LIMB-GIRDLE MUSCULAR DYSTROPHY I: P.9A comparison of the utility between three muscle strength assessment methods in dysferlinopathy

Abstract

This study compared results between 3 methods of muscle strength testing used in the jain clinical outcome study (COS) for dysferlinopathy performed at baseline and year 1 visits. The COS is an international natural history study of patients with dysferlinopathy with the intent of improving trial readiness. Dysferlinopathy presents with heterogeneity in muscle weakness, including both distal and proximal phenotypes which poses significant challenges for developing appropriate clinical trial outcome measures. Two hundred and three patients, at 15 sites in 8 countries were evaluated using three methods to measure strength on a variety of upper and lower limb muscle groups. Manual muscle testing (MMT) uses the medical research council scoring system to subjectively grade the amount of resistance the subject can withstand as the evaluator pushes against the extremity. Hand held dynamometry (HHD) uses a force transducer in a small device held against the extremity by the clinical evaluator. Quantitative muscle testing (QMT) uses a force transducer secured to a wall mounted fixed frame. Although MMT is quick, simple and does not require specific equipment, it produces ordinal level data, which can be difficult for statistical analysis. Both HHD and QMT provide objective and quantitative measures of muscle strength but require specific equipment to perform. Cost and the size are significant limitations of QMT. All sites completed MMT and HHD, while only 7 of the 15 sites had the QMT equipment available. Muscle strength changes over 1 year will be presented for each of the three assessment methods. Although HHD, QMT and MMT detected change in many of the same muscles, differences in the responsiveness will be highlighted. Both HHD and QMT options offer linear, objective and quantitative data. HHD is an inexpensive, more accessible and simple option compared to QMT muscle testing. All three methods were able to detect change in this heterogeneous cohort over one year.