Disease progression indicators in Duchenne muscular dystrophy for use in matched analyses comparing treatment effects: a targeted literature review



Poster Number: 101


Katharina Buesch PhD, Nermina Ferizović MSc, Jessica Summers BSc, Igor Beitia PhD, Christian Werner PhD, Joel Jiang PhD, Iulia Dunnett BSc, Erik Landfeldt PhD


1. PTC Therapeutics, 2. MAP BioPharma Limited, 3. MAP BioPharma Limited, 4. PTC Therapeutics, 5. PTC Therapeutics, 6. PTC Therapeutics, 7. PTC Therapeutics, 8. Karolinska Institute

Background: Duchenne muscular dystrophy (DMD) is a severe and progressive neuromuscular disease. When comparing outcomes between two populations in non-randomised studies, propensity score matching (PSM) analysis is a statistical technique used to limit bias from confounding factors. However, the choice of covariates for a PSM analysis is dependent on the outcome.
Objective: The objective of this study was to review the literature for prognostic indicators of disease progression in DMD to inform specification of PSM models of clinical outcomes as part of future non-randomised studies.
Methods: MEDLINE, Embase and Cochrane Library database searches were performed up to January 2020 to identify disease progression factors in DMD. Search terms included variations of Duchenne, prognostic factors, natural history, and disease progression. Publications were assessed for relevance based on pre-specified eligibility criteria by a single reviewer with quality checks by a second. All included studies were assessed for robustness using the grading system of the Centre for Evidence-Based Medicine.

Results: The search strategy identified a total of 2,749 publications, of which 256 were included for data extraction and synthesis. Patient age (current, at onset of symptoms, and diagnosis) and glucocorticoid exposure (type, and duration) were identified as core prognostic indicators in DMD affecting a wide range of clinical outcomes, from measures of cardiac, respiratory, and bone health, to lower and upper extremity function (as quantified using e.g., the North Star Ambulatory Assessment), age at loss of independent ambulation, and fracture risk. For cardiac outcomes, identified indicators also included angiotensin-converting enzyme inhibitors, beta blockers, and diuretics.

Conclusions: We show that patient age and glucocorticoid exposure constitute core prognostic indicators in DMD. Our synthesis should be helpful to inform specification of PSM models in this indication/disease population.