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Identifying and characterising sources of variability in digital outcome measures in Parkinson's disease.
Roussos, George; Herrero, Teresa Ruiz; Hill, Derek L; Dowling, Ariel V; L T M Müller, Martijn; Evers, Luc J W; Burton, Jackson; Derungs, Adrian; Fisher, Katherine; Kilambi, Krishna Praneeth; Mehrotra, Nitin; Bhatnagar, Roopal; Sardar, Sakshi; Stephenson, Diane; Adams, Jamie L; Ray Dorsey, E; Cosman, Josh.
Afiliação
  • Roussos G; Birkbeck College, University of London, London, UK. g.roussos@bbk.ac.uk.
  • Herrero TR; Bill and Melinda Gates Foundation, Seattle, WA, USA.
  • Hill DL; Panoramic Digital Health, Grenoble, France.
  • Dowling AV; Takeda, Deerfield, IL, USA.
  • L T M Müller M; Critical Path Institute, Tucson, AZ, USA.
  • Evers LJW; Radboud University Medical Center and Radboud University, Nijmegen, The Netherlands.
  • Burton J; Biogen, Cambridge, MA, USA.
  • Derungs A; Roche, Basel, Switzerland.
  • Fisher K; Biogen, Cambridge, MA, USA.
  • Kilambi KP; Biogen, Cambridge, MA, USA.
  • Mehrotra N; Alnylam Pharmaceuticals, Cambridge, MA, USA.
  • Bhatnagar R; Critical Path Institute, Tucson, AZ, USA.
  • Sardar S; Critical Path Institute, Tucson, AZ, USA.
  • Stephenson D; Critical Path Institute, Tucson, AZ, USA.
  • Adams JL; University of Rochester, Rochester, NY, USA.
  • Ray Dorsey E; University of Rochester, Rochester, NY, USA.
  • Cosman J; Abbvie, North Chicago, IL, USA.
NPJ Digit Med ; 5(1): 93, 2022 Jul 15.
Article em En | MEDLINE | ID: mdl-35840653
ABSTRACT
Smartphones and wearables are widely recognised as the foundation for novel Digital Health Technologies (DHTs) for the clinical assessment of Parkinson's disease. Yet, only limited progress has been made towards their regulatory acceptability as effective drug development tools. A key barrier in achieving this goal relates to the influence of a wide range of sources of variability (SoVs) introduced by measurement processes incorporating DHTs, on their ability to detect relevant changes to PD. This paper introduces a conceptual framework to assist clinical research teams investigating a specific Concept of Interest within a particular Context of Use, to identify, characterise, and when possible, mitigate the influence of SoVs. We illustrate how this conceptual framework can be applied in practice through specific examples, including two data-driven case studies.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article