Predicting risk of secondary progression in multiple sclerosis: A nomogram.
Adult
Age Factors
Age of Onset
Canada
/ epidemiology
Cohort Studies
Europe
/ epidemiology
Female
Humans
Male
Middle Aged
Models, Statistical
Multiple Sclerosis, Chronic Progressive
/ diagnosis
Multiple Sclerosis, Relapsing-Remitting
/ diagnosis
Nomograms
Prognosis
Registries
/ statistics & numerical data
Risk Assessment
/ statistics & numerical data
Severity of Illness Index
Sweden
/ epidemiology
Multiple sclerosis
disability
prediction
prognosis
secondary progressive
Journal
Multiple sclerosis (Houndmills, Basingstoke, England)
ISSN: 1477-0970
Titre abrégé: Mult Scler
Pays: England
ID NLM: 9509185
Informations de publication
Date de publication:
07 2019
07 2019
Historique:
pubmed:
19
6
2018
medline:
20
3
2020
entrez:
19
6
2018
Statut:
ppublish
Résumé
We aimed at designing a nomogram, a prediction tool, to predict the individual's risk of conversion to secondary progressive multiple sclerosis (SPMS) at the time of multiple sclerosis (MS) onset. One derivation and three validation cohorts were established. The derivation cohort included 8825 relapsing-onset MS patients in Sweden. A nomogram was built based on a survival model with the best statistical fit and prediction accuracy. The nomogram was validated using data from 3967 patients in the British Columbia cohort, 176 patients in the ACROSS and 2355 patients in FREEDOMS/FREEDOMS II extension studies. Sex, calendar year of birth, first-recorded Expanded Disability Status Scale (EDSS) score, age at the first EDSS and age at disease onset showed significant predictive ability to estimate the risk of SPMS conversion at 10, 15 and 20 years. The nomogram reached 84% (95% confidence intervals (CIs): 83-85) internal and 77% (95% CI: 76-78), 77% (95% CI: 70-85) and 87% (95% CI: 84-89) external accuracy. The SPMS nomogram represents a much-needed complementary tool designed to assist in decision-making and patient counselling in the early phase of MS. The SPMS nomogram may improve outcomes by prompting timely and more efficacious treatment for those with a worse prognosis.
Identifiants
pubmed: 29911467
doi: 10.1177/1352458518783667
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM