[en] [en] BACKGROUND: Digital mobility outcomes (DMOs) have emerged as novel biomarkers offering objective, quantitative, and examiner-independent outcome measures for clinical studies. Unfortunately, research efforts on DMOs have not yet investigated the domain of clinical utility in Parkinson's disease, i.e. providing evidence of improvements in health outcomes, diagnosis, decision-making, or prevention when compared to e.g. standard-of-care procedures. This manuscript, via a consensus building approach, aims to create a structured conceptual framework to map the knowledge generated by DMOs with clinical domains that could benefit from it.
METHODS: We conducted a three-round consensus-building study with 12 experts recruited from the Mobilise-D consortium's Parkinson's Disease Working Group. The experts designed and ranked different aspects of the conceptual framework via a 5-level Likert scale for level of agreement. Consensus for the different points evaluated was based on a double threshold: the simultaneous presence of a high level of agreement had to be accompanied by a low level of disagreement. As secondary objectives, the experts were asked to rate the practical application of DMOs by evaluating the timeline to applicability, the foreseen challenges for their implementation in clinical settings, and their main role in the decision-making process.
RESULTS: A full consensus on the clinical utility framework was achieved after three rounds. The final framework consisted of three main categories (Disease Diagnosis, Patient Evaluation, and Treatment Evaluation) and six underlying domains (Enhancing Diagnostic Procedure, Predicting Risk, Timely Detecting Deterioration, Enhancing Clinical Judgment, Selecting Treatment, and Monitoring Treatment Response). The experts believed in the next 1-5 years DMOs will play a relevant role in clinical decision making, complementing care knowledge with useful digital biomarkers information. However, the main challenge to address is the definition of clear reference value for DMOs interpretability.
CONCLUSIONS: This framework provides a structure for subsequent studies to build into by diversifying expert cohorts and expand our findings beyond PD. Additionally, our results support researchers planning future clinical trials where DMOs can play a valuable role for clinical decision support. Ultimately, this is the first step toward developing guidelines to assess DMOs' clinical utility and support their integration into Real World clinical practice.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
CASTRO MEJIA, Alan ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Digital Medicine
SAPIENZA, Stefano ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Digital Medicine
PACCOUD, Ivana ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Digital Medicine > Team Jochen KLUCKEN
Alcock, Lisa; NIHR Newcastle Biomedical Research Centre, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK ; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
Brown, Philip; The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
Gaßner, Heiko; Department of Molecular Neurology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany ; Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany
Hunter, Heather; The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
Maetzler, Walter; Department of Neurology, University Hospital Schleswig-Holstein and Kiel University, Kiel, Germany
Mirelman, Anat; Laboratory for Early Markers of Neurodegeneration (LEMON), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel ; School of Medicine & Health Sciences, Tel Aviv University, Tel Aviv, Israel ; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
Nieuwboer, Alice; Neurorehabilitation Research Group (eNRGy), Department of Rehabilitation Sciences, KU Leuven, Leuven, Vlaams-Brabant, Belgium ; Leuven Brain Institute (LBI), Leuven, Belgium
Regensburger, Martin; Department of Molecular Neurology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Rochester, Lynn; NIHR Newcastle Biomedical Research Centre, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK ; The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK ; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
Stallforth, Sabine; Department of Molecular Neurology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Vereijken, Beatrix; Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
Yarnall, Alison; NIHR Newcastle Biomedical Research Centre, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK ; The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
KLUCKEN, Jochen ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Digital Medicine ; Centre Hospitalier de Luxembourg, Luxembourg City, Luxembourg
Fonds National de la Recherche Luxembourg Innovative Medicines Initiative NIHR Newcastle Biomedical Research Centre Deutsche Forschungsgemeinschaft Fraunhofer Internal Programs
Funding text :
This paper presents independent research supported by the NIHR Newcastle Biomedical Research Centre (BRC). The NIHR Newcastle Biomedical Research Centre (BRC) is a partnership between Newcastle Hospitals NHS Foundation Trust, Newcastle University, and Cumbria, Northumberland and Tyne and Wear NHS Foundation Trust and is funded by the National Institute for Health and Care Research (NIHR).Research was supported by the Mobilise-D project, which received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 820820. This Joint Undertaking receives support from the European Union\u2019s Horizon 2020 research and innovation programme and EFPIA.Heiko Gassner is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) \u2013 SFB 1483 \u2013 Project-ID 442419336, EmpkinS. and Project-ID 438496663, Mobility_APP. He is further supported by the Fraunhofer Internal Programs under Grant No. Attract 044-602140 and 044-602150 as well as Grant No. SME 40-09311.Lynn Rochester, Lisa Alcock, Alison Yarnall are supported by funding from the National Institute for Health and Care Research (NIHR) Senior Investigator Awards (2020\u20132024; 2024\u20132028); and the NIHR Newcastle Biomedical Research Centre (BRC), the NIHR/Wellcome Trust Clinical Research Facility (CRF) infrastructure at Newcastle upon Tyne Hospitals NHS Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.This research was funded in whole, or in part, by the Luxembourg National Research Fund (FNR), grant reference 14146272 & 17981757. For the purpose of open access, and in fulfilment of the obligations arising from the grant agreement, the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission.
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