Proportion and characteristics of secondary progressive multiple sclerosis in five European registries using objective classifiers

Abstract

Background To assign a course of secondary progressive multiple sclerosis (MS) (SPMS) may be difficult and the proportion of persons with SPMS varies between reports. An objective method for disease course classification may give a better estimation of the relative proportions of relapsing–remitting MS (RRMS) and SPMS and may identify situations where SPMS is under reported. Materials and methods Data were obtained for 61,900 MS patients from MS registries in the Czech Republic, Denmark, Germany, Sweden, and the United Kingdom (UK), including date of birth, sex, SP conversion year, visits with an Expanded Disability Status Scale (EDSS) score, MS onset and diagnosis date, relapses, and disease-modifying treatment (DMT) use. We included RRMS or SPMS patients with at least one visit between January 2017 and December 2019 if ≥ 18 years of age. We applied three objective methods: A set of SPMS clinical trial inclusion criteria (“EXPAND criteria”) modified for a real-world evidence setting, a modified version of the MSBase algorithm, and a decision tree-based algorithm recently published. Results The clinically assigned proportion of SPMS varied from 8.7% (Czechia) to 34.3% (UK). Objective classifiers estimated the proportion of SPMS from 15.1% (Germany by the EXPAND criteria) to 58.0% (UK by the decision tree method). Due to different requirements of number of EDSS scores, classifiers varied in the proportion they were able to classify; from 18% (UK by the MSBase algorithm) to 100% (the decision tree algorithm for all registries). Objectively classified SPMS patients were older, converted to SPMS later, had higher EDSS at index date and higher EDSS at conversion. More objectively classified SPMS were on DMTs compared to the clinically assigned. Conclusion SPMS appears to be systematically underdiagnosed in MS registries. Reclassified patients were more commonly on DMTs.

Onboarding of siponimod in secondary progressive multiple sclerosis patients in Australia: Novel, real-world evidence from the MSGo digital support programme

“… 20 This is further reinforced in registry data showing an average age for SPMS conversion of 51.7 to 57.9 years depending on the classification method used. 21 Amongst the participants identifying as female, 23 (9%) underwent pregnancy testing. The high proportion of women beyond childbearing age enrolled in the MSGo programme also aligns with data supporting that the mean age of onset of SPMS occurs for most women during the perimenopausal period.…”

The impact of healthcare systems on the clinical diagnosis and disease-modifying treatment usage in relapse-onset multiple sclerosis: a real-world perspective in five registries across Europe

“…The classifier rules have been described previously. 5 The classifier was developed using data from the Swedish registry and validated with an external and separate dataset from British Columbia. 1 Here, the algorithm parsed each patient’s historical EDSS observations from the first EDSS and onwards, using each visit as a baseline and the following visits as follow-up.…”

“…By means of an algorithm, known as a decision tree classifier and its minimal data requirements, we were able to re-classify all subjects. 5 A clinical diagnosis of SPMS effectively makes it clear to the patient and treating team that up until that point, the current DMTs may no longer be appropriate. Conversely, with an algorithmic diagnosis, neither the MS patient nor HCP have recorded a change in diagnosis; therefore, it is unknown if either is aware of the change in diagnosis.…”

“…By means of an algorithm, known as a decision tree classifier and its minimal data requirements, we were able to re-classify all subjects. 5 …”