Digital Biomarkers of Cytokine Release Syndrome: Scoping Review and Ontology Development of the Role and Relevance of Digital Measures Using a Mixed Methods Approach

Standardization and adoption of the ontology of early warning signs for CRS will streamline data collection to support the creation of robust, fit-for-purpose datasets. This approach ensures practical and informative data collection, ultimately enhancing the ability to predict and manage CRS effectively. Developing predictive models based on these early warning signs can enhance CRS risk assessment, support decentralized trials, and improve access to cancer-targeted immunotherapies.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2025-09-19
DOI
https://doi.org/10.2196/71956
Primary Topic
Advanced Biosensing Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Digital Biomarkers of Cytokine Release Syndrome: Scoping Review and Ontology Development of the Role and Relevance of Digital Measures Using a Mixed Methods Approach

David J. Zahavi, Dana L. Wolff‐Hughes, M. Chen, Erik Koenig et al.
Journal of Medical Internet Research
Advanced Biosensing Techniques and Applications
article

Digital Biomarkers of Cytokine Release Syndrome: Scoping Review and Ontology Development of the Role and Relevance of Digital Measures Using a Mixed Methods Approach

David J. Zahavi, Dana L. Wolff‐Hughes, M. Chen, Erik Koenig, Nunzio Camerlingo, Cindy Varga, Jenifer Siegelman, Mark Stewart, Robert W. Phillips, Nazila Shafagati, C Marquez, Matt Wilkes, Benjamin Vandendriessche, Charlotte Zoe Angel, Samantha J. McClenahan, Ujwani Nukala, Ashita S. Batavia, Sarah K. Bradley, Daniel P. Sanchez, Christopher J Medberry, Lieke Kusters, Michael Pettinati, Sylvain Zorman, Mohamed Datoo, Premal Kamdar
article en

Abstract

Standardization and adoption of the ontology of early warning signs for CRS will streamline data collection to support the creation of robust, fit-for-purpose datasets. This approach ensures practical and informative data collection, ultimately enhancing the ability to predict and manage CRS effectively. Developing predictive models based on these early warning signs can enhance CRS risk assessment, support decentralized trials, and improve access to cancer-targeted immunotherapies.

Journal of Medical Internet ResearchVol. 27
Roche (Switzerland) (CH), Center for Biologics Evaluation and Research (US), United States Food and Drug Administration (US), Johnson & Johnson (United States) (US), Pfizer (United States) (US), Bristol-Myers Squibb (United States) (US), Levine Cancer Institute (US), Digital Science (United States) (US), Pensacola Historical Society (US), Takeda (United States) (US), National Cancer Institute (US), Blueroof Technologies (United States) (US), Sidney Kimmel Comprehensive Cancer Center (US), Case Western Reserve University (US), ILC Dover (United States) (US), Friends of Cancer Research (US)
Openalex Percentile: Top 64%
Advanced Biosensing Techniques and Applications
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