Validation of a Patient-Reported Outcome Measure Sensitive to Diet and Nutraceutical Exposure in Parkinson’s Disease
Bibliographic record
Abstract
Background: The Patient-Reported Outcomes in Parkinson’s Disease (PRO-PD) scale is a 35-item visual analog measure designed to quantify symptom severity across motor and non-motor domains. Developed as a continuous, patient-centered outcome, PRO-PD captures patient-perceived change over time and is suitable for remote longitudinal assessment. This study evaluated the psychometric properties of PRO-PD across two independent datasets, in-cluding reliability, validity, factor structure, and minimal clinically important change (MCIC), and assessed its relevance to nutrition- and lifestyle-focused research. Methods: Convergent validity was evaluated in a cross-sectional clinical dataset (n = 46) using established clinician-rated and patient-reported instruments, including Hoehn and Yahr, Unified Parkinson’s Disease Rating Scale (UPDRS), Parkinson’s Disease Questionnaire-39 (PDQ-39), Montreal Cognitive Assessment (MoCA), and PROMIS measures. Internal con-sistency, temporal stability, factor structure, and known-groups validity were assessed in a large remote-monitoring cohort (n = 2,612). MCID thresholds were estimated in a longitudinal sub-sample (n = 390) using anchor-based methods, multinomial regression, and receiver operating characteristic analyses. Joint modeling (two-stage procedure) approach was applied to model the sensitivity of PRO-PD change in time to the binary diet factors evolution in time. Results: PRO-PD demonstrated strong convergent validity with established clinical measures, excellent internal consistency (Cronbach’s α = 0.93–0.95), and good test–retest reliability (ICC = 0.78 overall; 0.89 at 6 months). Confirmatory testing of a previously proposed eight-factor structure showed suboptimal fit, leading to a parsimonious four-factor solution (Cognitive, Autonomic, Motor, Psycho-Emotional) explaining 47.6% of variance. PRO-PD scores increased significantly with advancing disease duration and stage. MCID thresholds were +53.5 points for worsening and −78.5 points for improvement (AUC = 0.63–0.71), with greater sensitivity for detecting deterioration than improvement. Joint modeling further demonstrated sensitivity of PRO-PD to baseline dietary behaviors and dietary change over time. Conclusions: These findings support PRO-PD as a psychometrically robust, low-burden out-come measure suitable for remote monitoring and for use across nutrition, nutraceutical, and pharmacologic intervention studies, including in early PD where traditional scales may lack sensitivity.
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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 | 0.025 | 0.036 |
| 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 | 0.001 |
| 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".