Evidence map›Paper›PMID 40679704›Full record

ArticleEuropean journal of epidemiology2025

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

Marie Beslay, Yvonne Geissbühler, Anna-Belle Beau, Davide Messina, Justine Benevent, Elisa Ballardini, Laia Barrachina-Bonet, Clara Cavero-Carbonell, Alex Coldea, Laura García-Villodre and 15 more

Abstract read
In one paragraph

Article in European journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Marie BeslayCERPOP-SPHERE Team, Toulouse University Hospital, Inserm UMR 1295, Toulouse University, Toulouse, France. beslay.m@chu-toulouse.fr.ORCID http://orcid.org/0000-0002-5153-1747
Yvonne GeissbühlerEvidence Generation, Novartis Pharma AG, Basel, Switzerland.
Anna-Belle BeauCERPOP-SPHERE Team, Toulouse University Hospital, Inserm UMR 1295, Toulouse University, Toulouse, France.
Davide MessinaARS Toscana, Florence, Italy.
Justine BeneventCERPOP-SPHERE Team, Toulouse University Hospital, Inserm UMR 1295, Toulouse University, Toulouse, France.
Elisa BallardiniNeonatal Intensive Care Unit, Department of Medical Sciences, Centre for Clinical and Epidemiological Research, Emilia Romagna Registry of Birth Defects, University Hospital of Ferrara, University of Ferrara, Ferrara, Italy.
Laia Barrachina-BonetRare Disease Research Unit, Foundation for Promotion of Health and Biomedical Research of Valencian Region (FISABIO), Valencia, Spain.
Clara Cavero-CarbonellRare Disease Research Unit, Foundation for Promotion of Health and Biomedical Research of Valencian Region (FISABIO), Valencia, Spain.
Alex ColdeaFaculty of Medicine, Health and Life Sciences, Swansea University, Swansea, Wales.
Laura García-VillodreRare Disease Research Unit, Foundation for Promotion of Health and Biomedical Research of Valencian Region (FISABIO), Valencia, Spain.
Anja GeldhofJanssen Biologics B.V, Leiden, Netherlands.
Rosa GiniARS Toscana, Florence, Italy.
Kerstin HellwigDepartment of Neurology, St. Josef-Hospital, Ruhr-University, Bochum, Germany.
Sue JordanFaculty of Medicine, Health and Life Sciences, Swansea University, Swansea, Wales.
Maarit K LeinonenDepartment of Data and Analytics, Finnish Institute for Health and Welfare, Helsinki, Finland.
Sandra Lopez-LeonNovartis Pharmaceuticals Corporation, East Hanover, USA.
Marco ManfriniDepartment of Medical Sciences, Centre for Clinical and Epidemiological Research, Ferrara University, Ferrara, Italy.
Visa MartikainenDepartment of Data and Analytics, Finnish Institute for Health and Welfare, Helsinki, Finland.
Vera R MitterSchool of Health Professionals, Midwifery Department, Bern University of Applied Sciences, Bern, Switzerland.
Amanda J NevilleIMER Registry (Emilia Romagna Registry of Birth Defects), University Hospital of Ferrara, Ferrara, Italy.
Hedvig NordengPharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
Aurora PucciniEmilia-Romagna Regional Center of Pharmacovigilance, Bologna, Italy.
Sandra VukusicHospices Civils de Lyon, Hôpital Pierre Wertheimer, Université Claude Bernard Lyon-I, Research on Healthcare Performance, INSERM U1290, Bron, Lyon, France.
Joan K MorrisCity St George's, Population Health Research Institute, University of London, London, UK.
Christine Damase-MichelCERPOP-SPHERE Team, Toulouse University Hospital, Inserm UMR 1295, Toulouse University, Toulouse, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsMultiple SclerosisAdolescentAdultEuropeFemaleFinlandHumansMiddle AgedPregnancyPrevalenceYoung AdultAdministrative healthcare data sourcesDdisease identification algorithmsMultiple sclerosisPregnant women.PrevalenceWomen of childbearing age

Identifiers

PMID40679704
PMCPMC12374901

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.