Short-term prediction of secondary progression in a sliding window: A test of a predicting algorithm in a validation cohort

B Skoog; J Link; H Tedeholm; M Longfils; O Nerman; J Fagius; O Andersen

doi:10.1177/2055217319875466

Short-term prediction of secondary progression in a sliding window: A test of a predicting algorithm in a validation cohort

Mult Scler J Exp Transl Clin. 2019 Sep 14;5(3):2055217319875466. doi: 10.1177/2055217319875466. eCollection 2019 Jul-Sep.

Authors

B Skoog¹, J Link², H Tedeholm¹, M Longfils³, O Nerman³, J Fagius⁴, O Andersen¹

Affiliations

¹ University of Gothenburg, the Sahlgrenska Academy, Institute of Neuroscience and Physiology, Section of Clinical Neuroscience and Rehabilitation, Sweden.
² Department of Clinical Neuroscience, Karolinska Institutet, Sweden.
³ Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
⁴ Neurology, Department of Neuroscience, Uppsala University, Sweden.

Abstract

Introduction: The Multiple Sclerosis Prediction Score (MSPS, www.msprediction.com) estimates, for any month during the course of relapsing-remitting multiple sclerosis (MS), the individual risk of transition to secondary progression (SP) during the following year.

Objective: Internal verification of the MSPS algorithm in a derivation cohort, the Gothenburg Incidence Cohort (GIC, n = 144) and external verification in the Uppsala MS cohort (UMS, n = 145).

Methods: Starting from their second relapse, patients were included and followed for 25 years. A matrix of MSPS values was created. From this matrix, a goodness-of-fit test and suitable diagnostic plots were derived to compare MSPS-calculated and observed outcomes (i.e. transition to SP).

Results: The median time to SP was slightly longer in the UMS than in the GIC, 15 vs. 11.5 years (p = 0.19). The MSPS was calibrated with multiplicative factors: 0.599 for the UMS and 0.829 for the GIC; the calibrated MSPS provided a good fit between expected and observed outcomes (chi-square p = 0.61 for the UMS), which indicated the model was not rejected.

Conclusion: The results suggest that the MSPS has clinically relevant generalizability in new cohorts, provided that the MSPS was calibrated to the actual overall SP incidence in the cohort.

Keywords: Epidemiology; multiple sclerosis; outcome measurement; progressive; relapsing/remitting.