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Identifying multiple sclerosis in women of childbearing age in six European countries: a contribution from the ConcePTION project

Marie Beslay Orcid Logo, Yvonne Geissbühler, Anna-Belle Beau, Davide Messina, Justine Benevent, Elisa Ballardini, Laia Barrachina-Bonet, Clara Cavero-Carbonell, Alex Coldea, Laura García-Villodre, Anja Geldhof, Rosa Gini, Kerstin Hellwig, Sue Jordan, Maarit K. Leinonen, Sandra Lopez-Leon, Marco Manfrini, Visa Martikainen, Vera R. Mitter, Amanda J. Neville, Hedvig Nordeng, Aurora Puccini, Sandra Vukusic, Joan K. Morris, Christine Damase-Michel

European Journal of Epidemiology

Swansea University Authors: Alex Coldea, Sue Jordan

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DOI (Published version): 10.1007/s10654-025-01264-3

Abstract

Prevalence of Multiple Sclerosis (MS) has increased over the last decades, primarily among women of childbearing age. Several algorithms for identifying MS have been described in the literature, providing heterogeneous prevalence estimates. We compared five algorithms to identify MS in women of chil...

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Published in: European Journal of Epidemiology
ISSN: 0393-2990 1573-7284
Published: Springer Science and Business Media LLC 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa70072
Abstract: Prevalence of Multiple Sclerosis (MS) has increased over the last decades, primarily among women of childbearing age. Several algorithms for identifying MS have been described in the literature, providing heterogeneous prevalence estimates. We compared five algorithms to identify MS in women of childbearing age and estimated MS prevalence by time period and age-group. The study population included women aged 15 to 49 years-old between 2005 and 2019, from three data sources including all women (from Italy, Norway, and Wales), and three including pregnant women only (from France, Finland, and Spain; data collected around pregnancy). Five algorithms were tested: MS1 to MS3 combined MS diagnoses and MS-medicine prescriptions/dispensations, requiring 1, 2, or 3 occurrences, respectively; MS4 and MS5 used only MS diagnoses, requiring at least 2 occurrences (MS4 allowed just 1 if diagnosis was from inpatient care). In 2015-2019, MS prevalence based on MS1 ranged from 109 to 359 per 100,000 women: 109 in France, 121 in Spain, 195 in Wales, 232 in Finland, 264 in Italy, and 359 in Norway. More restrictive algorithms led to greater disparity, with MS3 ranging from 53 in Spain to 325 in Norway, and MS5 from 21 in France to 345 in Norway. All algorithms showed expected prevalence trends by time and age among women of childbearing age, though lower than in the literature. Overall, MS1 provided prevalence estimates most closely aligned with existing literature. This study offers key insights into choosing algorithms for identifying MS in women of childbearing age and in pregnant women.
Keywords: Disease identification algorithms; Multiple sclerosis; Prevalence; Administrative healthcare data sources; Women of childbearing age; Pregnant women
College: Faculty of Medicine, Health and Life Sciences
Funders: Open access funding provided by Université de Toulouse. The ConcePTION project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 821520. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA. The research leading to these results was conducted as part of the ConcePTION consortium.

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