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Continuous prediction of secondary progression in the individual course of multiple sclerosis

Artikel i vetenskaplig tidskrift
Författare Bengt Skoog
Helen Tedeholm
Björn Runmarker
Anders Odén
Oluf Andersen
Publicerad i Multiple Sclerosis and related Disorders
Volym 3
Nummer/häfte 5
Sidor 584-592
ISSN 2211-0348
Publiceringsår 2014
Publicerad vid Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap och rehabilitering
Institutionen för matematiska vetenskaper, matematisk statistik
Sidor 584-592
Språk en
Länkar dx.doi.org/10.1016/j.msard.2014.04....
Ämnesord Multiple sclerosis, Secondary progression, Prognosis, Prediction, Continuous hazard function
Ämneskategorier Klinisk medicin

Sammanfattning

Background: Prediction of the course of multiple sclerosis (MS) was traditionally based on features close to onset. Objective: To evaluate predictors of the individual risk of secondary progression (SP) identified at any time during relapsing-remitting MS. Methods: We analysed a database comprising an untreated MS incidence cohort (n=306) with five decades of follow-up. Data regarding predictors of all attacks (n=749) and demographics from patients (n=157) with at least one distinct second attack were included as covariates in a Poisson regression analysis with SP as outcome. Results: The average hazard function of transition to SPMS was 0.046 events per patient year, showing a maximum at age 33. Three covariates were significant predictors: age, a descriptor of the most recent relapse, and the interaction between the descriptor and time since the relapse. A hazard function termed "prediction score" estimated the risk of SP as number of transition events per patient year (range <0.01 to >0.15). Conclusions: The insights gained from this study are that the risk of transition to SP varies over time in individual patients, that the risk of SP is linked to previous relapses, that predictors in the later stages of the course are more effective than the traditional onset predictors, and that the number of potential predictors can be reduced to a few (three in this study) essential items. This advanced simplification facilitates adaption of the "prediction score" to other (more recent, benign or treated) materials, and allows for compact web-based applications

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