| Affiliation: | 1. Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada;2. Multiple Sclerosis Center, Swedish Neuroscience Institute, Seattle, Washington, USA;3. Department of Neurology, Rijnstate Hospital, Arnhem, The Netherlands;4. Department of Medicine, Neurology service, Hôpital Maisonneuve-Rosemont, Montreal, Quebec, Canada Département de neurosciences, Faculté de médecine, Université de Montréal, Montreal, Quebec, Canada;5. Department of Neurology, MS Center Amsterdam, Amsterdam University Medical Centers, Amsterdam, The Netherlands;6. Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA |
| Abstract: | Background and purpose The timed 25-foot walk (T25FW) and nine-hole peg test (NHPT) exhibit random variability in the short term. A threshold of ≥20% change from baseline has been used to indicate true disability change, but other threshold definitions may be better suited to exclude false and include true change events. The aim of this study was to use patient-level original trial data to investigate the short-term variation in T25FW and NHPT, and to compare its extent with disability change at 12-month follow-up in people with primary progressive multiple sclerosis (PPMS). Methods We used original patient-level data from PROMISE, a large PPMS trial. In this trial, three separate T25FW and NHPT measurements were performed 1 week apart during screening. We used these repeated measures to describe the extent of short-term variation. We used binary logistic regression models to investigate the association between screening characteristics and unacceptable short-term variation. Results The traditional 20% threshold excluded a reasonable number of false change events, while also yielding a large number of change events at follow-up. Increasing index values on the T25FW and NHPT were associated with higher short-term variation. Conclusions The traditional ≥20% change threshold for the T25FW and NHPT represents a reasonable compromise between reducing the number of false change events and achieving the largest number of change events in people with PPMS. Our analyses inform the design of clinical trials in PPMS. |
