不相同。选择无效性和优越性的阈值是为了控制1型误差,然后在不同情况下评估预测能力和预期样本量。然后设计了一项试验,即儿童裂伤修复抗焦虑试验(ALICE),旨在比较三种干预措施,以减轻急诊科接受裂伤修复的儿童的焦虑:结果:随着干预措施数量的增加,SUCRA 的预测能力高于 Pbest。当存在有效干预时,使用 Pbest 会导致预期样本量降低。使用平均长度标准,ALICE 试验每个臂的最大样本量为 100 名患者。使用 Pbest 和 SUCRA 的预测能力分别为 86% 和 85%。因此,我们选择 Pbest 作为 ALICE 试验的排序方法:结论:贝叶斯排序法可用于无明确对照干预的多臂、多阶段试验。结论:贝叶斯排序法可用于无明确对照干预措施的多臂、多阶段试验。当纳入更多干预措施时,SUCRA 的结果比 Pbest 更有说服力。未来的工作应考虑其他排序方法是否也适用于临床试验设计。
{"title":"A comparison of alternative ranking methods in two-stage clinical trials with multiple interventions: An application to the anxiolysis for laceration repair in children trial.","authors":"Nam-Anh Tran, Abigail McGrory, Naveen Poonai, Anna Heath","doi":"10.1177/17407745241251812","DOIUrl":"10.1177/17407745241251812","url":null,"abstract":"<p><strong>Background/aims: </strong>Multi-arm, multi-stage trials frequently include a standard care to which all interventions are compared. This may increase costs and hinders comparisons among the experimental arms. Furthermore, the standard care may not be evident, particularly when there is a large variation in standard practice. Thus, we aimed to develop an adaptive clinical trial that drops ineffective interventions following an interim analysis before selecting the best intervention at the final stage without requiring a standard care.</p><p><strong>Methods: </strong>We used Bayesian methods to develop a multi-arm, two-stage adaptive trial and evaluated two different methods for ranking interventions, the probability that each intervention was optimal (P<sub><i>best</i></sub>) and using the surface under the cumulative ranking curve (SUCRA), at both the interim and final analysis. The proposed trial design determines the maximum sample size for each intervention using the Average Length Criteria. The interim analysis takes place at approximately half the pre-specified maximum sample size and aims to drop interventions for futility if either P<sub><i>best</i></sub> or the SUCRA is below a pre-specified threshold. The final analysis compares all remaining interventions at the maximum sample size to conclude superiority based on either P<sub><i>best</i></sub> or the SUCRA. The two ranking methods were compared across 12 scenarios that vary the number of interventions and the assumed differences between the interventions. The thresholds for futility and superiority were chosen to control type 1 error, and then the predictive power and expected sample size were evaluated across scenarios. A trial comparing three interventions that aim to reduce anxiety for children undergoing a laceration repair in the emergency department was then designed, known as the Anxiolysis for Laceration Repair in Children Trial (ALICE) trial.</p><p><strong>Results: </strong>As the number of interventions increases, the SUCRA results in a higher predictive power compared with P<sub><i>best</i></sub>. Using P<sub><i>best</i></sub> results in a lower expected sample size when there is an effective intervention. Using the Average Length Criterion, the ALICE trial has a maximum sample size for each arm of 100 patients. This sample size results in a 86% and 85% predictive power using P<sub><i>best</i></sub> and the SUCRA, respectively. Thus, we chose P<sub><i>best</i></sub> as the ranking method for the ALICE trial.</p><p><strong>Conclusion: </strong>Bayesian ranking methods can be used in multi-arm, multi-stage trials with no clear control intervention. When more interventions are included, the SUCRA results in a higher power than P<sub><i>best</i></sub>. Future work should consider whether other ranking methods may also be relevant for clinical trial design.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241251812"},"PeriodicalIF":2.2,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11528845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141070934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Causal interpretation of the hazard ratio in randomized clinical trials 随机临床试验中危险比的因果解释
IF 2.7 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-04-29 DOI: 10.1177/17407745241243308
Michael P Fay, Fan Li
Background:Although the hazard ratio has no straightforward causal interpretation, clinical trialists commonly use it as a measure of treatment effect.Methods:We review the definition and examples of causal estimands. We discuss the causal interpretation of the hazard ratio from a two-arm randomized clinical trial, and the implications of proportional hazards assumptions in the context of potential outcomes. We illustrate the application of these concepts in a synthetic model and in a model of the time-varying effects of COVID-19 vaccination.Results:We define causal estimands as having either an individual-level or population-level interpretation. Difference-in-expectation estimands are both individual-level and population-level estimands, whereas without strong untestable assumptions the causal rate ratio and hazard ratio have only population-level interpretations. We caution users against making an incorrect individual-level interpretation, emphasizing that in general a hazard ratio does not on average change each individual’s hazard by a factor. We discuss a potentially valid interpretation of the constant hazard ratio as a population-level causal effect under the proportional hazards assumption.Conclusion:We conclude that the population-level hazard ratio remains a useful estimand, but one must interpret it with appropriate attention to the underlying causal model. This is especially important for interpreting hazard ratios over time.
背景:虽然危险比没有直接的因果解释,但临床试验人员通常将其用作治疗效果的衡量标准。方法:我们回顾了因果估计的定义和示例。我们讨论了双臂随机临床试验中危险比的因果解释,以及潜在结果中比例危险假设的含义。我们说明了这些概念在合成模型和 COVID-19 疫苗接种时变效应模型中的应用。期望差异估计值既是个体水平的估计值,也是人群水平的估计值,而在没有强烈的不可检验假设的情况下,因果比率比和危险比只具有人群水平的解释。我们提醒用户不要做出不正确的个体水平解释,并强调一般来说,危险比并不会平均改变每个人的危险系数。我们讨论了在比例危险假设下将恒定危险比解释为人群水平因果效应的潜在有效解释。结论:我们得出结论,人群水平的危险比仍然是一个有用的估计指标,但在解释它时必须适当注意基本的因果模型。这对于解释随时间变化的危险比尤为重要。
{"title":"Causal interpretation of the hazard ratio in randomized clinical trials","authors":"Michael P Fay, Fan Li","doi":"10.1177/17407745241243308","DOIUrl":"https://doi.org/10.1177/17407745241243308","url":null,"abstract":"Background:Although the hazard ratio has no straightforward causal interpretation, clinical trialists commonly use it as a measure of treatment effect.Methods:We review the definition and examples of causal estimands. We discuss the causal interpretation of the hazard ratio from a two-arm randomized clinical trial, and the implications of proportional hazards assumptions in the context of potential outcomes. We illustrate the application of these concepts in a synthetic model and in a model of the time-varying effects of COVID-19 vaccination.Results:We define causal estimands as having either an individual-level or population-level interpretation. Difference-in-expectation estimands are both individual-level and population-level estimands, whereas without strong untestable assumptions the causal rate ratio and hazard ratio have only population-level interpretations. We caution users against making an incorrect individual-level interpretation, emphasizing that in general a hazard ratio does not on average change each individual’s hazard by a factor. We discuss a potentially valid interpretation of the constant hazard ratio as a population-level causal effect under the proportional hazards assumption.Conclusion:We conclude that the population-level hazard ratio remains a useful estimand, but one must interpret it with appropriate attention to the underlying causal model. This is especially important for interpreting hazard ratios over time.","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":"2012 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140841816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reply to Heitjan’s commentary 回复 Heitjan 的评论
IF 2.7 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-04-29 DOI: 10.1177/17407745241243311
Michael P Fay, Fan Li
{"title":"Reply to Heitjan’s commentary","authors":"Michael P Fay, Fan Li","doi":"10.1177/17407745241243311","DOIUrl":"https://doi.org/10.1177/17407745241243311","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":"37 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140830354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comment on “Causal interpretation of the hazard ratio in randomized clinical trials” by Fay and Li 就 Fay 和 Li 的 "随机临床试验中危险比的因果解释 "发表评论
IF 2.7 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-04-29 DOI: 10.1177/17407745241243307
Daniel F Heitjan
{"title":"Comment on “Causal interpretation of the hazard ratio in randomized clinical trials” by Fay and Li","authors":"Daniel F Heitjan","doi":"10.1177/17407745241243307","DOIUrl":"https://doi.org/10.1177/17407745241243307","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":"24 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140830296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design and implementation of community consultation for research conducted under exception from informed consent regulations for the PreVent and the PreVent 2 trials: Changes over time and during the COVID-19 pandemic 设计和实施社区咨询,为 PreVent 和 PreVent 2 试验中根据知情同意例外规定进行的研究提供咨询:随着时间推移和在 COVID-19 大流行期间的变化
IF 2.7 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Pub Date : 2024-04-27 DOI: 10.1177/17407745241243045
Tom Gugel, Karen Adams, Madelon Baranoski, N David Yanez, Michael Kampp, Tesheia Johnson, Ani Aydin, Elaine C Fajardo, Emily Sharp, Aartee Potnis, Chanel Johnson, Miriam M Treggiari
Introduction:Emergency clinical research has played an important role in improving outcomes for acutely ill patients. This is due in part to regulatory measures that allow Exception From Informed Consent (EFIC) trials. The Food and Drug Administration (FDA) requires sponsor-investigators to engage in community consultation and public disclosure activities prior to initiating an Exception From Informed Consent trial. Various approaches to community consultation and public disclosure have been described and adapted to local contexts and Institutional Review Board (IRB) interpretations. The COVID-19 pandemic has precluded the ability to engage local communities through direct, in-person public venues, requiring research teams to find alternative ways to inform communities about emergency research.Methods:The PreVent and PreVent 2 studies were two Exception From Informed Consent trials of emergency endotracheal intubation, conducted in one geographic location for the PreVent Study and in two geographic locations for the PreVent 2 Study. During the period of the two studies, there was a substantial shift in the methodological approach spanning across the periods before and after the pandemic from telephone, to in-person, to virtual settings.Results:During the 10 years of implementation of Exception From Informed Consent activities for the two PreVent trials, there was overall favorable public support for the concept of Exception From Informed Consent trials and for the importance of emergency clinical research. Community concerns were few and also did not differ much by method of contact. Attendance was higher with the implementation of virtual technology to reach members of the community, and overall feedback was more positive compared with telephone contacts or in-person events. However, the proportion of survey responses received after completion of the remote, live event was substantially lower, with a greater proportion of respondents having higher education levels. This suggests less active engagement after completion of the synchronous activity and potentially higher selection bias among respondents. Importantly, we found that engagement with local community leaders was a key component to develop appropriate plans to connect with the public.Conclusion:The PreVent experience illustrated operational advantages and disadvantages to community consultation conducted primarily by telephone, in-person events, or online activities. Approaches to enhance community acceptance included partnering with community leaders to optimize the communication strategies and trust building with the involvement of Institutional Review Board representatives during community meetings. Researchers might need to pivot from in-person planning to virtual techniques while maintaining the ability to engage with the public with two-way communication approaches. Due to less active engagement, and potential for selection bias in the responders, further research is needed to addr
导言:急诊临床研究在改善急症患者预后方面发挥了重要作用。这部分归功于允许知情同意例外(EFIC)试验的监管措施。美国食品和药物管理局(FDA)要求申办者-研究者在启动知情同意例外试验之前,必须开展社区咨询和公开披露活动。社区咨询和公开披露的方法多种多样,并根据当地情况和机构审查委员会 (IRB) 的解释进行了调整。方法:PreVent 和 PreVent 2 研究是两项紧急气管插管知情同意例外试验,PreVent 研究在一个地区进行,PreVent 2 研究在两个地区进行。结果:在两项 PreVent 试验的 "例外知情同意 "活动实施的 10 年间,公众对 "例外知情同意 "试验的概念和紧急临床研究的重要性总体上表示支持。社区关注的问题很少,而且联系方法也没有太大差别。采用虚拟技术联系社区成员的出席率更高,与电话联系或现场活动相比,总体反馈更为积极。不过,远程现场活动结束后收到的调查回复比例要低得多,受访者中受教育程度较高的比例更高。这表明,在完成同步活动后,受访者的参与积极性较低,可能存在较大的选择偏差。重要的是,我们发现与当地社区领袖的接触是制定与公众联系的适当计划的关键要素。结论:PreVent 的经验说明了主要通过电话、现场活动或在线活动进行社区咨询的操作优缺点。提高社区接受度的方法包括与社区领袖合作以优化沟通策略,以及在社区会议期间让机构审查委员会代表参与进来以建立信任。研究人员可能需要从现场规划转向虚拟技术,同时保持与公众进行双向交流的能力。由于参与的积极性较低,而且可能会出现选择偏差,因此需要进一步研究虚拟社区咨询和公开披露活动与现场活动相比的成本和效益。
{"title":"Design and implementation of community consultation for research conducted under exception from informed consent regulations for the PreVent and the PreVent 2 trials: Changes over time and during the COVID-19 pandemic","authors":"Tom Gugel, Karen Adams, Madelon Baranoski, N David Yanez, Michael Kampp, Tesheia Johnson, Ani Aydin, Elaine C Fajardo, Emily Sharp, Aartee Potnis, Chanel Johnson, Miriam M Treggiari","doi":"10.1177/17407745241243045","DOIUrl":"https://doi.org/10.1177/17407745241243045","url":null,"abstract":"Introduction:Emergency clinical research has played an important role in improving outcomes for acutely ill patients. This is due in part to regulatory measures that allow Exception From Informed Consent (EFIC) trials. The Food and Drug Administration (FDA) requires sponsor-investigators to engage in community consultation and public disclosure activities prior to initiating an Exception From Informed Consent trial. Various approaches to community consultation and public disclosure have been described and adapted to local contexts and Institutional Review Board (IRB) interpretations. The COVID-19 pandemic has precluded the ability to engage local communities through direct, in-person public venues, requiring research teams to find alternative ways to inform communities about emergency research.Methods:The PreVent and PreVent 2 studies were two Exception From Informed Consent trials of emergency endotracheal intubation, conducted in one geographic location for the PreVent Study and in two geographic locations for the PreVent 2 Study. During the period of the two studies, there was a substantial shift in the methodological approach spanning across the periods before and after the pandemic from telephone, to in-person, to virtual settings.Results:During the 10 years of implementation of Exception From Informed Consent activities for the two PreVent trials, there was overall favorable public support for the concept of Exception From Informed Consent trials and for the importance of emergency clinical research. Community concerns were few and also did not differ much by method of contact. Attendance was higher with the implementation of virtual technology to reach members of the community, and overall feedback was more positive compared with telephone contacts or in-person events. However, the proportion of survey responses received after completion of the remote, live event was substantially lower, with a greater proportion of respondents having higher education levels. This suggests less active engagement after completion of the synchronous activity and potentially higher selection bias among respondents. Importantly, we found that engagement with local community leaders was a key component to develop appropriate plans to connect with the public.Conclusion:The PreVent experience illustrated operational advantages and disadvantages to community consultation conducted primarily by telephone, in-person events, or online activities. Approaches to enhance community acceptance included partnering with community leaders to optimize the communication strategies and trust building with the involvement of Institutional Review Board representatives during community meetings. Researchers might need to pivot from in-person planning to virtual techniques while maintaining the ability to engage with the public with two-way communication approaches. Due to less active engagement, and potential for selection bias in the responders, further research is needed to addr","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":"133 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140812301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
期刊
Clinical Trials
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1