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 Methods We randomly selected 18 trial protocols with three statuses, terminated, withdrawn, and completed, from ClinicalTrials.gov, between 2014 and 2018 inclusive.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judgement and provide a reason for that judgement (via a 12-item questionnaire) on the status of the trial (terminated, withdrawn or completed), if the trial met its recruitment target, if it recruited on time, and if it retained its participants.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..

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:24

Enthalten in:

Trials - 24(2023), 1 vom: 18. Juli

Sprache:

Englisch

Beteiligte Personen:

Shiely, Frances [VerfasserIn]
Murphy, Danielle [VerfasserIn]
Millar, Seán R. [VerfasserIn]

Links:

Volltext [kostenfrei]

BKL:

44.00 / Medizin: Allgemeines / Medizin: Allgemeines

Themen:

Clinical research nurse
Recruitment
Retention
Trial methodology

Anmerkungen:

© The Author(s) 2023

doi:

10.1186/s13063-023-07504-9

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

OLC2144539642

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