Michelle Hyczy de Siqueira Tosin1,2, Christopher G Goetz2, Sheng Luo3, Dongrak Choi3, Glenn T Stebbins2. 1. Department of Nursing, Federal Fluminense University, Niterói, Rio de Janeiro, Brazil. 2. Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA. 3. Department of Biostatistics and Bioinformatics, Duke University, Medical Center, Durham, North Carolina, USA.
Abstract
BACKGROUND: In PD, tremor severity behaves differently from other core motor features. However, the most commonly used assessment of overall motor severity, total MDS-UPDRS Motor Examination (Part 3) score, does not account for this distinction. OBJECTIVES: To investigate the Motor Examination (Part 3) using Item Response Theory approaches focusing on sample-independent strategies that assess how well items measure latent models of PD motor severity. METHODS: Data from 6,298 PD patients were analyzed with graded response model Item Response Theory approaches involving two analyses all 33 Part 3 items versus the 10 tremor items and 23 bradykinesia, rigidity, gait, and posture items considered separately. The strength of relationship between items and the latent measure of parkinsonian motor severity (discrimination parameter) and calculated thresholds (location parameters) were assessed using the mirt program implemented in R (R Foundation for Statistical Computing, Vienna, Austria). RESULTS: Analyzing all Part 3 items together, nontremor items demonstrated good discrimination parameters (mean = 1.83 ± 0.37) and range of thresholds (-1.73 to +4.42), but tremor items had poor discrimination (mean = 0.52 ± 0.76) and thresholds (-0.69 to 14.29). Segregating nontremor from tremor items in two independent analyses provided markedly improved discrimination and location parameters for both. CONCLUSIONS: MDS-UPDRS Part 3 tremor and nontremor items have very different relations to the construct of PD severity. Strongly improved clinimetric properties for Part 3 are obtained when tremor and nontremor items are considered separately. We suggest that evaluating PD motor severity, as an operationalized summary measure, is best attained through separate analyses with tremor and nontremor motor scores.
BACKGROUND: In PD, tremor severity behaves differently from other core motor features. However, the most commonly used assessment of overall motor severity, total MDS-UPDRS Motor Examination (Part 3) score, does not account for this distinction. OBJECTIVES: To investigate the Motor Examination (Part 3) using Item Response Theory approaches focusing on sample-independent strategies that assess how well items measure latent models of PD motor severity. METHODS: Data from 6,298 PD patients were analyzed with graded response model Item Response Theory approaches involving two analyses all 33 Part 3 items versus the 10 tremor items and 23 bradykinesia, rigidity, gait, and posture items considered separately. The strength of relationship between items and the latent measure of parkinsonian motor severity (discrimination parameter) and calculated thresholds (location parameters) were assessed using the mirt program implemented in R (R Foundation for Statistical Computing, Vienna, Austria). RESULTS: Analyzing all Part 3 items together, nontremor items demonstrated good discrimination parameters (mean = 1.83 ± 0.37) and range of thresholds (-1.73 to +4.42), but tremor items had poor discrimination (mean = 0.52 ± 0.76) and thresholds (-0.69 to 14.29). Segregating nontremor from tremor items in two independent analyses provided markedly improved discrimination and location parameters for both. CONCLUSIONS: MDS-UPDRS Part 3 tremor and nontremor items have very different relations to the construct of PD severity. Strongly improved clinimetric properties for Part 3 are obtained when tremor and nontremor items are considered separately. We suggest that evaluating PD motor severity, as an operationalized summary measure, is best attained through separate analyses with tremor and nontremor motor scores.
Authors: Haotian Zou; Varun Aggarwal; Glenn T Stebbins; Martijn L T M Müller; Jesse M Cedarbaum; Anne Pedata; Diane Stephenson; Tanya Simuni; Sheng Luo Journal: CPT Pharmacometrics Syst Pharmacol Date: 2022-08-09