Outcome Measures in Duchenne Muscular Dystrophy.

4 stairs climbed (4SC) 6-Minute walking test (6MWT) Clinical outcomes Duchenne muscular dystrophy North star ambulatory assessment (NSAA) Performance of the upper limb (PUL)

Journal

Acta neurologica Belgica
ISSN: 2240-2993
Titre abrégé: Acta Neurol Belg
Pays: Italy
ID NLM: 0247035

Informations de publication

Date de publication:
31 Jul 2024
Historique:
received: 23 04 2024
accepted: 11 07 2024
medline: 31 7 2024
pubmed: 31 7 2024
entrez: 30 7 2024
Statut: aheadofprint

Résumé

Duchenne Muscular Dystrophy (DMD) is an X-linked recessive neuromuscular disorder primarily affecting males, caused by mutations in the dystrophin gene. The absence of dystrophin protein leads to progressive skeletal muscle degeneration. Recent advances in the therapeutic landscape underscore the need to identify appropriate outcome measures to assess treatment efficacy in ambulant and non-ambulant DMD patients, across clinical and research settings. This is essential for accurately evaluating new treatments and attributing therapeutic benefits.It is crucial to establish a robust correlation between outcome scores and disease progression patterns. This task is challenging since functional test performance may be influenced by different patient's characteristics, including the physiological evolution of the neurodevelopment together with the disease progression. While widely used DMD outcomes such as the North Star Ambulatory Assessment, the 6-Minute Walking Test, the 4 stairs climbed, and the Performance of the Upper Limb exhibit reliability and validity, their clinical significance is influenced by the wide phenotype and progression variability of the disease.We present and discuss the features (relevance, quantifiability, validity, objectivity, reliability, sensitivity, specificity, precision) of available DMD outcome measures, including new potential measures that may be provided by digital tools and artificial intelligence.

Identifiants

pubmed: 39080230
doi: 10.1007/s13760-024-02600-2
pii: 10.1007/s13760-024-02600-2
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

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pubmed: 11246687

Auteurs

Silvia Benemei (S)

Medical Affairs, Pfizer Italy, Rome, Italy. silvia.benemei@pfizer.com.

Francesca Gatto (F)

Medical Affairs, Pfizer Italy, Rome, Italy.

Luca Boni (L)

U.O. Epidemiologia Clinica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Marika Pane (M)

Nemo Clinical Centre, Fondazione Policlinico Universitario A. Gemelli IRCSS, Università Cattolica del Sacro Cuore, Rome, Italy.

Classifications MeSH