Portable fixed dynamometry enables home-based, reliable assessment of muscle strength in patients with amyotrophic lateral sclerosis: a pilot study

OBJECTIVE: To determine the feasibility, reliability, and sensitivity of remotely monitoring muscle strength loss of knee extensors using a novel portable fixed dynamometer (PFD) in patients with amyotrophic lateral sclerosis (ALS). METHODS: We conducted a pilot study with a newly developed device to measure knee extension strength. Patients performed unsupervised PFD measurements, biweekly, for 6 months at home. We evaluated feasibility using adherence and a device-specific questionnaire. Reliability was assessed by (1) comparing unsupervised and supervised measurements to identify systematic bias, and (2) comparing consecutive unsupervised measurements to determine test-retest reliability expressed as intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Sensitivity to detect longitudinal change was described using linear mixed-effects models. RESULTS: We enrolled 18 patients with ALS. Adherence was 86%, where all patients found that the device suitable to measure muscle strength at home; 4 patients (24%) found the measurements burdensome. The correlation between (un)supervised measurements was excellent (Pearson's r 0.97, 95%CI; 0.94 - 0.99) and no systematic bias was present (mean difference 0.13, 95%CI; -2.22 - 2.48, p  = 0.91). Unsupervised measurements had excellent test-retest reliability with an average ICC of 0.97 (95%CI: 0.94 - 0.99) and SEM of 5.8% (95%CI: 4.8 - 7.0). Muscle strength declined monthly by 1.9 %predicted points (95%CI; -3.0 to -0.9, p  = 0.001). CONCLUSIONS: Using the PFD, it proved feasible to perform knee extension strength measurements at home which were reliable and sensitive for detecting muscle strength loss. Larger studies are warranted to compare the device with conventional outcomes

Development and Evaluation of a Simulation-Based Algorithm to Optimize the Planning of Interim Analyses for Clinical Trials in ALS

BACKGROUND AND OBJECTIVES: Late-phase clinical trials for neurodegenerative diseases have a low probability of success. In this study, we introduce an algorithm that optimizes the planning of interim analyses for clinical trials in amyotrophic lateral sclerosis (ALS) to better use the time and resources available and minimize the exposure of patients to ineffective or harmful drugs. METHODS: A simulation-based algorithm was developed to determine the optimal interim analysis scheme by integrating prior knowledge about the success rate of ALS clinical trials with drug-specific information obtained in early-phase studies. Interim analysis schemes were optimized by varying the number and timing of interim analyses, together with their decision rules about when to stop a trial. The algorithm was applied retrospectively to 3 clinical trials that investigated the efficacy of diaphragm pacing or ceftriaxone on survival in patients with ALS. Outcomes were additionally compared with conventional interim designs. RESULTS: We evaluated 183-1,351 unique interim analysis schemes for each trial. Application of the optimal designs correctly established lack of efficacy, would have concluded all studies 1.2-19.4 months earlier (reduction of 4.6%-57.7% in trial duration), and could have reduced the number of randomized patients by 1.7%-58.1%. By means of simulation, we illustrate the efficiency for other treatment scenarios. The optimized interim analysis schemes outperformed conventional interim designs in most scenarios. DISCUSSION: Our algorithm uses prior knowledge to determine the uncertainty of the expected treatment effect in ALS clinical trials and optimizes the planning of interim analyses. Improving futility monitoring in ALS could minimize the exposure of patients to ineffective or harmful treatments and result in significant ethical and efficiency gains