在芬兰使用国家注册的实用临床试验中,对严重不良事件进行实时监测的发展。

IF 3.2 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Clinical Epidemiology Pub Date : 2024-12-13 eCollection Date: 2024-01-01 DOI:10.2147/CLEP.S483034
Tuomo A Nieminen, Arto A Palmu, Raija Auvinen, Sangita Kulathinal, Kari Auranen, Ritva K Syrjänen, Heta Nieminen, Tamala Mallett Moore, Stephanie Pepin, Jukka Jokinen
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引用次数: 0

摘要

目的:我们为一项大剂量四价流感疫苗(QIV-HD)的大型实用临床试验开发了一种混合安全性监测方法,使用主动和被动数据收集方法。在这里,我们提出了基于被动登记的严重不良事件(SAE)监测的方法和结果,在试验期间取代了传统的SAE报告。患者和方法:该试验招募了33,000多名老年人,其中50%接受了QIV-HD疫苗,其余接受了标准剂量疫苗(QIV-SD)作为对照疫苗。我们从国家登记中收集疫苗接种后6个月内所有急性住院的诊断。在试验的盲法阶段,我们采用队列研究设计,比较试验人群和试验外接种QIV-SD的老年人之间1811例ICD10诊断组(SAE类别)的发病率,无论是在研究期间还是之前的流感季节。基于实时概率比较,我们标记了试验人群中发生率较高的SAE类别,然后评估了每个标记类别与试验干预之间可能的因果关系。结果:我们的新型安全监测方法提供了信息,我们可以在试验期间实时评估这些信息。试验参与者经历了1217例与SAE相关的住院治疗,其中941例患者。在研究过程中,我们标记了10种SAE类别以进行进一步分析,但基于进一步的数据回顾,没有一种与疫苗接种存在因果关系的有力证据。结论:通过基于登记的随访,利用被动数据收集和人群水平比较,在实用的疫苗试验中可以实时检测和评估安全性信号。与传统的安全随访方法相比,该方法可能更加全面、客观和资源有效。
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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Development of Real-Time Surveillance for Serious Adverse Events in a Pragmatic Clinical Trial Using National Registers in Finland.

Purpose: We developed a hybrid safety surveillance approach for a large, pragmatic clinical trial of a high-dose quadrivalent influenza vaccine (QIV-HD), using both active and passive data collection methods. Here, we present the methods and results for the passive register-based surveillance of serious adverse events (SAEs), which replaced conventional SAE reporting during the trial.

Patients and methods: The trial recruited over 33,000 older adults of whom 50% received the QIV-HD while the rest received a standard-dose vaccine (QIV-SD) as a control vaccine. We collected diagnoses related to all acute hospitalizations during the six months following vaccination from national registers. During the blinded phase of the trial, we utilized a cohort study design and compared the incidences of 1811 ICD10 diagnosis groups (SAE categories) between the trial population and older adults vaccinated with the QIV-SD outside the trial, either during the study or the previous influenza season. Based on a real-time probabilistic comparison, we flagged SAE categories with higher incidence in the trial population and then evaluated possible causal associations between each flagged category and the trial intervention.

Results: Our novel approach to safety surveillance provided information, which we could evaluate in real-time during the trial. The trial participants experienced 1217 hospitalizations related to any SAE categories, contributed by 941 patients. We flagged 10 SAE categories for further analysis during the study but based on further data review, none presented strong evidence of causality with vaccination.

Conclusion: Safety signals can be detected and evaluated in real-time during a pragmatic vaccine trial with register-based follow-up, utilizing passive data collection and population level comparison. Compared to conventional methods of safety follow-up, this method is likely to be more comprehensive, objective and resource effective.

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来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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