Evidence map›Paper›PMID 40742695›Full record

ArticleEuropean journal of epidemiology2026

Methods of estimating prevalence of multiple sclerosis in six European healthcare data sources: a contribution from the ConcePTION project.

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

Abstract read
In one paragraph

Article in European journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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
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.
Christine Damase-MichelCERPOP-SPHERE Team, Toulouse University Hospital, Inserm UMR 1295, Toulouse University, Toulouse, France.
Yvonne GeissbühlerEvidence Generation, Novartis Pharma AG, Basel, Switzerland.
Joan K MorrisPopulation Health Research Institute, City St George's , University of London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is a chronic autoimmune condition primarily affecting women and often diagnosed during childbearing years. This study assessed the impact of the lookback period and calculation method on MS prevalence in three healthcare data sources including women of childbearing age (from Italy, Norway and Wales) and three data sources including pregnant women (from France, Finland and Spain). Women aged 15 to 49 years from 2005 to 2019 were included, data from pregnant women were collected around the pregnancy period. MS cases were identified based on at least one MS diagnosis or one dispensation for an MS-specific medication. All data sources provided inpatient diagnoses and medication data; outpatient diagnoses were available in Norway and Finland, and primary care diagnoses in Norway, Finland and Wales. We assessed MS case detection rate by lookback period, and compared three methods for estimating yearly MS prevalence: period prevalence (PP), average point prevalence (APP) and person-time prevalence (PTP). The estimated lookback periods to identify 95% of MS cases ranged from 6 to 9 years. APP and PTP provided lower prevalence estimates than PP, especially when the lookback to identify MS was short. In women of childbearing age, MS prevalence increased over time with all calculation methods and the highest MS prevalence was observed in Norway (PP of 402 per 100,000 in 2019). Finland showed the highest MS prevalence in pregnant women (PP of 218 per 100,000 in 2018). This study highlights the importance of sufficient lookback and available data to accurately estimate MS prevalence.

Indexed as

Multiple SclerosisAdolescentAdultEuropeFemaleFinlandHumansMiddle AgedNorwayPregnancyPrevalenceYoung AdultAdministrative healthcare data sourcesLookbackMultiple sclerosisPregnant womenPrevalence calculation methodsWomen of childbearing age

Identifiers

PMID40742695
PMCPMC13612616

What OpenQuestion holds

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Registered trials

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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.