Diagnostic prediction model for levodopa-induced dyskinesia in Parkinson’s disease

Abstract: Background: There are currently no methods to predict the development of levodopa-induced dyskinesia (LID), a frequent complication of Parkinson's disease (PD) treatment. Clinical predictors and single nucleotide polymorphisms (SNP) have been associated to LID in PD. Objective: To investigate the association of clinical and genetic variables with LID and to develop a diagnostic prediction model for LID in PD. Methods: We studied 430 PD patients using levodopa. The presence of LID was defined as an MDS-UPDRS Part IV score ≥1 on item 4.1. We tested the association between specific clinical variables and seven SNPs and the development of LID, using logistic regression models. Results: Regarding clinical variables, age of PD onset, disease duration, initial motor symptom and use of dopaminergic agonists were associated to LID. Only CC genotype of ADORA2A rs2298383 SNP was associated to LID after adjustment. We developed two diagnostic prediction models with reasonable accuracy, but we suggest that the clinical prediction model be used. This prediction model has an area under the curve of 0.817 (95% confidence interval [95%CI] 0.77–0.85) and no significant lack of fit (Hosmer-Lemeshow goodness-of-fit test p=0.61). Conclusion: Predicted probability of LID can be estimated with reasonable accuracy using a diagnostic clinical prediction model which combines age of PD onset, disease duration, initial motor symptom and use of dopaminergic agonists.

Alternative title
Modelo de predição diagnóstica para discinesias induzidas por levodopa na doença de Parkinson
Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Diagnostic prediction model for levodopa-induced dyskinesia in Parkinson’s disease ; volume:78 ; number:04 ; year:2020 ; pages:214-216
Arquivos de neuro-psiquiatria ; 78, Heft 04 (2020), 214-216

Contributor
SANTOS-LOBATO, Bruno Lopes
SCHUMACHER-SCHUH, Artur F.
RIEDER, Carlos R. M.
HUTZ, Mara H.
BORGES, Vanderci
FERRAZ, Henrique Ballalai
MATA, Ignacio F.
ZABETIAN, Cyrus P.
TUMAS, Vitor

DOI
10.1590/0004-282X20190191
URN
urn:nbn:de:101:1-2023072710483264126014
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:57 AM CEST

Data provider

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Associated

  • SANTOS-LOBATO, Bruno Lopes
  • SCHUMACHER-SCHUH, Artur F.
  • RIEDER, Carlos R. M.
  • HUTZ, Mara H.
  • BORGES, Vanderci
  • FERRAZ, Henrique Ballalai
  • MATA, Ignacio F.
  • ZABETIAN, Cyrus P.
  • TUMAS, Vitor

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