Assessing the impact of risk-based data monitoring on outcomes for a paediatric multicentre randomised controlled trial

Author:

Le Marsney Renate1,Johnson Kerry12ORCID,Chumbes Flores Jenipher3,Coetzer Shelley4,Darvas Jennifer5,Delzoppo Carmel67,Jolly Arielle3,Masterson Kate67ORCID,Sherring Claire4,Thomson Hannah3,Ergetu Endrias1,Gilholm Patricia1,Gibbons Kristen S1ORCID

Affiliation:

1. Children’s Intensive Care Research Program, Child Health Research Centre, The University of Queensland, South Brisbane, QLD, Australia

2. Paediatric Intensive Care Unit, Queensland Children’s Hospital, Children’s Health Queensland, Brisbane, QLD, Australia

3. Paediatric Intensive Care Unit, Perth Children’s Hospital, Perth, WA, Australia

4. Paediatric Intensive Care Unit, Starship Child Health, Auckland, New Zealand

5. Paediatric Intensive Care Unit, The Children’s Hospital at Westmead, Sydney, NSW, Australia

6. Paediatric Intensive Care Unit, Royal Children’s Hospital Melbourne, Melbourne, VIC, Australia

7. Murdoch Children’s Research Institute, Melbourne, VIC, Australia

Abstract

Background/Aims Regulatory guidelines recommend that sponsors develop a risk-based approach to monitoring clinical trials. However, there is a lack of evidence to guide the effective implementation of monitoring activities encompassed in this approach. The aim of this study was to assess the efficiency and impact of the risk-based monitoring approach used for a multicentre randomised controlled trial comparing treatments in paediatric patients undergoing cardiac bypass surgery. Methods This is a secondary analysis of data from a randomised controlled trial that implemented targeted source data verification as part of the risk-based monitoring approach. Monitoring duration and source to database error rates were calculated across the monitored trial dataset. The monitored and unmonitored trial dataset, and simulated trial datasets with differing degrees of source data verification and cohort sizes were compared for their effect on trial outcomes. Results In total, 106,749 critical data points across 1,282 participants were verified from source data either remotely or on-site during the trial. The total time spent monitoring was 365 hours, with a median (interquartile range) of 10 (7, 16) minutes per participant. An overall source to database error rate of 3.1% was found, and this did not differ between treatment groups. A low rate of error was found for all outcomes undergoing 100% source data verification, with the exception of two secondary outcomes with error rates >10%. Minimal variation in trial outcomes were found between the unmonitored and monitored datasets. Reduced degrees of source data verification and reduced cohort sizes assessed using simulated trial datasets had minimal impact on trial outcomes. Conclusions Targeted source data verification of data critical to trial outcomes, which carried with it a substantial time investment, did not have an impact on study outcomes in this trial. This evaluation of the cost-effectiveness of targeted source data verification contributes to the evidence-base regarding the context where reduced emphasis should be placed on source data verification as the foremost monitoring activity.

Funder

heartkids australia

Perth Children’s Hospital Foundation

national health and medical research council

green lane research and educational fund

Publisher

SAGE Publications

Reference34 articles.

1. Assessing the Gold Standard — Lessons from the History of RCTs

2. Monitoring clinical trials: a practical guide

3. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. ICH harmonised guideline: integrated addendum to ICH E6 (R1): guideline for good clinical practice E6 (R2), 2016, https://ichgcp.net/.

4. US Food & Drug Administration (FDA). Guidance for industry oversight of clinical investigations: a risk-based approach to monitoring, 2013, https://www.regulations.gov/document/FDA-2011-D-0597-0053.

5. Extended Risk-Based Monitoring Model, On-Demand Query-Driven Source Data Verification, and Their Economic Impact on Clinical Trial Operations

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