A Pilot Study on the Collection of Adverse Event Data from the Patient Using an Electronic Platform in a Cancer Clinical Trial Unit.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Minna Grahvendy, Bena Brown, Laurelie R Wishart
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引用次数: 0

Abstract

Background and objective: Accurate and robust adverse event (AE) data collection is crucial in cancer clinical trials to ensure participant safety. Frameworks have been developed to facilitate the collection of AE data and now the traditional workflows are facing renewal to include patient-reported data, improving completeness of AE data. We explored one of these workflows in a cancer clinical trial unit.

Methods: The study was a single-site study conducted at a tertiary hospital located in Australia. Patients consenting to a clinical trial were eligible for inclusion in this study. Participants used an electronic platform-My Health My Way (MHMW)-to report their symptomatic data weekly for 24 weeks. A symptom list was included within the platform, along with a free text field. Data reported via the platform was compared with data recorded in the patient's medical chart. Time taken to compile data from each source was recorded, along with missing data points. Agreement between patient-reported data and data recorded in the medical notes was assessed using Kappa and Gwet's AC1; time taken to compile data and missing data points were assessed using a Wilcoxon signed rank test.

Results: Low agreement was found between patient- and clinician-reported data (- 0.482 and - 0.159 by Kappa and Gwet's AC1 respectively). Only 127 (30%) of the total 428 AEs were reported by both MHMW and medical notes. Patients reported higher rates of symptoms from the symptom list, while clinicians reported higher rates of symptoms outside of the symptom list. Time taken to compile the data from MHMW was significantly less than that taken to review medical notes (2.19 min versus 5.73 min respectively; P <  0.001). There were significantly less missing data points from the MHMW data compared with the medical notes (1.4 versus 7.8; P < 0.001).

Conclusions: This study confirms previous reports that patient- and clinician-reported adverse event data show low agreement. This study also shows that clinical trial sites could significantly reduce the work performed by research staff in the collection of adverse event data by implementing an electronic, patient-reported platform.

癌症临床试验单位使用电子平台收集患者不良事件数据的试点研究。
背景和目的:在癌症临床试验中,准确、可靠的不良事件(AE)数据收集对确保参与者的安全至关重要。为方便收集 AE 数据,人们开发了一些框架,现在传统的工作流程正面临更新,以纳入患者报告的数据,从而提高 AE 数据的完整性。我们在一个癌症临床试验单位探索了其中一个工作流程:本研究是在澳大利亚一家三级医院进行的单点研究。同意参加临床试验的患者有资格加入本研究。参与者使用电子平台 "我的健康我做主(MHMW)"报告症状数据,每周一次,持续24周。该平台包含一个症状列表和一个自由文本字段。通过平台报告的数据与患者病历中记录的数据进行比较。记录了从每个来源收集数据所需的时间以及缺失的数据点。使用 Kappa 和 Gwet's AC1 评估患者报告的数据与病历记录的数据之间的一致性;使用 Wilcoxon 签名秩检验评估整理数据所花费的时间和缺失的数据点:患者和临床医生报告的数据之间的一致性较低(根据 Kappa 和 Gwet's AC1 分别为 - 0.482 和 - 0.159)。在总共 428 例 AE 中,只有 127 例(30%)同时由 MHMW 和医疗记录报告。患者报告的症状清单中的症状比例较高,而临床医生报告的症状清单之外的症状比例较高。汇编 MHMW 数据所需的时间明显少于查阅病历所需的时间(分别为 2.19 分钟和 5.73 分钟;P 结论:本研究证实了之前的报告,即患者和临床医生报告的不良事件数据显示出较低的一致性。本研究还表明,临床试验机构可通过实施患者报告电子平台,大幅减少研究人员收集不良事件数据的工作量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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