Disease Progression in Multiple System Atrophy: The Value of Clinical Cohorts with Long Follow-Up

In their recent publication, Kühnel et al¹ described the progression of multiple system atrophy (MSA) in the European MSA study group (EMSA-SG) cohort via an innovative disease progression model (DPM). DPMs are valuable longitudinal methods to describe MSA natural history while accounting for data uncertainty (delayed diagnosis, uncertain timing, heterogeneous staging).² The mean trajectories of clinical progression are described along the homogeneous disease continuum (Fig. 1C) rather than the observed time since diagnosis (Fig. 1A) thanks to a temporal recalibration of progression according to an individual latent disease time, anchored to MSA disease stage at inclusion.

The population characteristics and the length of individual follow-up are critical in natural history studies and DPMs. Kühnel's study relied on 121 patients with rather advanced stage, outdated diagnosis criteria, and short follow-up of 2 years.^{1, 3} We replicated Kühnel's analysis on repeated Unified MSA Rating Scale sum scores I (activities of daily living) and II (motor examination) from the French MSA cohort⁴ (663 patients) with maximum follow-up of 11 years, consensus diagnosis criteria,⁵ and early stages at entry (see Supplementary Material Data S1 for details). MSA progression spanned a larger period than in the original paper (Fig. 1C) with mean time gaps at inclusion estimated at 3.6 and 9.1 years for moderately-dependent and helpless patients at inclusion, respectively (Fig. 1B right panels); and significant inter-patient differences (SD = 2.14 years). When restricting the sample to 2.5-year follow-up, these differences were smaller, especially among the most aggressively affected patients at entry, with estimates of 2.5 and 6.6 years (Fig. 1B left panels) and smaller inter-patient differences (SD = 0.79 years). This suggests that studies restricted to short-term follow-up overestimate the progression rate and underestimate inter-patient differences.

When applying DPMs, differences across stages should be carefully interpreted. They do not quantify the expected amount of time spent in each stage by a patient, but the time gap between patients entering the study at different stages. Estimating the duration spent in each disability stage requires specific modeling of disability over time.

T.S.: 1A, 1B, 1C, 2A, 2B, 3A

M.F.: 2C, 3B

A.P.L.: 2C, 3B

M.L.: 2C, 3B

C.H.: 2C, 3B

P.P.: 2C, 3B

W.G.M.: 2C, 3B

O.R.: 2C, 3B

A.F.S.: 1A, 1B, 2A, 2C, 3A

C.P.L.: 1A, 1B, 2A, 2C, 3A