Ataluren delays loss of ambulation and respiratory decline in nonsense mutation Duchenne muscular dystrophy patients
Abstract
Aim: We investigated the effect of ataluren plus standard of care (SoC) on age at loss of ambulation (LoA) and respiratory decline in patients with nonsense mutation Duchenne muscular dystrophy (nmDMD) versus patients with DMD on SoC alone. Patients & methods: Study 019 was a long-term Phase III study of ataluren safety in nmDMD patients with a history of ataluren exposure. Propensity score matching identified Study 019 and CINRG DNHS patients similar in disease progression predictors. Results & conclusion: Ataluren plus SoC was associated with a 2.2-year delay in age at LoA (p = 0.0006), and a 3.0-year delay in decline of predicted forced vital capacity to ClinicalTrials.gov registration: NCT01557400.
How strong is the evidence?
Evidence Hub reads this as a clinical trial, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
Read the paper
Related studies
- Safety and efficacy of COVID‐19 vaccines: A systematic review and meta‐analysis of controlled and randomized clinical trials
- Accuracy Comparison between Robot-Assisted Dental Implant Placement and Static/Dynamic Computer-Assisted Implant Surgery: A Systematic Review and Meta-Analysis of In Vitro Studies
- Determinants of passive antibody efficacy in SARS-CoV-2 infection: a systematic review and meta-analysis
- Cleaning efficacy of EDDY versus ultrasonically-activated irrigation in root canals: a systematic review and meta-analysis
- Bonding Efficacy of Universal Resin Adhesives to Zirconia Substrates: Systematic Review and Meta-Analysis
- In vitro antimicrobial activity of extracts and essential oils of Cinnamomum, Salvia, and Mentha spp. against foodborne pathogens: A meta-analysis study
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.