Securely sharing DSMB reports to speed decision making from multiple, concurrent, independent studies of similar treatments in COVID-19

Author:

Dilts Natalie A.ORCID,Harrell Frank E.,Lindsell Christopher J.ORCID,Nwosu Samuel,Stewart Thomas G.,Shotwell Matthew S.,Pulley Jill M.,Edwards Terri L.,Serdoz Emily ShefferORCID,Benhoff Katelyn,Bernard Gordon R.

Abstract

Abstract Introduction: As clinical trials were rapidly initiated in response to the COVID-19 pandemic, Data and Safety Monitoring Boards (DSMBs) faced unique challenges overseeing trials of therapies never tested in a disease not yet characterized. Traditionally, individual DSMBs do not interact or have the benefit of seeing data from other accruing trials for an aggregated analysis to meaningfully interpret safety signals of similar therapeutics. In response, we developed a compliant DSMB Coordination (DSMBc) framework to allow the DSMB from one study investigating the use of SARS-CoV-2 convalescent plasma to treat COVID-19 to review data from similar ongoing studies for the purpose of safety monitoring. Methods: The DSMBc process included engagement of DSMB chairs and board members, execution of contractual agreements, secure data acquisition, generation of harmonized reports utilizing statistical graphics, and secure report sharing with DSMB members. Detailed process maps, a secure portal for managing DSMB reports, and templates for data sharing and confidentiality agreements were developed. Results: Four trials participated. Data from one trial were successfully harmonized with that of an ongoing trial. Harmonized reports allowing for visualization and drill down into the data were presented to the ongoing trial’s DSMB. While DSMB deliberations are confidential, the Chair confirmed successful review of the harmonized report. Conclusion: It is feasible to coordinate DSMB reviews of multiple independent studies of a similar therapeutic in similar patient cohorts. The materials presented mitigate challenges to DSMBc and will help expand these initiatives so DSMBs may make more informed decisions with all available information.

Publisher

Cambridge University Press (CUP)

Subject

General Medicine

Reference25 articles.

1. 15. ClinicalTrials.gov. Convalescent Plasma to Limit SARS-CoV-2 Associated Complications (CSSC-004). ClinicalTrials.gov identifier: NCT04373460. May 4, 2020 [cited July 7, 2020]. (https://www.clinicaltrials.gov/ct2/show/NCT04373460)

2. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support

3. Data Safety Monitoring during Covid‐19: Keep On Keeping On

4. 3. Centers for Disease Control and Prevention. CDC COVID data tracker, 2020. (https://covid.cdc.gov/covid-data-tracker/#trends_totaldeaths)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3