Longitudinal Evaluation of an Abbreviated Patient‐Reported Movement Disorder Society‐sponsored revision of the Unified Parkinson's Disease Rating Scale ( <scp>MDS</scp> ‐ <scp>UPDRS)</scp> for Predicting Dopaminergic Therapy Initiation in Early Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Predicting initiation of dopaminergic therapy in early Parkinson's disease (PD) is important for clinical management and trial design. Prior cross-sectional work identified a six-item patient-reported subset from the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts IB + II, but its longitudinal utility is unknown. OBJECTIVES: To test whether modeling longitudinal symptom trajectories improves prediction of dopaminergic therapy initiation beyond baseline-only models, and to identify an abbreviated patient-reported subset with stable prognostic value and utility for trial stratification. METHODS: Data were harmonized from 1787 untreated early PD patients across six multicenter studies. All 20 MDS-UPDRS Parts IB + II items were analyzed using a longitudinal item response theory model. Items were ranked by discrimination and information functions, and cumulative subsets evaluated in Cox models with time-dependent covariates, adjusted for age, sex, disease duration, and Hoehn and Yahr stage. Predictive accuracy was quantified by concordance index (C-index) for full follow-up and truncation at 1 and 2 years. Risk stratification was assessed based on baseline abbreviated subset scores using Kaplan-Meier analyses. RESULTS: An 11-item model consistently outperformed the full 20-item scale (C-index 0.609 vs. 0.597, P < 0.001 with full follow-up; 0.621 vs. 0.599, P < 0.001 at 1 year; 0.615 vs. 0.602, P < 0.001 at 2 years). Longitudinal updates improved discrimination over baseline-only models (eg, 0.609 vs. 0.594 for full follow-up). Higher baseline 11-item scores were strongly associated with earlier therapy initiation. CONCLUSIONS: Longitudinal symptom modeling improves prediction of therapy initiation in early PD. An abbreviated 11-item patient-reported MDS-UPDRS provides stronger prognostic value than the full scale and supports trial stratification and clinical monitoring. © 2025 International Parkinson and Movement Disorder Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".