Neurology · 2025
Disability Worsening Phenotypes in Multiple Sclerosis and Impact of Disease-Modifying Treatments.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
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De Meo Ermelinda, Addazio Ilaria, Portaccio Emilio, Bonacchi Raffaello, Betti Matteo, Patti Francesco, Guerrieri Simone, Foschi Matteo, Ferraro Diana, Annovazzi Pietro, Brescia Morra Vincenzo, Tortorella Carla, Lugaresi Alessandra, Camilli Federico, Pozzilli Carlo, Perini Paola, Granella Franco, De Luca Giovanna, Torri Clerici Valentina Liliana Adriana Maria, Vianello Marika, Romano Silvia, Cocco Eleonora E, Lus G, Di Sapio Alessia, Rocca Maria A, Simone Marta, Iaffaldano Pietro, Filippi Massimo, Trojano Maria, Amato Maria Pia
Аннотация
BACKGROUND AND OBJECTIVES: Patients with multiple sclerosis (MS) exhibit variability in disability progression and response to disease-modifying therapies (DMTs). Identifying those at greatest risk of disability worsening and most likely to benefit from high-efficacy DMTs remains challenging. We aimed to identify distinct disability worsening phenotypes, explore their mechanisms, and evaluate DMT impact across them.
METHODS: In this multicenter cohort study, we analyzed clinical and MRI data from propensity-matched cohorts of treated and untreated patients with relapse-onset MS from the Italian MS Register. Inclusion criteria were as follows: ≥3 years of follow-up, ≤1 year between disease onset and first assessment, and complete clinical and baseline MRI data. Latent class mixture models were applied to Expanded Disability Status Scale (EDSS) scores from untreated patients to identify disability worsening phenotypes. We compared proportions of progression independent of relapse activity (PIRA) and relapse-associated worsening events across phenotypes. A random forest algorithm, trained (70%) and tested (30%) on baseline clinical and MRI features of untreated patients, was used to assign phenotypes to treated patients. Linear mixed-effects models estimated DMT impact on disability trajectories within each phenotype.
RESULTS: We analyzed data from 2,563 untreated (mean age 41.2 ± 10 years, 67% female) and 2,952 treated (mean age 40.8 ± 11.4 years, 66% female) patients with MS over a median follow-up of 10.1 (interquartile range: 7.0-13.0) years. Four phenotypes were identified in untreated patients: "minimal-worsening" (15%), "late-worsening" (70%), "early-worsening" (3%), and "rapid-worsening" (12%). In all phenotypes, PIRA represented the main disability accrual mechanism. "Early-worsening" and "rapid-worsening" phenotypes exhibited more brain and spinal cord T2-hyperintense and gadolinium-enhancing lesions at baseline. The classification algorithm assigned phenotypes to patients receiving DMTs with 71% accuracy: "minimal-worsening" (18%), "late-worsening" (61%), "early-worsening" (13%), and "rapid-worsening" (8%). DMT exposure significantly reduced disability accrual in all phenotypes, with high-efficacy DMTs (β = -0.16, standard error (SE) = 0.06, p < 0.001) and early escalation (β = -0.18, SE = 0.06, p < 0.001) proving especially beneficial for the "rapid-worsening" phenotype.
DISCUSSION: We identified 4 clinically relevant disability worsening phenotypes in relapse-onset MS, primarily driven by PIRA, with greater CNS involvement linked to early and rapid progression. Despite reliance on EDSS alone, these phenotypes may inform personalized treatment and response assessment.
METHODS: In this multicenter cohort study, we analyzed clinical and MRI data from propensity-matched cohorts of treated and untreated patients with relapse-onset MS from the Italian MS Register. Inclusion criteria were as follows: ≥3 years of follow-up, ≤1 year between disease onset and first assessment, and complete clinical and baseline MRI data. Latent class mixture models were applied to Expanded Disability Status Scale (EDSS) scores from untreated patients to identify disability worsening phenotypes. We compared proportions of progression independent of relapse activity (PIRA) and relapse-associated worsening events across phenotypes. A random forest algorithm, trained (70%) and tested (30%) on baseline clinical and MRI features of untreated patients, was used to assign phenotypes to treated patients. Linear mixed-effects models estimated DMT impact on disability trajectories within each phenotype.
RESULTS: We analyzed data from 2,563 untreated (mean age 41.2 ± 10 years, 67% female) and 2,952 treated (mean age 40.8 ± 11.4 years, 66% female) patients with MS over a median follow-up of 10.1 (interquartile range: 7.0-13.0) years. Four phenotypes were identified in untreated patients: "minimal-worsening" (15%), "late-worsening" (70%), "early-worsening" (3%), and "rapid-worsening" (12%). In all phenotypes, PIRA represented the main disability accrual mechanism. "Early-worsening" and "rapid-worsening" phenotypes exhibited more brain and spinal cord T2-hyperintense and gadolinium-enhancing lesions at baseline. The classification algorithm assigned phenotypes to patients receiving DMTs with 71% accuracy: "minimal-worsening" (18%), "late-worsening" (61%), "early-worsening" (13%), and "rapid-worsening" (8%). DMT exposure significantly reduced disability accrual in all phenotypes, with high-efficacy DMTs (β = -0.16, standard error (SE) = 0.06, p < 0.001) and early escalation (β = -0.18, SE = 0.06, p < 0.001) proving especially beneficial for the "rapid-worsening" phenotype.
DISCUSSION: We identified 4 clinically relevant disability worsening phenotypes in relapse-onset MS, primarily driven by PIRA, with greater CNS involvement linked to early and rapid progression. Despite reliance on EDSS alone, these phenotypes may inform personalized treatment and response assessment.