Evidence map›Paper›PMID 42427169›Full record

ArticleMovement disorders clinical practice2026

Disease-Duration-Specific Percentiles for Prospective Subtyping of Parkinson's Disease: A PPMI-Based Study.

Ahmed Negida, Nitai Mukhopadhyay, Brian D Berman, Seyed-Mohammad Fereshtehnejad, Matthew J Barrett

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Article in Movement disorders clinical practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ahmed NegidaParkinson's and Movement Disorders Center, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0001-5363-6369
Nitai MukhopadhyayDepartment of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0002-1530-9516
Brian D BermanParkinson's and Movement Disorders Center, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0002-0602-9942
Seyed-Mohammad FereshtehnejadPacific Parkinson's Research Centre (PPRC), Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0001-9255-9351
Matthew J BarrettParkinson's and Movement Disorders Center, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0003-4480-0221

Funding

Elucidating the Role of Cholinergic Degeneration in Cognitive Fluctuations in Lewy Body DementiaR01NS142622 · NINDS · VIRGINIA COMMONWEALTH UNIVERSITY · PI Matthew James Barrett · 2025 to 2026
$1.4M
Development and characterization of EEG signature of cognitive fluctuations in Lewy body dementiaR21AG077469 · NIA · VIRGINIA COMMONWEALTH UNIVERSITY · PI BARRETT, MATTHEW JAMES, MUKHOPADHYAY, NITAI D. · 2022 to 2022
$427k
NIA NIH HHS 1R01NS142622-01NIA NIH HHS 1R21AG077469-01NIA NIH HHS R21 AG077469NINDS NIH HHS R01 NS142622
6 · The paper itself

Abstract

backgroundParkinson's disease (PD) is clinically heterogeneous, with variable progression rates that complicate clinical trial design. The data-driven diffuse malignant (DM), intermediate (IM), and mild-motor predominant (MMP) subtyping model has prognostic value but lacks disease duration-specific thresholds for prospective use in disease-modifying trials.

objectiveTo define year-specific percentile thresholds for key motor and non-motor measures within the first 5 years after diagnosis to enable real-time PD subtyping and assess progression patterns across subtypes.

methodsWe analyzed de-identified PPMI data (downloaded April 22, 2026) from 1030 individuals with idiopathic PD. For each disease year, we computed percentiles for a composite motor score (MDS-UPDRS II + III + PIGD) and non-motor measures (MoCA, RBDSQ, SCOPA-AUT). Thresholds were set at the 75th percentile for motor, RBDSQ, and SCOPA-AUT, and the 25th percentile for MoCA, and applied annually to classify DM-, IM-, and MMP-PD. Subtype stability (years 1-5) and progression were assessed using 25 predefined PPMI milestones. Kaplan-Meier and Cox regression models evaluated time to first milestone.

resultsPercentile thresholds worsened progressively over time, paralleling cohort-level decline. DM-PD prevalence ranged from 19.2-20.5% (IM 41.8-44.4%; MMP 35.1-38.8%). At baseline, clinical measures differed significantly across subtypes. Compared to MMP-PD, DM-PD (HR 3.03; 95% CI: 2.30-3.97) and IM-PD (HR 1.48; 95% CI: 1.19-1.84) showed faster progression.

conclusionsWe establish disease duration-specific percentiles for prospective application of the DM/IM/MMP subtyping model, supporting patient stratification and enrichment in disease-modifying trials.

Indexed as

diffuse‐malignantParkinson's diseasestrartificationsubtypestrial enrichment

Identifiers

PMID42427169
PMCPMC13351593

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.