Predicting risk of secondary progression in multiple sclerosis: A nomogram

Abstract

Objectives:

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.

Methods:

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.

Results:

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.

Conclusions:

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.

Keywords

Multiple sclerosis prediction disability prognosis secondary progressive

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