In a Digital Version of the 9-Hole Peg Test, Intra-Task Speed, Accounting for Variance in Distance Traveled, May be a Better Measure of MS-Related Upper-Limb Disability Than Completion Time.
Xiaotong Jiang1, Marisa McGinley2, Joshua Johnston3, Jay Alberts3, Robert Bermel2, Daniel Ontaneda2, Nicholas Levitt1, Johan Van Beek1, Nolan Campbell1
1Biogen Inc., 2Mellen Center, Cleveland Clinic, 3Biomedical Engineering, Cleveland Clinic
Objective:
To determine if speed is a better measure of MS-related decline in upper limb function than the current standard of completion time utilizing a digital version of the 9-hole peg test (MDT).
Background:
MDT completion time reflects both the speed and distance travelled during the task. How each contributes to the variance and whether each is related to MS disease worsening can be measured.
Design/Methods:
Assessments were acquired using the Multiple Sclerosis Performance Test (MSPT) within the MS PATHS network. ‘Distance’ was the summed direct distance between every consecutive peg movement. ‘Speed’ was the summed direct distance per second of completion time. Intra-patient longitudinal change associations between MDT measures and Patient-Determined Disease Steps (PDDS), Processing Speed Test (PST), and Neuro-QoL scores were assessed by repeated measure correlations. Intra-patient minimum and maximum distance and dispersion (SD/mean) for speed and completion time were calculated in patients with >2 MDT assessments. Cox-models were used to assess covariates predicting time to 20% confirmed worsening (T20%CW) in completion time after 2 years.
Results:
Speed and completion time showed similar significant longitudinal associations with PDDS, PST, and Neuro-QoL upper extremity scores; distance was not associated. Intra-patient distance varied substantially between assessments; 62% of patients had >10cm; 27% had >20cm differences. Speed had lower dispersion than completion time. T20%CW in completion time models had better Akaike information criterion and Bayesian information criterion values, indicating better fit, when speed was used as the predictive covariate versus completion time. Adding speed to models with completion time significantly improved model performance; adding completion time to those with speed yielded no improvement.
Conclusions:
MDT completion time longitudinal changes have variance contributed by fluctuating distances travelled between assessments that are unrelated to MS disease. Accounting for this variance by measuring speed lowers dispersion and improves predictive model performance for time to meaningful worsening.