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. 2025 Jul;34(7):e70182.
doi: 10.1002/pds.70182.

Quality of Clinical Information in Pregnancy Pharmacovigilance Data Sources-A Contribution of the ConcePTION Project

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Quality of Clinical Information in Pregnancy Pharmacovigilance Data Sources-A Contribution of the ConcePTION Project

Yrea R J van Rijt-Weetink et al. Pharmacoepidemiol Drug Saf. 2025 Jul.

Abstract

Purpose: Good documentation of adverse events related to medicines is essential for the assessment of safety signals. Information on the clinical quality of primary pregnancy safety data sources is lacking. The objective of this study was to assess the differences in clinical quality of various sources of primary pregnancy pharmacovigilance (PV) data.

Methods: Fifty reports of exposures to medicines during pregnancy were collected from: spontaneous and literature reports from EudraVigilance, European Network of Teratology Information Services (ENTIS), the Dutch Pregnancy Drug Register, enhanced PV programmes (EPV), and patient support programmes (PSP). Reports were standardized and anonymized, after which their clinical quality was assessed. Mean scores per source were compared using ANOVA (analysis of variance test).

Results: Mean clinical quality scores were 89.0% (SD 10.1%) for the Dutch Pregnancy Drug Register, 77.1% (SD 13.3%) for TIS, 64.7% (SD 20.5%) for EPVs, 49.5% (SD 16.2%) for PSPs, 40.9% (SD 21.6%) for spontaneous reports, and 38.6% (SD 18.0%) for literature reports. All were statistically significantly different (p ≤ 0.05) except for spontaneous versus literature reports (mean difference 2.2%, p = 0.99) and spontaneous reports versus reports from PSPs (-8.6%, p = 0.14).

Conclusions: For data sources specifically designed for pregnancy data collection, the clinical quality of information generally outweighed sources designed to capture general safety information. EPV methods showed better scores for clinical quality compared to spontaneous reporting data for pregnancy PV.

Keywords: pharmacovigilance; pregnancy; quality.

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Conflict of interest statement

David J. Lewis is a full‐time employee of Novartis Pharma AG and holds shares in Alcon, GlaxoSmithKline, Novartis, and Sandoz. Laura M. Yates provided consultancy for Sanofi Genzyme South Africa on two occasions in 2021 relating to genetic testing in Gaucher's Disease (April 2021, Advisory Board presentation) and a conference lecture on genetic testing in cardiac clinics (September 2021). The other authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Boxplots of clinical quality per data source, expressed as percentage of present and relevant over relevant elements of information. The boxplots consist of the median quality score (bold line), interquartile range (box), minimum to maximum quality score (whiskers) and if applicable outliers (dots). Vertical lines at the cut‐off values between categories are shown; < 45% poor clinical quality, 45%–65% intermediate clinical quality, and ≥ 65% excellent clinical quality. PV, pharmacovigilance.

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