363P A cross-sectional survey upper limb functional using PUL 2.0 at large clinical centers and registries in patients with Duchenne muscular dystrophy

Abstract

Upper limb function is a critical determinant of quality of life for patients with Duchenne Muscular Dystrophy (DMD) who have lost the ability to walk. However, the majority of clinical trials assessing new therapeutic agents have focused on ambulant patients with DMD. The reasons for this gap are multi-fold but are due in part to the consensus for using the PUL 2.0 assessment as a primary endpoint being more recent. This study is a cross-functional survey of upper limb functional assessments focused on the large clinical centers and clinical registries led by cTAP collaborators and determined i) the number of patients with PUL 2.0 assessments, ii) frequency of evaluation, iii) functional characteristics of patients at baseline, and iv) the trigger for initiating PUL 2.0 evaluation. Most centers assessed upper limb function at 6-month intervals. The number of patients and patient visits at each center were, respectively: Italian Group (341,1628), CCHMC (256, 1145), GOSH (84, ∼240), Leiden University Medical Center (LUMC)(81, 278) and NMCL (25, >100). Mean PUL 2.0 entry score was 29.9 (SD 12.5) and 30.93 (SD 5.1) in the Italian Group and LUMC respectively; corresponding age at entry was (12.2 (SD 6.23) and 11.75 (SD 12.1). The number of patients with 5 or more follow-up assessments was 88 at 6 monthly intervals for the Italian Group and 28 at 12-month intervals for LUMC. Assessment of ambulatory function across centers was largely coherent, while protocols to assess bone health, cardiac function, and pulmonary function were less consistent. The results of this study will aid drug developers in better understanding the characteristics of this patient population, a pre-requisite step to designing clinical trials that can yield definitive assessment and therapeutic efficacy. It also highlights the importance of collecting consistent and high-quality real-world data in rare diseases.