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Comparison of 2 Methods for Estimating Multiple Sclerosis-Related Mortality. | LitMetric

Comparison of 2 Methods for Estimating Multiple Sclerosis-Related Mortality.

Neurology

From the Université de Lyon (F.R., S.V.), Université Claude Bernard Lyon 1; Service de Neurologie, Sclérose en Plaques, Pathologies de la Myéline et Neuroinflammation (F.R., S.V.), Hôpital Neurologique Pierre Wertheimer, Hospices Civils de Lyon, Bron; Observatoire Français de la Sclérose en Plaques (F.R., S.V.), Centre de Recherche en Neurosciences de Lyon, INSERM 1028 et CNRS UMR 5292; EUGENE DEVIC EDMUS Foundation Against Multiple Sclerosis (F.R., S.V.), State-Approved Foundation, Bron; Direction des Maladies non Transmissible et des Traumatismes (Z.U.), Santé Publique France, Saint-Maurice; Service de Biostatistique-Bioinformatique (Z.U., E.D., M.F., L.R.), Pôle Santé Publique, Hospices Civils de Lyon; Laboratoire de Biométrie et Biologie Evolutive UMR 5558 (E.D., M.F., L.R.), Université Lyon 1 and CNRS, Villeurbanne; Service de Neurologie (M.D.), Centre Hospitalier Régional et Universitaire de Nancy, Université de Lorraine, EA 4360 APEMAC, Vandoeuvre-Lès-Nancy; Neurology Department (E.L.P.), CRCSEP Rennes, Clinical Investigation Centre CIC-P 1414, Rennes University Hospital; Service de Neurologie (J.C.), CHU de Toulouse, Hôpital Pierre-Paul Riquet, CRC-SEP; Institut Toulousain des Maladies Infectieuses et Inflammatoires (Infinity) (J.C.), INSERM UMR 1291, CNRS UMR 5051, Université Toulouse III; Service de Neurologie (A.R.), CRC SEP, CHU de Bordeaux; U1215 INSERM (A.R.), Neurocentre Magendie, Université de Bordeaux; Service de Neurologie et Centre d'Investigation Clinique (J.D.S.), CHU de Strasbourg, INSERM 1434; Pôle des Neurosciences et de l'Appareil Locomoteur (H.Z.), CRC-SEP, Hôpital Roger Salengro, Université de Lille, Inserm U1172; CRC SEP (P.L.), Service de Neurologie, CHU de Montpellier; Service de Neurologie (G.D.), CRC-SEP Normandie, CHU de Caen, Université Normandie; Service de Neurologie (C.L.-F.), Neurologie Pasteur 2, CHU de Nice, Université Nice Cote d'Azur UR2CA-URRIS; Service de Neurologie (T.M.), CHU de Dijon; Service de Neurologie (D.A.L.), CHU Nantes; INSERM (D.A.L.), CIC 0004, CRTI-INSERM UMR U1064, Nantes; Service de Neurologie (E.B.), CHU de Besançon; Service de Neurologie (P.C.), CHU de Clermont-Ferrand, INSERM 1107 NeuroDol, Clermont-Ferrand; Aix Marseille University (J.P.), APHM, Hôpital de la Timone, Pôle de Neurosciences Cliniques, Service de Neurologie, CEMEREM; Service de Neurologie (E.T.), CHU de Nîmes; Institut de Génomique Fonctionnelle (E.T.), Université de Montpellier, CNRS, INSERM; Service de Neurologie (O.H.), CH de Poissy; Service de Neurologie (J.-P.C.), Hôpital Nord, CHU Saint-Étienne; and Univ Rennes (E.L.), EHESP, CNRS, Inserm, ARENES UMR 6051, RSMS U 1309, France.

Published: December 2023

AI Article Synopsis

  • This study compares two methods for estimating death probabilities in multiple sclerosis (MS) patients: the Cause-Specific Framework (CSF) which requires known causes of death, and the Excess Mortality Framework (EMF) which does not.
  • Using data from a large MS registry and a subset with detailed death records, the researchers found that EMF generally estimated higher death probabilities than CSF across different age groups.
  • Overall, the analysis revealed varying mortality probabilities for MS patients based on the initial disease type, sex, and age; with significant differences particularly noted between relapsing-onset MS and primary progressive patients over a 30-year follow-up.

Article Abstract

Background And Objectives: Determining whether multiple sclerosis (MS) causes death is challenging. Our objective was to contrast 2 frameworks to estimate probabilities of death attributed to MS (P) and other causes (P): the cause-specific framework (CSF), which requires the causes of death, and the excess mortality framework (EMF), which does not.

Methods: We used data from the Observatoire Français de la Sclérose en Plaques (OFSEP, n = 37,524) and from a comparative subset where causes of death were available (4,004 women with relapsing-onset MS [R-MS]). In CSF, the probabilities were estimated using the Aalen-Johansen method. In EMF, they were estimated from the excess mortality hazard, which is the additional mortality among patients with MS as compared with the expected mortality in the matched general population. P values were estimated at 30 years of follow-up, (1) with both frameworks in the comparative subset, by age group at onset, and (2) with EMF only in the OFSEP population, by initial phenotype, sex, and age at onset.

Results: In the comparative subset, the estimated 30-year P values were greater using EMF than CSF: 10.9% (95% CI 8.3-13.6) vs 8.7% (6.4-11.8) among the youngest and 20.4% (11.3-29.5) vs 16.2% (8.7-30.2) for the oldest groups, respectively. In the CSF, probabilities of death from unknown causes ranged from 1.5% (0.7-3.0) to 6.4% (2.5-16.4), and even after their reallocation, P values remained lower with CSF than with EMF. The estimated probabilities of being alive were close using the 2 frameworks, and the estimated P (EMF vs CSF) was 2.6% (2.5-2.6) vs 2.1% (1.2-3.9) and 18.1% (16.9-19.3) vs 26.4% (16.5-42.2), respectively, for the youngest and oldest groups. In the OFSEP population, the estimated 30-year P values ranged from 7.5% (6.4-8.7) to 24.0% (19.1-28.9) in patients with R-MS and from 25.4% (21.1-29.7) to 36.8% (28.3-45.3) in primary progressive patients, depending on sex and age.

Discussion: EMF has the great advantage of not requiring death certificates, their quality being less than optimal. Conceptually, it also seems more relevant because it avoids having to state, for each individual, whether death was directly or indirectly caused by MS or whether it would have occurred anyway, which is especially difficult in such chronic diseases.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10791051PMC
http://dx.doi.org/10.1212/WNL.0000000000207925DOI Listing

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