Increasing Sensitivity in Patient-Reported MDS-UPDRS Items for Predicting Medication Initiation in Early PD.

Mov Disord Clin Pract

Department of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina, USA.

Published: October 2024

Background: The MDS-UPDRS Parts IB and II are self-reported items providing a direct patient voice to the experiences of PD.

Objective: To determine the most sensitive combination of MDS-UPDRS Parts IB and II items that accurately predicted the clinically relevant target of dopaminergic therapy initiation.

Methods: Utilizing a longitudinal cohort of de novo non-treated PD patients, we applied item response theory (IRT) and survival analysis to assess the relationship between baseline patient-reported symptoms and the later initiation of dopaminergic therapy. The 20 MDS-UPDRS Parts IB and II items were analyzed for their relationship to PD severity (discrimination) and the amount of information they provided in this determination (information). These parameters were used to develop models of predictive accuracy for initiation of dopaminergic therapy.

Results: A six-item version showed a significantly higher C-index as compared to the full 20 item model (P = 0.001). This shortened version of the MDS-UPDRS contained only Part II items and provided a predictive accuracy for initiation of dopaminergic therapy better than the total combined scale score or any other combination.

Conclusions: A six-item "Baseline Outcome Voice" version of patient-reported MDS-UPDRS items significantly increases the sensitivity of predicting the key future clinical outcome of starting dopaminergic treatment in early PD. This study also demonstrates how IRT modeling can provide information useful to refining existing measures to identify the most sensitive combination of items honoring the voice of the patient in determining key clinically pertinent decisions. Further research is needed to validate these findings in underrepresented populations.

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Source
http://dx.doi.org/10.1002/mdc3.14229DOI Listing

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