Investigating the Long-term Effect of Pregnancy on the Course of Multiple Sclerosis Using Causal Inference - Université de Rennes Accéder directement au contenu
Article Dans Une Revue Neurology Année : 2023

Investigating the Long-term Effect of Pregnancy on the Course of Multiple Sclerosis Using Causal Inference

Fabien Rollot
  • Fonction : Auteur
Marc Debouverie
  • Fonction : Auteur
Jerome de Seze
  • Fonction : Auteur
Elisabeth Maillart
Christine Lebrun-Frenay
Bruno Stankoff
Abdullatif Al Khedr
  • Fonction : Auteur
Olivier Casez
  • Fonction : Auteur
Bertrand Bourre
Philippe Cabre
  • Fonction : Auteur
Abir Wahab
  • Fonction : Auteur
Laurent Magy
  • Fonction : Auteur
Jean-Philippe Camdessanche
  • Fonction : Auteur
Aude Maurousset
  • Fonction : Auteur
Solène Moulin
  • Fonction : Auteur
Nasr Haifa Ben
  • Fonction : Auteur
Dalia Dimitri Boulos
  • Fonction : Auteur
Karolina Hankiewicz
  • Fonction : Auteur
Jean-Philippe Neau
  • Fonction : Auteur
Corinne Pottier
  • Fonction : Auteur
Chantal Nifle
  • Fonction : Auteur
Fabien Subtil
  • Fonction : Auteur

Résumé

Background and objectives - The question of the long-term safety of pregnancy is a major concern in patients with multiple sclerosis (MS), but its study is biased by reverse causation (women with higher disability are less likely to experience pregnancy). Using a causal inference approach, we aimed to estimate the unbiased long-term effects of pregnancy on disability and relapse risk in patients with MS and secondarily the short-term effects (during the perpartum and postpartum years) and delayed effects (occurring beyond 1 year after delivery). Methods - We conducted an observational cohort study with data from patients with MS followed in the Observatoire Français de la Sclérose en Plaques registry between 1990 and 2020. We included female patients with MS aged 18-45 years at MS onset, clinically followed up for more than 2 years, and with ≥3 Expanded Disease Status Scale (EDSS) measurements. Outcomes were the mean EDSS score at the end of follow-up and the annual probability of relapse during follow-up. Counterfactual outcomes were predicted using the longitudinal targeted maximum likelihood estimator in the entire study population. The patients exposed to at least 1 pregnancy during their follow-up were compared with the counterfactual situation in which, contrary to what was observed, they would not have been exposed to any pregnancy. Short-term and delayed effects were analyzed from the first pregnancy of early-exposed patients (who experienced it during their first 3 years of follow-up). Results - We included 9,100 patients, with a median follow-up duration of 7.8 years, of whom 2,125 (23.4%) patients were exposed to at least 1 pregnancy. Pregnancy had no significant long-term causal effect on the mean EDSS score at 9 years (causal mean difference [95% CI] = 0.00 [-0.16 to 0.15]) or on the annual probability of relapse (causal risk ratio [95% CI] = 0.95 [0.93-1.38]). For the 1,253 early-exposed patients, pregnancy significantly decreased the probability of relapse during the perpartum year and significantly increased it during the postpartum year, but no significant delayed effect was found on the EDSS and relapse rate. Discussion - Using a causal inference approach, we found no evidence of significantly deleterious or beneficial long-term effects of pregnancy on disability. The beneficial effects found in other studies were probably related to a reverse causation bias.
Fichier principal
Vignette du fichier
Gavoille et al -2023-Contribution of causal inference to the analysis of the long-term effect of.pdf (1.41 Mo) Télécharger le fichier
Supplementary materials.pdf (313.61 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03963580 , version 1 (19-07-2023)

Identifiants

Citer

Antoine Gavoille, Fabien Rollot, Romain Casey, Marc Debouverie, Emmanuelle Le Page, et al.. Investigating the Long-term Effect of Pregnancy on the Course of Multiple Sclerosis Using Causal Inference. Neurology, 2023, 100 (12), pp.e1296-e1308. ⟨10.1212/WNL.0000000000206774⟩. ⟨hal-03963580⟩
132 Consultations
16 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More