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Ilg W, Milne S, Schmitz-Hübsch T, Alcock L, Beichert L, Bertini E, Mohamed Ibrahim N, Dawes H, Gomez CM, Hanagasi H, Kinnunen KM, Minnerop M, Németh AH, Newman J, Ng YS, Rentz C, Samanci B, Shah VV, Summa S, Vasco G, McNames J, Horak FB. Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers. CEREBELLUM (LONDON, ENGLAND) 2024; 23:1566-1592. [PMID: 37955812 PMCID: PMC11269489 DOI: 10.1007/s12311-023-01625-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/20/2023] [Indexed: 11/14/2023]
Abstract
With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid, finely granulated, digital health measures are highly warranted to augment clinical and patient-reported outcome measures. Gait and balance disturbances most often present as the first signs of degenerative cerebellar ataxia and are the most reported disabling features in disease progression. Thus, digital gait and balance measures constitute promising and relevant performance outcomes for clinical trials.This narrative review with embedded consensus will describe evidence for the sensitivity of digital gait and balance measures for evaluating ataxia severity and progression, propose a consensus protocol for establishing gait and balance metrics in natural history studies and clinical trials, and discuss relevant issues for their use as performance outcomes.
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Affiliation(s)
- Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, Otfried-Müller-Straße 25, 72076, Tübingen, Germany.
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany.
| | - Sarah Milne
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, Melbourne University, Melbourne, VIC, Australia
- Physiotherapy Department, Monash Health, Clayton, VIC, Australia
- School of Primary and Allied Health Care, Monash University, Frankston, VIC, Australia
| | - Tanja Schmitz-Hübsch
- Experimental and Clinical Research Center, a cooperation of Max-Delbrueck Center for Molecular Medicine and Charité, Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Lisa Alcock
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne, UK
| | - Lukas Beichert
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Enrico Bertini
- Research Unit of Neuromuscular and Neurodegenerative Disorders, Bambino Gesu' Children's Research Hospital, IRCCS, Rome, Italy
| | | | - Helen Dawes
- NIHR Exeter BRC, College of Medicine and Health, University of Exeter, Exeter, UK
| | | | - Hasmet Hanagasi
- Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | | | - Martina Minnerop
- Institute of Neuroscience and Medicine (INM-1)), Research Centre Juelich, Juelich, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jane Newman
- NIHR Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne, UK
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle upon Tyne, UK
| | - Yi Shiau Ng
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle upon Tyne, UK
| | - Clara Rentz
- Institute of Neuroscience and Medicine (INM-1)), Research Centre Juelich, Juelich, Germany
| | - Bedia Samanci
- Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Vrutangkumar V Shah
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- APDM Precision Motion, Clario, Portland, OR, USA
| | - Susanna Summa
- Movement Analysis and Robotics Laboratory (MARLab), Neurorehabilitation Unit, Neurological Science and Neurorehabilitation Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Gessica Vasco
- Movement Analysis and Robotics Laboratory (MARLab), Neurorehabilitation Unit, Neurological Science and Neurorehabilitation Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - James McNames
- APDM Precision Motion, Clario, Portland, OR, USA
- Department of Electrical and Computer Engineering, Portland State University, Portland, OR, USA
| | - Fay B Horak
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- APDM Precision Motion, Clario, Portland, OR, USA
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Hermle D, Schubert R, Barallon P, Ilg W, Schüle R, Reilmann R, Synofzik M, Traschütz A. Multifeature quantitative motor assessment of upper limb ataxia including drawing and reaching. Ann Clin Transl Neurol 2024; 11:1097-1109. [PMID: 38590028 DOI: 10.1002/acn3.52024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/18/2024] [Accepted: 02/03/2024] [Indexed: 04/10/2024] Open
Abstract
OBJECTIVE Voluntary upper limb movements are an ecologically important yet insufficiently explored digital-motor outcome domain for trials in degenerative ataxia. We extended and validated the trial-ready quantitative motor assessment battery "Q-Motor" for upper limb movements with clinician-reported, patient-focused, and performance outcomes of ataxia. METHODS Exploratory single-center cross-sectional assessment in 94 subjects (46 cross-genotype ataxia patients; 48 matched controls), comprising five tasks measured by force transducer and/or position field: Finger Tapping, diadochokinesia, grip-lift, and-as novel implementations-Spiral Drawing, and Target Reaching. Digital-motor measures were selected if they discriminated from controls (AUC >0.7) and correlated-with at least one strong correlation (rho ≥0.6)-to the Scale for the Assessment and Rating of Ataxia (SARA), activities of daily living (FARS-ADL), and the Nine-Hole Peg Test (9HPT). RESULTS Six movement features with 69 measures met selection criteria, including speed and variability in all tasks, stability in grip-lift, and efficiency in Target Reaching. The novel drawing/reaching tasks best captured impairment in dexterity (|rho9HPT| ≤0.81) and FARS-ADL upper limb items (|rhoADLul| ≤0.64), particularly by kinematic analysis of smoothness (SPARC). Target hit rate, a composite of speed and endpoint precision, almost perfectly discriminated ataxia and controls (AUC: 0.97). Selected measures in all tasks discriminated between mild, moderate, and severe impairment (SARA upper limb composite: 0-2/>2-4/>4-6) and correlated with severity in the trial-relevant mild ataxia stage (SARA ≤10, n = 20). INTERPRETATION Q-Motor assessment captures multiple features of impaired upper limb movements in degenerative ataxia. Validation with key clinical outcome domains provides the basis for evaluation in longitudinal studies and clinical trial settings.
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Affiliation(s)
- Dominik Hermle
- Division Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
| | | | | | - Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany
| | - Rebecca Schüle
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Division of Neurodegenerative Disease, Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
- Department of Neurodegenerative Diseases, Center of Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Ralf Reilmann
- George-Huntington-Institute, Münster, Germany
- Department of Neurodegenerative Diseases, Center of Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Matthis Synofzik
- Division Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Andreas Traschütz
- Division Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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Fichera M, Nanetti L, Monelli A, Castaldo A, Marchini G, Neri M, Vukaj X, Marzorati M, Porcelli S, Mariotti C. Accelerometer-based measures in Friedreich ataxia: a longitudinal study on real-life activity. Front Pharmacol 2024; 15:1342965. [PMID: 38567352 PMCID: PMC10985256 DOI: 10.3389/fphar.2024.1342965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/28/2024] [Indexed: 04/04/2024] Open
Abstract
Quantitative measurement of physical activity may complement neurological evaluation and provide valuable information on patients' daily life. We evaluated longitudinal changes of physical activity in patients with Friedreich ataxia (FRDA) using remote monitoring with wearable sensors. We performed an observational study in 26 adult patients with FRDA and 13 age-sex matched healthy controls (CTR). Participants were asked to wear two wearable sensors, at non-dominant wrist and at waist, for 7 days during waking hours. Evaluations were performed at baseline and at 1-year follow-up. We analysed the percentage of time spent in sedentary or physical activities, the Vector Magnitude on the 3 axes (VM3), and average number of steps/min. Study participants were also evaluated with ataxia clinical scales and functional tests for upper limbs dexterity and walking capability. Baseline data showed that patients had an overall reduced level of physical activity as compared to CTR. Accelerometer-based measures were highly correlated with clinical scales and disease duration in FRDA. Significantly changes from baseline to l-year follow-up were observed in patients for the following measures: (i) VM3; (ii) percentage of sedentary and light activity, and (iii) percentage of Moderate-Vigorous Physical Activity (MVPA). Reduction in physical activity corresponded to worsening in gait score of the Scale for Assessment and Rating of Ataxia. Real-life activity monitoring is feasible and well tolerated by patients. Accelerometer-based measures can quantify disease progression in FRDA over 1 year, providing objective information about patient's motor activities and supporting the usefulness of these data as complementary outcome measure in interventional trials.
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Affiliation(s)
- Mario Fichera
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Lorenzo Nanetti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Alessia Monelli
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Anna Castaldo
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Gloria Marchini
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Marianna Neri
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Xhuljano Vukaj
- Institute of Biomedical Technologies, National Research Council, Segrate, Italy
| | - Mauro Marzorati
- Institute of Biomedical Technologies, National Research Council, Segrate, Italy
| | - Simone Porcelli
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Caterina Mariotti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
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Lang CE, Hoyt CR, Konrad JD, Bell KR, Marrus N, Bland MD, Lohse KR, Miller AE. Referent data for investigations of upper limb accelerometry: harmonized data from three cohorts of typically-developing children. Front Pediatr 2024; 12:1361757. [PMID: 38496366 PMCID: PMC10940427 DOI: 10.3389/fped.2024.1361757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 02/23/2024] [Indexed: 03/19/2024] Open
Abstract
Aim The rise of wearable sensing technology shows promise for addressing the challenges of measuring motor behavior in pediatric populations. The current pediatric wearable sensing literature is highly variable with respect to the number of sensors used, sensor placement, wearing time, and how data extracted from the sensors are analyzed. Many studies derive conceptually similar variables via different calculation methods, making it hard to compare across studies and clinical populations. In hopes of moving the field forward, this report provides referent upper limb wearable sensor data from accelerometers on 25 variables in typically-developing children, ages 3-17 years. Methods This is a secondary analysis of data from three pediatric cohorts of children 3-17 years of age. Participants (n = 222) in the cohorts wore bilateral wrist accelerometers for 2-4 days for a total of 622 recording days. Accelerometer data were reprocessed to compute 25 variables that quantified upper limb movement duration, intensity, symmetry, and complexity. Analyses examined the influence of hand dominance, age, gender, reliability, day-to-day stability, and the relationships between variables. Results The majority of variables were similar on the dominant and non-dominant sides, declined slightly with age, and were not different between boys and girls. ICC values were moderate to excellent. Variation within individuals across days generally ranged from 3% to 32%. A web-based R shiny object is available for data viewing. Interpretation With the use of wearable movement sensors increasing rapidly, these data provide key, referent information for researchers as they design studies, and analyze and interpret data from neurodevelopmental and other pediatric clinical populations. These data may be of particularly high value for pediatric rare diseases.
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Affiliation(s)
- Catherine E. Lang
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Catherine R. Hoyt
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States
| | - Jeffrey D. Konrad
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
| | - Kayla R. Bell
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
| | - Natasha Marrus
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Marghuretta D. Bland
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Keith R. Lohse
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Allison E. Miller
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
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Poleur M, Markati T, Servais L. The use of digital outcome measures in clinical trials in rare neurological diseases: a systematic literature review. Orphanet J Rare Dis 2023; 18:224. [PMID: 37533072 PMCID: PMC10398976 DOI: 10.1186/s13023-023-02813-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 07/07/2023] [Indexed: 08/04/2023] Open
Abstract
Developing drugs for rare diseases is challenging, and the precision and objectivity of outcome measures is critical to this process. In recent years, a number of technologies have increasingly been used for remote monitoring of patient health. We report a systematic literature review that aims to summarize the current state of progress with regard to the use of digital outcome measures for real-life motor function assessment of patients with rare neurological diseases. Our search of published literature identified 3826 records, of which 139 were included across 27 different diseases. This review shows that use of digital outcome measures for motor function outside a clinical setting is feasible and employed in a broad range of diseases, although we found few outcome measures that have been robustly validated and adopted as endpoints in clinical trials. Future research should focus on validation of devices, variables, and algorithms to allow for regulatory qualification and widespread adoption.
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Affiliation(s)
- Margaux Poleur
- Department of Neurology, Liege University Hospital Center, Liège, Belgium.
- Neuromuscular Reference Center, Division of Paediatrics University, Hospital University of Liège, Liège, Belgium.
- Centre de Référence des Maladies Neuromusculaires, Centre Hospitalier Régional de la Citadelle, Boulevard du 12eme de Ligne 1, 4000, Liège, Belgium.
| | - Theodora Markati
- MDUK Oxford Neuromuscular Centre and NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Laurent Servais
- MDUK Oxford Neuromuscular Centre and NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
- Neuromuscular Reference Center, Division of Paediatrics University, Hospital University of Liège, Liège, Belgium
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Grobe-Einsler M, Faber J, Taheri A, Kybelka J, Raue J, Volkening J, Helmhold F, Synofzik M, Klockgether T. SARA speech-Feasibility of automated assessment of ataxic speech disturbance. NPJ Digit Med 2023; 6:43. [PMID: 36927996 PMCID: PMC10020430 DOI: 10.1038/s41746-023-00787-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 02/24/2023] [Indexed: 03/18/2023] Open
Abstract
Ataxias are a group of movement disorders that are characterized by progressive loss of balance, impaired coordination and speech disturbance, which together lead to markedly reduced quality of life. Speech disturbance is clinically diagnosed, but methods for objective assessment of severity are lacking. Using 71 sets of speech recordings from ataxia patients, we developed an automated classification system. With a tolerance of ±1 point, this classification system correctly predicted experts' ratings of speech disturbance according to item 4 of the Scale for Assessment and rating of ataxia (SARA) in 80% of cases. We thereby demonstrate feasibility of computer-assisted voice analysis for automated assessment of severity of speech disturbance.
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Affiliation(s)
- M Grobe-Einsler
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. .,Department of Neurology, University Hospital Bonn, Bonn, Germany.
| | - J Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - A Taheri
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | | | - J Raue
- PeakProfiling GmbH, Berlin, Germany
| | | | | | - M Synofzik
- Division of Translational Genomics for Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University Tübingen, Tübingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - T Klockgether
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
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Liu J, Barrett JS, Leonardi ET, Lee L, Roychoudhury S, Chen Y, Trifillis P. Natural History and Real‐World Data in Rare Diseases: Applications, Limitations, and Future Perspectives. J Clin Pharmacol 2022; 62 Suppl 2:S38-S55. [PMID: 36461748 PMCID: PMC10107901 DOI: 10.1002/jcph.2134] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/28/2022] [Indexed: 12/04/2022]
Abstract
Rare diseases represent a highly heterogeneous group of disorders with high phenotypic and genotypic diversity within individual conditions. Due to the small numbers of people affected, there are unique challenges in understanding rare diseases and drug development for these conditions, including patient identification and recruitment, trial design, and costs. Natural history data and real-world data (RWD) play significant roles in defining and characterizing disease progression, final patient populations, novel biomarkers, genetic relationships, and treatment effects. This review provides an introduction to rare diseases, natural history data, RWD, and real-world evidence, the respective sources and applications of these data in several rare diseases. Considerations for data quality and limitations when using natural history and RWD are also elaborated. Opportunities are highlighted for cross-sector collaboration, standardized and high-quality data collection using new technologies, and more comprehensive evidence generation using quantitative approaches such as disease progression modeling, artificial intelligence, and machine learning. Advanced statistical approaches to integrate natural history data and RWD to further disease understanding and guide more efficient clinical study design and data analysis in drug development in rare diseases are also discussed.
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Affiliation(s)
- Jing Liu
- Pfizer, Inc.GrotonConnecticutUSA
| | - Jeffrey S. Barrett
- Critical Path InstituteRare Disease Cures Accelerator Data Analytics PlatformTucsonArizonaUSA
| | | | - Lucy Lee
- PTC Therapeutics, Inc.South PlainfieldNew JerseyUSA
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Clay I, Cormack F, Fedor S, Foschini L, Gentile G, van Hoof C, Kumar P, Lipsmeier F, Sano A, Smarr B, Vandendriessche B, De Luca V. Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint. J Med Internet Res 2022; 24:e35951. [PMID: 35617003 PMCID: PMC9185357 DOI: 10.2196/35951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/14/2022] [Accepted: 04/25/2022] [Indexed: 11/18/2022] Open
Abstract
The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities.
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Affiliation(s)
- Ieuan Clay
- Digital Medicine Society, Boston, MA, United States
| | | | | | | | | | | | | | | | - Akane Sano
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, United States
| | - Benjamin Smarr
- Department of Bioengineering and Halicioglu Data Science Institute, University of California, San Diego, San Diego, CA, United States
| | | | - Valeria De Luca
- Novartis Institutes for Biomedical Research, Basel, Switzerland
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