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

Yrea R. J. Rijt-Weetink (), Toine C. G. Egberts (), Florence P. A. M. Hunsel (), David J. Lewis (), Laura M. Yates (), Ursula Winterfeld () and Eugène P. Puijenbroek ()
Additional contact information
Yrea R. J. Rijt-Weetink: Pharmacovigilance Centre Lareb
Toine C. G. Egberts: Utrecht University
Florence P. A. M. Hunsel: Pharmacovigilance Centre Lareb
David J. Lewis: Novartis Pharma GmbH
Laura M. Yates: University of Kwazulu-Natal, KRISP
Ursula Winterfeld: Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne
Eugène P. Puijenbroek: Pharmacovigilance Centre Lareb

Drug Safety, 2024, vol. 47, issue 3, No 7, 270 pages

Abstract: 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.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40264-023-01389-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:drugsa:v:47:y:2024:i:3:d:10.1007_s40264-023-01389-y

Ordering information: This journal article can be ordered from
http://www.springer.com/adis/journal/40264

DOI: 10.1007/s40264-023-01389-y

Access Statistics for this article

Drug Safety is currently edited by Nitin Joshi

More articles in Drug Safety from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().