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• W4365455380 abstract "Movement Disorders Clinical PracticeEarly View VIEWPOINT Digital Biomarkers in Parkinson's Disease: Missing the Forest for the Trees? Ashwani Jha MRCP, PhD, Corresponding Author Ashwani Jha MRCP, PhD [email protected] orcid.org/0000-0003-2835-6837 UCL Queen Square Institute of Neurology, London, United Kingdom Correspondence to: Dr Ashwani Jha, UCL Queen Square Institute of Neurology, Russell Square House, 10-12 Russell Square, 1st floor Stroke Research Centre, London WC1B 5EH, UK; E-mail: [email protected]Search for more papers by this authorAlberto J. Espay MD, MSc, Alberto J. Espay MD, MSc orcid.org/0000-0002-3389-136X James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, Ohio, USASearch for more papers by this authorAndrew J. Lees FRCP, F.Med.Sci, PhD, Andrew J. Lees FRCP, F.Med.Sci, PhD Reta Lila Weston Institute of Neurological Studies, Department of Clinical Movement Disorder and Neuroscience, Institute of Neurology, University College London, London, United KingdomSearch for more papers by this author Ashwani Jha MRCP, PhD, Corresponding Author Ashwani Jha MRCP, PhD [email protected] orcid.org/0000-0003-2835-6837 UCL Queen Square Institute of Neurology, London, United Kingdom Correspondence to: Dr Ashwani Jha, UCL Queen Square Institute of Neurology, Russell Square House, 10-12 Russell Square, 1st floor Stroke Research Centre, London WC1B 5EH, UK; E-mail: [email protected]Search for more papers by this authorAlberto J. Espay MD, MSc, Alberto J. Espay MD, MSc orcid.org/0000-0002-3389-136X James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, Ohio, USASearch for more papers by this authorAndrew J. Lees FRCP, F.Med.Sci, PhD, Andrew J. Lees FRCP, F.Med.Sci, PhD Reta Lila Weston Institute of Neurological Studies, Department of Clinical Movement Disorder and Neuroscience, Institute of Neurology, University College London, London, United KingdomSearch for more papers by this author First published: 12 April 2023 https://doi.org/10.1002/mdc3.13746 Relevant disclosures and conflict of interest are listed at the end of this article. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL References 1Stephenson D, Badawy R, Mathur S, Tome M, Rochester L. Digital progression biomarkers as novel endpoints in clinical trials: a multistakeholder perspective. J Parkinsons Dis 2021; 11(s1): S103– S109. https://doi.org/10.3233/JPD-202428. 2Espay AJ, Hausdorff JM, Sánchez-Ferro Á, et al. A roadmap for implementation of patient-centered digital outcome measures in Parkinson's disease obtained using mobile health technologies. Mov Disord 2019; 34(5): 657– 663. https://doi.org/10.1002/mds.27671. 3Goetz CG, Tilley BC, Shaftman SR, et al. Movement Disorder Society-sponsored revision of the unified Parkinson's disease rating scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov Disord 2008; 23(15): 2129– 2170. https://doi.org/10.1002/mds.22340. 4Lipsmeier F, Taylor KI, Postuma RB, et al. Reliability and validity of the Roche PD Mobile application for remote monitoring of early Parkinson's disease. Sci Rep 2022; 12(1): 1– 15. https://doi.org/10.1038/s41598-022-15874-4. 5Woodrow H, Horne MK, Fernando CV, Kotschet KE, Treat to Target Study Group. A blinded, controlled trial of objective measurement in Parkinson's disease. npj Park Dis 2020; 6(1): 1– 10. https://doi.org/10.1038/s41531-020-00136-9. 6Zhan A, Mohan S, Tarolli C, et al. Using smartphones and machine learning to quantify Parkinson disease severity the mobile Parkinson disease score. JAMA Neurol 2018; 75(7): 876– 880. https://doi.org/10.1001/jamaneurol.2018.0809. 7Omberg L, Chaibub Neto E, Perumal TM, et al. Remote smartphone monitoring of Parkinson's disease and individual response to therapy. Nat Biotechnol 2021; 40: 480– 487. https://doi.org/10.1038/S41587-021-00974-9. 8Lo C, Arora S, Lawton M, et al. A composite clinical motor score as a comprehensive and sensitive outcome measure for Parkinson's disease. J Neurol Neurosurg Psychiatry 2022; 93(6): 617– 624. https://doi.org/10.1136/JNNP-2021-327880. 9Jha A, Menozzi E, Oyekan R, et al. The CloudUPDRS smartphone software in Parkinson's study: cross-validation against blinded human raters. npj Park Dis 2020; 6(1): 1– 8. https://doi.org/10.1038/s41531-020-00135-w. 10Rochester L, Mazzà C, Mueller A, et al. A roadmap to inform development, validation and approval of digital mobility outcomes: the mobilise-D approach. Digit Biomarkers 2020; 4(Suppl 1): 13– 27. https://doi.org/10.1159/000512513. 11Heldman DA, Espay AJ, LeWitt PA, Giuffrida JP. Clinician versus machine: reliability and responsiveness of motor endpoints in Parkinson's disease. Parkinsonism Relat Disord 2014; 20(6): 590– 595. https://doi.org/10.1016/J.PARKRELDIS.2014.02.022. 12Peto V, Jenkinson C, Fitzpatrick R, Greenhall R. The development and validation of a short measure of functioning and well being for individuals with Parkinson's disease. Qual Life Res 1995; 4(3): 241– 248. https://doi.org/10.1007/BF02260863. 13Chaudhuri KR, Martinez-Martin P, Brown RG, et al. The metric properties of a novel non-motor symptoms scale for Parkinson's disease: results from an international pilot study. Mov Disord 2007; 22(13): 1901– 1911. https://doi.org/10.1002/mds.21596. 14Powers R, Etezadi-Amoli M, Arnold EM, et al. Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinson's disease. Sci Transl Med 2021; 13(579): 1– 11. https://doi.org/10.1126/SCITRANSLMED.ABD7865. 15Elm JJ, Daeschler M, Bataille L, et al. Feasibility and utility of a clinician dashboard from wearable and mobile application Parkinson's disease data. NPJ Digit Med 2019; 2(1): 95. https://doi.org/10.1038/S41746-019-0169-Y. 16Roussos G, Herrero TR, Hill DL, et al. Identifying and characterising sources of variability in digital outcome measures in Parkinson's disease. NPJ Digit Med. 2022; 5(1): 93. https://doi.org/10.1038/S41746-022-00643-4. 17Manta C, Patrick-Lake B, Goldsack JC. Digital measures that matter to patients: a framework to guide the selection and development of digital measures of health. Digit Biomarkers 2020; 4(3): 69– 77. https://doi.org/10.1159/000509725. 18Badawy R, Hameed F, Bataille L, et al. Metadata concepts for advancing the use of digital health technologies in clinical research. Digit Biomarkers 2019; 3(3): 116– 132. https://doi.org/10.1159/000502951 19Vizcarra JA, Sánchez-Ferro Á, Maetzler W, et al. The Parkinson's disease e-diary: developing a clinical and research tool for the digital age. Mov Disord 2019; 34(5): 676– 681. https://doi.org/10.1002/MDS.27673. 20Steinhubl SR, Topol EJ. Digital medicine, on its way to being just plain medicine. npj Digit Med 2018; 1(1): 1– 1. https://doi.org/10.1038/s41746-017-0005-1. Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation" @default.
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