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临床试验现场绩效指标工具的开发:一项研究方案。

Development of the clinical trial site performance metrics instrument: A study protocol.

作者信息

Bozzetti Mattia, Caruso Rosario, Soncini Silvia, Guberti Monica

机构信息

Department of Biomedicine and Prevention, University of Rome, Tor Vergata, Italy.

Health Professions Research and Development Unit, IRCCS Policlinico San Donato, San Donato Milanese, Italy.

出版信息

MethodsX. 2025 Jan 8;14:103165. doi: 10.1016/j.mex.2025.103165. eCollection 2025 Jun.

DOI:10.1016/j.mex.2025.103165
PMID:39897650
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11782877/
Abstract

Clinical trials (CTs) are essential for medical advancements, yet their increasing complexity and cost demand improved efficiency in trial management. One major challenge in multicenter studies is the inconsistency in evaluating site performance. This study aims to develop and validate a Clinical Trial Site Performance Measure (CT-SPM) to assess "good performance" across trials. The tool will be tested and refined through psychometric analysis, resulting in both a comprehensive scale and a short form for universal application. The study is conducted in three phases: Phase 1 involves metric selection through expert consensus; Phase 2 focuses on psychometric testing to evaluate the reliability and validity of the instrument; and Phase 3 defines a cut-off for "good performance" using statistical models. This protocol aims to standardize site performance evaluation, potentially reducing research costs and enhancing trial quality.•The study develops and validates a Clinical Trial Site Performance Measure (CT-SPM) using expert consensus and psychometric testing.•A comprehensive and short-form tool will be created to evaluate site performance in multicenter clinical trials.•A cut-off for "good performance" will be established using statistical models, facilitating consistent and efficient site evaluations.

摘要

临床试验对于医学进步至关重要,然而其日益增加的复杂性和成本要求提高试验管理效率。多中心研究中的一个主要挑战是评估研究点表现时缺乏一致性。本研究旨在开发并验证一种临床试验研究点表现衡量方法(CT-SPM),以评估各试验中的“良好表现”。该工具将通过心理测量分析进行测试和完善,从而得出一个全面量表和一个便于广泛应用的简化版。本研究分三个阶段进行:第一阶段通过专家共识选择指标;第二阶段专注于心理测量测试,以评估该工具的信度和效度;第三阶段使用统计模型确定“良好表现”的临界值。本方案旨在使研究点表现评估标准化,有可能降低研究成本并提高试验质量。

• 本研究通过专家共识和心理测量测试开发并验证一种临床试验研究点表现衡量方法(CT-SPM)。

• 将创建一个全面且简化的工具,以评估多中心临床试验中的研究点表现。

• 将使用统计模型确定“良好表现”的临界值,便于进行一致且高效的研究点评估。

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Semin Oncol Nurs. 2024 Oct;40(5):151711. doi: 10.1016/j.soncn.2024.151711. Epub 2024 Aug 17.
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Envisioning clinical trials as complex interventions.
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Cancer. 2022 Sep 1;128(17):3145-3151. doi: 10.1002/cncr.34357. Epub 2022 Jun 29.
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Machine Learning Prediction of Clinical Trial Operational Efficiency.机器学习预测临床试验运营效率。
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