Longitudinal natural history in young boys with Duchenne muscular dystrophy

Giorgia Coratti1, Claudia Brogna1, Giulia Norcia2

  • 1Paediatric Neurology, Catholic University, Rome, Italy; Centro Clinico Nemo, Policlinico Gemelli, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.

Insights

Disease progression in Duchenne muscular dystrophy (DMD) boys aged 3-6 years shows North Star Ambulatory Assessment scores increase with age. Corticosteroid use and mutation site impact these changes, informing clinical trial design.

Area of Science:

  • Neurology
  • Genetics
  • Pediatrics

Background:

  • Duchenne muscular dystrophy (DMD) is a progressive genetic disorder affecting young boys.
  • Early assessment of disease progression is crucial for managing DMD and designing clinical trials.
  • The North Star Ambulatory Assessment (NSAA) scale is used to evaluate functional abilities in DMD patients.

Purpose of the Study:

  • To document the disease progression in young boys with DMD between the ages of 3 and 6 years.
  • To identify factors influencing disease progression as measured by the NSAA scale.
  • To provide data for the assessment, counseling, and clinical trial design for young DMD patients.

Main Methods:

  • Prospective, multicentric study involving 153 DMD boys aged 3-6 years.
  • 573 NSAA assessments were conducted.
  • Multiple linear regression analysis was used to identify factors affecting NSAA scores.

Main Results:

  • NSAA scores progressively increased with age, with the largest gains between 3-4 years.
  • Corticosteroid treatment and mutation site significantly influenced NSAA changes (p < 0.001).
  • Boys on corticosteroids and those with mutations at the 5' end of the gene showed better outcomes.

Conclusions:

  • Disease progression in young DMD boys is characterized by increasing NSAA scores until age 6.
  • Corticosteroid use and specific mutation locations are key determinants of functional outcomes.
  • Findings support the use of NSAA for monitoring DMD progression and optimizing clinical trial strategies.

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