Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 11, 2025
Date Accepted: Sep 19, 2025
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Digital biomarkers of Cytokine Release Syndrome: A Scoping review of the role and relevance of digital measures
ABSTRACT
Background:
Rapid advancements in cancer-targeted immunotherapies have transformed care, yet these therapies present a high likelihood of cytokine release syndrome (CRS), a potentially severe immune-related adverse event. The ability to accurately identify CRS earlier could improve care by mitigating risks, widening patient access by removing treatment barriers and reducing the burden on patients, caregivers, and healthcare providers. While the number of studies focused on CRS detection has been increasing, inconsistencies in the symptoms and measures most strongly associated with CRS highlight the urgent need for a comprehensive review to identify the most reliable and commonly reported indicators. Despite this growing body of research, reliable predictive and diagnostic measures for early warning for CRS following the administration of immunotherapy have yet to be established.
Objective:
This scoping review aims to address this gap by developing an ontology of early warning signs for CRS – a structured model defining measurement concepts, properties, and interrelationships – for advancing early warning models for CRS.
Methods:
We reviewed articles from PubMed and Embase that detailed measures collected between therapy administration and CRS onset and demonstrated a relationship between the measure and the development of CRS. Studies were limited to publications between January 2014 and March 2024 excluding those that did not assess an immunotherapy-based treatment, were not conducted in humans, did not compare collected measures to CRS diagnosed using standard of care, or were not available in English. Identified measures were further assessed through surveys and interviews with subject matter experts and key opinion leaders, respectively.
Results:
A comprehensive ontology of early warning signs for CRS that includes physiological signs, clinical symptoms, and laboratory markers was developed. Within the full ontology, a common set of early warning signs for CRS - temperature, heart rate, blood pressure, and oxygen saturation - was identified as the minimally necessary data to evaluate for their predictive value for CRS. Three of these four signs align with the American Society for Transplantation and Cellular Therapy criteria for CRS grading.
Conclusions:
Standardization and adoption of the concepts and their values in the ontology of early warning signs for CRS will streamline data collection to support the creation of robust, fit-for-purpose datasets. This approach aims to ensure 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.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.