Literature DB >> 29582054

Office-Based Screening for Dementia in Parkinson Disease: The Montreal Parkinson Risk of Dementia Scale in 4 Longitudinal Cohorts.

Benjamin K Dawson1,2, Seyed-Mohammad Fereshtehnejad1,3, Julius B M Anang1, Takashi Nomura4, Silvia Rios-Romenets1, Kenji Nakashima4, Jean-François Gagnon5,6, Ronald B Postuma1.   

Abstract

Importance: Parkinson disease dementia dramatically increases mortality rates, patient expenditures, hospitalization risk, and caregiver burden. Currently, predicting Parkinson disease dementia risk is difficult, particularly in an office-based setting, without extensive biomarker testing. Objective: To appraise the predictive validity of the Montreal Parkinson Risk of Dementia Scale, an office-based screening tool consisting of 8 items that are simply assessed. Design, Setting, and Participants: This multicenter study (Montreal, Canada; Tottori, Japan; and Parkinson Progression Markers Initiative sites) used 4 diverse Parkinson disease cohorts with a prospective 4.4-year follow-up. A total of 717 patients with Parkinson disease were recruited between May 2005 and June 2016. Of these, 607 were dementia-free at baseline and followed-up for 1 year or more and so were included. The association of individual baseline scale variables with eventual dementia risk was calculated. Participants were then randomly split into cohorts to investigate weighting and determine the scale's optimal cutoff point. Receiver operating characteristic curves were calculated and correlations with selected biomarkers were investigated. Main Outcomes and Measures: Dementia, as defined by Movement Disorder Society level I criteria.
Results: Of the 607 patients (mean [SD] age, 63.4 [10.1]; 376 men [62%]), 70 (11.5%) converted to dementia. All 8 items of the Montreal Parkinson Risk of Dementia Scale independently predicted dementia development at the 5% significance level. The annual conversion rate to dementia in the high-risk group (score, >5) was 14.9% compared with 5.8% in the intermediate group (score, 4-5) and 0.6% in the low-risk group (score, 0-3). The weighting procedure conferred no significant advantage. Overall predictive validity by the area under the receiver operating characteristic curve was 0.877 (95% CI, 0.829-0.924) across all cohorts. A cutoff of 4 or greater yielded a sensitivity of 77.1% (95% CI, 65.6-86.3) and a specificity of 87.2% (95% CI, 84.1-89.9), with a positive predictive value (as of 4.4 years) of 43.90% (95% CI, 37.76-50.24) and a negative predictive value of 96.70% (95% CI, 95.01-97.85). Positive and negative likelihood ratios were 5.94 (95% CI, 4.08-8.65) and 0.26 (95% CI, 0.17-0.40), respectively. Scale results correlated with markers of Alzheimer pathology and neuropsychological test results. Conclusions and Relevance: Despite its simplicity, the Montreal Parkinson Risk of Dementia Scale demonstrated predictive validity equal or greater to previously described algorithms using biomarker assessments. Future studies using head-to-head comparisons or refinement of weighting would be of interest.

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Mesh:

Year:  2018        PMID: 29582054      PMCID: PMC5885166          DOI: 10.1001/jamaneurol.2018.0254

Source DB:  PubMed          Journal:  JAMA Neurol        ISSN: 2168-6149            Impact factor:   18.302


  31 in total

1.  Diagnostic accuracy of REM sleep behaviour disorder screening questionnaire: a meta-analysis.

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2.  Neuropathological and genetic correlates of survival and dementia onset in synucleinopathies: a retrospective analysis.

Authors:  David J Irwin; Murray Grossman; Daniel Weintraub; Howard I Hurtig; John E Duda; Sharon X Xie; Edward B Lee; Vivianna M Van Deerlin; Oscar L Lopez; Julia K Kofler; Peter T Nelson; Gregory A Jicha; Randy Woltjer; Joseph F Quinn; Jeffery Kaye; James B Leverenz; Debby Tsuang; Katelan Longfellow; Dora Yearout; Walter Kukull; C Dirk Keene; Thomas J Montine; Cyrus P Zabetian; John Q Trojanowski
Journal:  Lancet Neurol       Date:  2017-01       Impact factor: 44.182

3.  White matter hyperintensities, cerebrospinal amyloid-β and dementia in Parkinson's disease.

Authors:  Yaroslau Compta; Mariateresa Buongiorno; Núria Bargalló; Francesc Valldeoriola; Esteban Muñoz; Eduardo Tolosa; José Ríos; Ana Cámara; Manel Fernández; Maria J Martí
Journal:  J Neurol Sci       Date:  2016-06-11       Impact factor: 3.181

4.  Prediction of cognition in Parkinson's disease with a clinical-genetic score: a longitudinal analysis of nine cohorts.

Authors:  Ganqiang Liu; Joseph J Locascio; Jean-Christophe Corvol; Brendon Boot; Zhixiang Liao; Kara Page; Daly Franco; Kyle Burke; Iris E Jansen; Ana Trisini-Lipsanopoulos; Sophie Winder-Rhodes; Caroline M Tanner; Anthony E Lang; Shirley Eberly; Alexis Elbaz; Alexis Brice; Graziella Mangone; Bernard Ravina; Ira Shoulson; Florence Cormier-Dequaire; Peter Heutink; Jacobus J van Hilten; Roger A Barker; Caroline H Williams-Gray; Johan Marinus; Clemens R Scherzer
Journal:  Lancet Neurol       Date:  2017-06-16       Impact factor: 44.182

Review 5.  The Parkinson Progression Marker Initiative (PPMI).

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6.  Cognitive predictors of dementia in Parkinson's disease: a community-based, 4-year longitudinal study.

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Review 7.  Diagnostic procedures for Parkinson's disease dementia: recommendations from the movement disorder society task force.

Authors:  Bruno Dubois; David Burn; Christopher Goetz; Dag Aarsland; Richard G Brown; Gerald A Broe; Dennis Dickson; Charles Duyckaerts; Jefferey Cummings; Serge Gauthier; Amos Korczyn; Andrew Lees; Richard Levy; Irene Litvan; Yoshikuni Mizuno; Ian G McKeith; C Warren Olanow; Werner Poewe; Cristina Sampaio; Eduardo Tolosa; Murat Emre
Journal:  Mov Disord       Date:  2007-12       Impact factor: 10.338

8.  Combined dementia-risk biomarkers in Parkinson's disease: a prospective longitudinal study.

Authors:  Yaroslau Compta; Joana B Pereira; Jose Ríos; Naroa Ibarretxe-Bilbao; Carme Junqué; Núria Bargalló; Ana Cámara; Mariateresa Buongiorno; Manel Fernández; Claustre Pont-Sunyer; Maria J Martí
Journal:  Parkinsonism Relat Disord       Date:  2013-05-03       Impact factor: 4.891

9.  Clinical variables and biomarkers in prediction of cognitive impairment in patients with newly diagnosed Parkinson's disease: a cohort study.

Authors:  Anette Schrag; Uzma Faisal Siddiqui; Zacharias Anastasiou; Daniel Weintraub; Jonathan M Schott
Journal:  Lancet Neurol       Date:  2016-11-18       Impact factor: 44.182

10.  An Alzheimer's Disease-Derived Biomarker Signature Identifies Parkinson's Disease Patients with Dementia.

Authors:  Yosef Berlyand; Daniel Weintraub; Sharon X Xie; Ian A Mellis; Jimit Doshi; Jacqueline Rick; Jennifer McBride; Christos Davatzikos; Leslie M Shaw; Howard Hurtig; John Q Trojanowski; Alice S Chen-Plotkin
Journal:  PLoS One       Date:  2016-01-26       Impact factor: 3.240

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Authors:  Hojoong M Kim; Carter Nazor; Cyrus P Zabetian; Joseph F Quinn; Kathryn A Chung; Amie L Hiller; Shu-Ching Hu; James B Leverenz; Thomas J Montine; Karen L Edwards; Brenna Cholerton
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3.  Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson's disease: Protocol of the mixed method, cyclic ActiveAgeing study.

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  3 in total

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