0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Definitions of digital biomarkers: a systematic mapping of the biomedical literature

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Technological devices such as smartphones, wearables and virtual assistants enable health data collection, serving as digital alternatives to conventional biomarkers. We aimed to provide a systematic overview of emerging literature on ‘digital biomarkers,’ covering definitions, features and citations in biomedical research.

          Methods

          We analysed all articles in PubMed that used ‘digital biomarker(s)’ in title or abstract, considering any study involving humans and any review, editorial, perspective or opinion-based articles up to 8 March 2023. We systematically extracted characteristics of publications and research studies, and any definitions and features of ‘digital biomarkers’ mentioned. We described the most influential literature on digital biomarkers and their definitions using thematic categorisations of definitions considering the Food and Drug Administration Biomarkers, EndpointS and other Tools framework (ie, data type, data collection method, purpose of biomarker), analysing structural similarity of definitions by performing text and citation analyses.

          Results

          We identified 415 articles using ‘digital biomarker’ between 2014 and 2023 (median 2021). The majority (283 articles; 68%) were primary research. Notably, 287 articles (69%) did not provide a definition of digital biomarkers. Among the 128 articles with definitions, there were 127 different ones. Of these, 78 considered data collection, 56 data type, 50 purpose and 23 included all three components. Those 128 articles with a definition had a median of 6 citations, with the top 10 each presenting distinct definitions.

          Conclusions

          The definitions of digital biomarkers vary significantly, indicating a lack of consensus in this emerging field. Our overview highlights key defining characteristics, which could guide the development of a more harmonised accepted definition.

          Related collections

          Most cited references45

          • Record: found
          • Abstract: found
          • Article: not found

          A typology of reviews: an analysis of 14 review types and associated methodologies.

          The expansion of evidence-based practice across sectors has lead to an increasing variety of review types. However, the diversity of terminology used means that the full potential of these review types may be lost amongst a confusion of indistinct and misapplied terms. The objective of this study is to provide descriptive insight into the most common types of reviews, with illustrative examples from health and health information domains. Following scoping searches, an examination was made of the vocabulary associated with the literature of review and synthesis (literary warrant). A simple analytical framework -- Search, AppraisaL, Synthesis and Analysis (SALSA) -- was used to examine the main review types. Fourteen review types and associated methodologies were analysed against the SALSA framework, illustrating the inputs and processes of each review type. A description of the key characteristics is given, together with perceived strengths and weaknesses. A limited number of review types are currently utilized within the health information domain. Few review types possess prescribed and explicit methodologies and many fall short of being mutually exclusive. Notwithstanding such limitations, this typology provides a valuable reference point for those commissioning, conducting, supporting or interpreting reviews, both within health information and the wider health care domain.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            The Delphi method as a research tool: an example, design considerations and applications

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A clinical case definition of post-COVID-19 condition by a Delphi consensus

              People with COVID-19 might have sustained postinfection sequelae. Known by a variety of names, including long COVID or long-haul COVID, and listed in the ICD-10 classification as post-COVID-19 condition since September, 2020, this occurrence is variable in its expression and its impact. The absence of a globally standardised and agreed-upon definition hampers progress in characterisation of its epidemiology and the development of candidate treatments. In a WHO-led Delphi process, we engaged with an international panel of 265 patients, clinicians, researchers, and WHO staff to develop a consensus definition for this condition. 14 domains and 45 items were evaluated in two rounds of the Delphi process to create a final consensus definition for adults: post-COVID-19 condition occurs in individuals with a history of probable or confirmed SARS-CoV-2 infection, usually 3 months from the onset, with symptoms that last for at least 2 months and cannot be explained by an alternative diagnosis. Common symptoms include, but are not limited to, fatigue, shortness of breath, and cognitive dysfunction, and generally have an impact on everyday functioning. Symptoms might be new onset following initial recovery from an acute COVID-19 episode or persist from the initial illness. Symptoms might also fluctuate or relapse over time. A separate definition might be applicable for children. Although the consensus definition is likely to change as knowledge increases, this common framework provides a foundation for ongoing and future studies of epidemiology, risk factors, clinical characteristics, and therapy.
                Bookmark

                Author and article information

                Journal
                BMJ Health Care Inform
                BMJ Health Care Inform
                bmjhci
                bmjhci
                BMJ Health & Care Informatics
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2632-1009
                2024
                8 April 2024
                : 31
                : 1
                : e100914
                Affiliations
                [1 ]departmentDepartment of Applied Natural Sciences , Technische Hochschule Lübeck , Lübeck, Germany
                [2 ]departmentPragmatic Evidence Lab, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) , Ringgold_27209University Hospital Basel and University of Basel , Basel, Switzerland
                [3 ]departmentDepartment of Clinical Research , University Hospital Basel and University of Basel , Basel, Switzerland
                [4 ]departmentDepartment of Health , Eastern Switzerland University of Applied Sciences , St.Gallen, Switzerland
                [5 ]departmentDepartment of Neurology and MS Center , University Hospital Basel and University of Basel , Basel, Switzerland
                [6 ]departmentMeta-Research Innovation Center at Stanford (METRICS) , Stanford University , Stanford, California, USA
                [7 ]departmentMeta-Research Innovation Center Berlin (METRIC-B) , Berlin Institute of Health , Berlin, Germany
                Author notes
                [Correspondence to ] Dr Lars G Hemkens; lars.hemkens@ 123456usb.ch
                Author information
                http://orcid.org/0000-0001-6589-3936
                Article
                bmjhci-2023-100914
                10.1136/bmjhci-2023-100914
                11015196
                38589213
                dcfb4396-b4ba-4177-88f2-aa9f00ead84a
                © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                History
                : 27 September 2023
                : 06 March 2024
                Categories
                Review
                1506
                Custom metadata
                unlocked

                medical informatics
                medical informatics

                Comments

                Comment on this article