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Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design
BACKGROUND: Clinical research nurses are a key part of the clinical trial team but typically get involved later in the trial, usually during recruitment. The purpose of our study was to establish if CRNs who read the trial protocol can predict the performance of the trial. METHODS: We randomly selec...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353190/ https://www.ncbi.nlm.nih.gov/pubmed/37464255 http://dx.doi.org/10.1186/s13063-023-07504-9 |
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author | Shiely, Frances Murphy, Danielle Millar, Seán R. |
author_facet | Shiely, Frances Murphy, Danielle Millar, Seán R. |
author_sort | Shiely, Frances |
collection | PubMed |
description | BACKGROUND: Clinical research nurses are a key part of the clinical trial team but typically get involved later in the trial, usually during recruitment. The purpose of our study was to establish if CRNs who read the trial protocol can predict the performance of the trial. METHODS: We randomly selected 18 trial protocols with three statuses, terminated, withdrawn, and completed, from ClinicalTrials.gov, between 2014 and 2018 inclusive. We gave the protocols to five CRNs, asked them to make a judgement and provide a reason for that judgement (via a 12-item questionnaire) on the status of the trial (terminated, withdrawn or completed), if the trial met its recruitment target, if it recruited on time, and if it retained its participants. We also asked if it was likely a CRN was involved in the design of the trial. The CRNs were blinded to the study outcomes, did not receive any training on how to read a protocol and were prohibited from using/abstained from using the internet while completing the task. RESULTS: Twenty-three questionnaires on 23 trial protocols (18 different trials) were completed by 5 CRNs. The CRNs correctly predicted the trial status 48%, 95% CI: 29–67% (11/23) of the time; successful/unsuccessful recruitment 74%, 95% CI: 54–87% (17/23) of the time; on-time recruitment 70%, 95% CI: 49–84% (16/23) of the time; and participant retention 52%, 95% CI: 33–71% (12/23). CRNs identified 100% (sensitivity) of sites that hit their target and 63%, 95% CI: 36–84% (specificity) of sites that missed their target. CONCLUSIONS: CRNs are very good judges of trial recruitment and site performance issues and are a vital part of the clinical trial team. Taken with the ESP (Estimating Site Performance) study, we have made a strong case for broadening the trial team at the trial design stage. Early engagement of a broad skillset can potentially offset problems of recruitment, retention and trial failure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-023-07504-9. |
format | Online Article Text |
id | pubmed-10353190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103531902023-07-19 Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design Shiely, Frances Murphy, Danielle Millar, Seán R. Trials Research BACKGROUND: Clinical research nurses are a key part of the clinical trial team but typically get involved later in the trial, usually during recruitment. The purpose of our study was to establish if CRNs who read the trial protocol can predict the performance of the trial. METHODS: We randomly selected 18 trial protocols with three statuses, terminated, withdrawn, and completed, from ClinicalTrials.gov, between 2014 and 2018 inclusive. We gave the protocols to five CRNs, asked them to make a judgement and provide a reason for that judgement (via a 12-item questionnaire) on the status of the trial (terminated, withdrawn or completed), if the trial met its recruitment target, if it recruited on time, and if it retained its participants. We also asked if it was likely a CRN was involved in the design of the trial. The CRNs were blinded to the study outcomes, did not receive any training on how to read a protocol and were prohibited from using/abstained from using the internet while completing the task. RESULTS: Twenty-three questionnaires on 23 trial protocols (18 different trials) were completed by 5 CRNs. The CRNs correctly predicted the trial status 48%, 95% CI: 29–67% (11/23) of the time; successful/unsuccessful recruitment 74%, 95% CI: 54–87% (17/23) of the time; on-time recruitment 70%, 95% CI: 49–84% (16/23) of the time; and participant retention 52%, 95% CI: 33–71% (12/23). CRNs identified 100% (sensitivity) of sites that hit their target and 63%, 95% CI: 36–84% (specificity) of sites that missed their target. CONCLUSIONS: CRNs are very good judges of trial recruitment and site performance issues and are a vital part of the clinical trial team. Taken with the ESP (Estimating Site Performance) study, we have made a strong case for broadening the trial team at the trial design stage. Early engagement of a broad skillset can potentially offset problems of recruitment, retention and trial failure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-023-07504-9. BioMed Central 2023-07-18 /pmc/articles/PMC10353190/ /pubmed/37464255 http://dx.doi.org/10.1186/s13063-023-07504-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Shiely, Frances Murphy, Danielle Millar, Seán R. Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
title | Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
title_full | Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
title_fullStr | Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
title_full_unstemmed | Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
title_short | Clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
title_sort | clinical research nurse predictions of trial failure, recruitment and retention: a case for their early inclusion in trial design |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353190/ https://www.ncbi.nlm.nih.gov/pubmed/37464255 http://dx.doi.org/10.1186/s13063-023-07504-9 |
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