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Predicting the longitudinal changes of levodopa dose requirements in Parkinson's disease using item response theory assessment of real-world Unified Parkinson's Disease Rating Scale

DC Field Value Language
dc.contributor.author박경수-
dc.contributor.author이필휴-
dc.contributor.author채동우-
dc.date.accessioned2021-09-29T01:49:05Z-
dc.date.available2021-09-29T01:49:05Z-
dc.date.issued2021-06-
dc.identifier.issn2163-8306-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/184561-
dc.description.abstractItem response theory (IRT) has been recently adopted to successfully characterize the progression of Parkinson's disease using serial Unified Parkinson's Disease Rating Scale (UPDRS) measurements. However, it has yet to be applied in predicting the longitudinal changes of levodopa dose requirements in the real-world setting. Here we use IRT to extract two latent variables that represent tremor and non-tremor-related symptoms from baseline assessments of UPDRS Part III scores. We show that relative magnitudes of the two latent variables are strong predictors of the progressive increase of levodopa equivalent dose (LED). Retrospectively collected item-level UPDRS Part III scores and longitudinal records of prescribed medication doses of 128 patients with de novo PD extracted from the electronic medical records were used for model building. Supplementary analysis based on a subset of 36 patients with at least three serial assessments of UPDRS Part III scores suggested that the two latent variables progress at significantly different rates. A web application was developed to facilitate the use of our model in making individualized predictions of future LED and disease progression.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherNature Pub. Group-
dc.relation.isPartOfCPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titlePredicting the longitudinal changes of levodopa dose requirements in Parkinson's disease using item response theory assessment of real-world Unified Parkinson's Disease Rating Scale-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Pharmacology (약리학교실)-
dc.contributor.googleauthorDongwoo Chae-
dc.contributor.googleauthorSu Jin Chung-
dc.contributor.googleauthorPhil Hyu Lee-
dc.contributor.googleauthorKyungsoo Park-
dc.identifier.doi10.1002/psp4.12632-
dc.contributor.localIdA01422-
dc.contributor.localIdA03270-
dc.contributor.localIdA04014-
dc.relation.journalcodeJ04097-
dc.identifier.pmid33939329-
dc.contributor.alternativeNamePark, Kyung Soo-
dc.contributor.affiliatedAuthor박경수-
dc.contributor.affiliatedAuthor이필휴-
dc.contributor.affiliatedAuthor채동우-
dc.citation.volume10-
dc.citation.number6-
dc.citation.startPage611-
dc.citation.endPage621-
dc.identifier.bibliographicCitationCPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, Vol.10(6) : 611-621, 2021-06-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pharmacology (약리학교실) > 1. Journal Papers

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