Niels S Vermeer1,2, Hans C Ebbers1, Sabine M J M Straus2,3, Hubert G M Leufkens1,2, Toine C G Egberts1,4, Marie L De Bruin1,2. 1. Utrecht Institute for Pharmaceutical Sciences (UIPS), Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, The Netherlands. 2. Medicines Evaluation Board, Utrecht, The Netherlands. 3. Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands. 4. Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht, The Netherlands.
Abstract
BACKGROUND AND OBJECTIVE: The availability of accurate product-specific exposure information is essential in the pharmacovigilance of biologicals, because differences in the safety profile may emerge between products containing the same active substance. In spontaneous adverse drug reaction (ADR) reports, drug exposure may, however, be misclassified, that is, attributed to the incorrect product. The aim of this study was to explore the effect of exposure misclassification on the time to detection of product-specific risks in spontaneous reporting systems. METHODS: We used data simulations to explore the effect of exposure misclassification. We simulated an active substance-specific subset of a spontaneous reporting system and used the proportional reporting ratio for signal detection. The effect of exposure misclassification was evaluated in three test cases representing product-specific ADRs that may occur for biologicals and studied in relative terms by varying the model parameters (market share and relative risk). RESULTS: We found that exposure misclassification results in the largest delay in identification of risks that have a weak association (relative risk < 2 or 3) with the product of interest and in situations where the product associated with the unique risk has a large (>50%) market share. The absolute public health impact of exposure misclassification, in terms of cases/time to detection, varied considerably across the test cases. CONCLUSION: Exposure misclassification in ADR reports may result in a delayed detection of product-specific risks, particularly in the detection of weak drug-event associations. Our findings can help inform the future implementation and refinement of product-specific and batch-specific signal detection procedures.
BACKGROUND AND OBJECTIVE: The availability of accurate product-specific exposure information is essential in the pharmacovigilance of biologicals, because differences in the safety profile may emerge between products containing the same active substance. In spontaneous adverse drug reaction (ADR) reports, drug exposure may, however, be misclassified, that is, attributed to the incorrect product. The aim of this study was to explore the effect of exposure misclassification on the time to detection of product-specific risks in spontaneous reporting systems. METHODS: We used data simulations to explore the effect of exposure misclassification. We simulated an active substance-specific subset of a spontaneous reporting system and used the proportional reporting ratio for signal detection. The effect of exposure misclassification was evaluated in three test cases representing product-specific ADRs that may occur for biologicals and studied in relative terms by varying the model parameters (market share and relative risk). RESULTS: We found that exposure misclassification results in the largest delay in identification of risks that have a weak association (relative risk < 2 or 3) with the product of interest and in situations where the product associated with the unique risk has a large (>50%) market share. The absolute public health impact of exposure misclassification, in terms of cases/time to detection, varied considerably across the test cases. CONCLUSION: Exposure misclassification in ADR reports may result in a delayed detection of product-specific risks, particularly in the detection of weak drug-event associations. Our findings can help inform the future implementation and refinement of product-specific and batch-specific signal detection procedures.
Authors: Luis Correia Pinheiro; Thijs J Giezen; Elena Wolff-Holz; Martina Weise; Andrea Laslop; Ana Hidalgo-Simon Journal: Clin Pharmacol Ther Date: 2021-09-26 Impact factor: 6.903