Skoog B, Tedeholm H, Runmarker B, Odén A, Andersen O. Continuous prediction of secondary progression in the individual course of multiple sclerosis.
Mult Scler Relat Disord 2014;
3:584-92. [PMID:
26265270 DOI:
10.1016/j.msard.2014.04.004]
[Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 03/23/2014] [Accepted: 04/12/2014] [Indexed: 01/22/2023]
Abstract
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 (http://msprediction.com).
Collapse