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评估妊娠相关药物警戒病例报告中临床信息质量的新方法的验证: ConcePTION 项目。

Validation of a Novel Method to Assess the Clinical Quality of Information in Pregnancy-Related Pharmacovigilance Case Reports: A ConcePTION Project.

机构信息

Pharmacovigilance Centre Lareb, Goudsbloemvallei 7, 5237 MH, s-Hertogenbosch, The Netherlands.

Groningen Research Institute of Pharmacy, PharmacoTherapy, -Epidemiology and -Economics, University of Groningen, Groningen, The Netherlands.

出版信息

Drug Saf. 2024 Mar;47(3):261-270. doi: 10.1007/s40264-023-01389-y. Epub 2024 Jan 6.


DOI:10.1007/s40264-023-01389-y
PMID:38183608
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10874330/
Abstract

BACKGROUND: To assess the causal relationship between a medicinal product and a reported event, relevant information needs to be present. Information elements for assessing cases of exposure to medicinal products during pregnancy were predefined and used in a new tool to assess the quality of information. However, the extent in which the presence or absence of these predefined information elements is associated with the overall clinical quality of these cases, as evaluated by pharmacovigilance experts, remains uncertain. OBJECTIVE: We aimed to validate a novel method to assess the clinical quality of information in real-world pregnancy pharmacovigilance case reports. METHODS: The clinical quality of case reports regarding medicinal product exposure and pregnancy-related outcomes was appraised from spontaneous reports, literature, Teratology Information Services (UK and Switzerland), The Dutch Pregnancy Drug Register, the Gilenya pregnancy registry and the Enhanced PV programme of Novartis. Assessment was done by means of the novel standardised tool based on the presence and relevance of information, and by expert judgement. The novel tool was validated compared to the expert assessment as the gold standard expressed as the area under the receiver operating characteristic curves, after which the sensitivity and specificity were calculated using cross-tabulations. Inter-rater variability was determined by means of weighted Cohen's kappa. RESULTS: One hundred and eighty-six case reports were included. The clinical quality score as assessed by the novel method was divided into three categories with cut-off values of 45% (poor to intermediate) and 65% (intermediate to excellent). Sensitivity was 0.93 and 0.96 for poor to intermediate and intermediate to excellent, respectively. Specificity was respectively 0.52 and 0.73. Inter-rater variability was 0.65 (95% confidence interval 0.53-0.78) for the newly developed approach, and 0.40 (95% confidence interval 0.28-0.52) for the gold standard assessment. CONCLUSIONS: The tool described in this study using the presence and relevance of elements of information is the first designed, validated and standardised method for the assessment of the quality of information of case reports in pregnancy pharmacovigilance data. This method confers less inter-rater variability compared with a quality assessment by experts of pregnancy-related pharmacovigilance data.

摘要

背景:为了评估药品与报告事件之间的因果关系,需要提供相关信息。已预先定义了评估妊娠期间药物暴露病例的信息要素,并将其用于评估信息质量的新工具中。然而,这些预先定义的信息要素的存在或缺失与药物警戒专家评估的这些病例的整体临床质量之间的关联程度尚不确定。

目的:我们旨在验证一种评估真实世界妊娠药物警戒病例报告中信息临床质量的新方法。

方法:从自发报告、文献、致畸信息服务(英国和瑞士)、荷兰妊娠药物登记处、Gilenya 妊娠登记处和诺华增强药物警戒计划中评估与药物暴露和妊娠相关结局相关的病例报告的临床质量。评估是通过基于信息的存在和相关性的新型标准化工具以及专家判断进行的。将新工具与作为金标准的专家评估进行比较,通过接受者操作特征曲线下的面积来表示,然后使用交叉表计算灵敏度和特异性。通过加权 Cohen's kappa 确定组内变异系数。

结果:共纳入 186 例病例报告。新型方法评估的临床质量评分分为三个类别,截断值分别为 45%(差到中等)和 65%(中等到优秀)。灵敏度分别为差到中等和中等到优秀的 0.93 和 0.96。特异性分别为 0.52 和 0.73。新方法的组内变异系数为 0.65(95%置信区间为 0.53-0.78),金标准评估的组内变异系数为 0.40(95%置信区间为 0.28-0.52)。

结论:本研究中使用信息要素的存在和相关性描述的工具是第一个专门设计、验证和标准化的方法,用于评估妊娠药物警戒数据中病例报告的信息质量。与专家对妊娠相关药物警戒数据的质量评估相比,该方法的组内变异系数更小。

相似文献

[1]
Validation of a Novel Method to Assess the Clinical Quality of Information in Pregnancy-Related Pharmacovigilance Case Reports: A ConcePTION Project.

Drug Saf. 2024-3

[2]
Comparison of three methods (consensual expert judgement, algorithmic and probabilistic approaches) of causality assessment of adverse drug reactions: an assessment using reports made to a French pharmacovigilance centre.

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[3]
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Cochrane Database Syst Rev. 2022-2-1

[4]
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[5]
Comparison of three methods (an updated logistic probabilistic method, the Naranjo and Liverpool algorithms) for the evaluation of routine pharmacovigilance case reports using consensual expert judgement as reference.

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[6]
Validation and Reproducibility of the Updated French Causality Assessment Method: an Evaluation by Pharmacovigilance Centres & Pharmaceutical Companies.

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[7]
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[8]
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[9]
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[10]
Comparison of different methods for causality assessment of adverse drug reactions.

Int J Clin Pharm. 2018-8

引用本文的文献

[1]
Quality of Clinical Information in Pregnancy Pharmacovigilance Data Sources-A Contribution of the ConcePTION Project.

Pharmacoepidemiol Drug Saf. 2025-7

[2]
Uncovering Pregnancy Exposures in Pharmacovigilance Case Report Databases: A Comprehensive Evaluation of the VigiBase Pregnancy Algorithm.

Drug Saf. 2025-6-23

本文引用的文献

[1]
An alternative to product-specific pregnancy registries? PRIM; PRegnancy outcomes Intensive Monitoring.

Reprod Toxicol. 2020-6

[2]
Evaluation of pregnancy outcomes in patients with multiple sclerosis after fingolimod exposure.

Ther Adv Neurol Disord. 2018-11-3

[3]
Aim and Design of pREGnant, the Dutch Pregnancy Drug Register.

Drug Saf. 2019-1

[4]
First experiences with a tool to measure the level of clinical information present in adverse drug reaction reports.

Expert Opin Drug Saf. 2018-2

[5]
The importance of pharmacoepidemiology in pregnancy-implications for safety.

Expert Opin Drug Saf. 2017-10

[6]
What is an ROC curve?

Emerg Med J. 2017-6

[7]
vigiGrade: a tool to identify well-documented individual case reports and highlight systematic data quality issues.

Drug Saf. 2014-1

[8]
How can the quality of medical data in pharmacovigilance, pharmacoepidemiology and clinical studies be guaranteed?

Therapie. 2013-8-28

[9]
Interrater reliability: the kappa statistic.

Biochem Med (Zagreb). 2012

[10]
Comparison of three methods (consensual expert judgement, algorithmic and probabilistic approaches) of causality assessment of adverse drug reactions: an assessment using reports made to a French pharmacovigilance centre.

Drug Saf. 2010-11-1

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