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Evaluating multivariable prediction models for Parkinson's disease prognosis: a scoping review protocol
Lynn Eickholt1, Megan Super1, Whitley Aamodt2,3
1Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
BMJ Open
|December 30, 2025
Summary
This scoping review will identify and appraise existing Parkinson's disease (PD) prognostic models. The findings will guide the development of better prediction tools for individual patient outcomes.
Area of Science:
- Neurology
- Biostatistics
- Data Science
Background:
- Parkinson's disease (PD) presents with varied motor and non-motor symptoms, impacting prognosis individually.
- Current prediction models for PD clinical outcomes lack comprehensive development, validation, and demonstrated clinical utility.
- There is a need for systematic evaluation of existing prognostic models to guide future research and clinical practice.
Purpose of the Study:
- To develop a systematic method for identifying, reviewing, and appraising multivariable prognostic models in Parkinson's disease.
- To summarize the current literature on PD prognostic models and identify knowledge gaps.
- To inform the development and validation of improved clinical prediction models for individual prognostication in PD.
Main Methods:
- A scoping review guided by PRISMA-ScR methodology.
- Inclusion of multivariable models predicting PD progression using traditional statistics or machine learning, excluding univariable models.
- Comprehensive search of PubMed, EMBASE, Web of Science, and Scopus databases through 2025, with data extraction and dual-reviewer screening using Covidence.
- Appraisal of included models using TRIPOD+AI and PROBAST guidelines.
Main Results:
- The review will synthesize findings from identified multivariable prediction models, categorized by clinical outcome.
- Deficiencies and areas for improvement in existing PD prognostic models will be identified through systematic appraisal.
- The study will provide a comprehensive overview of the current landscape of PD prognostic modeling.
Conclusions:
- This scoping review will establish a foundation for understanding the current state of prognostic modeling in Parkinson's disease.
- The findings will guide the development of more robust and clinically useful prediction models for individual PD patient prognoses.
- Dissemination through publications and conferences will aid clinicians in evidence-based decision-making and inform future research directions.
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