ArticleFrontiers in immunology2024
Identification of early predictive biomarkers for severe cytokine release syndrome in pediatric patients with chimeric antigen receptor T-cell therapy.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction models for CAR-T Cell therapy-related adverse events in hematologic malignancies: a systematic review and meta-analysis.BMC cancer · 2026Pooled it
- Dose Optimization of Elranatamab to Mitigate the Risk of Cytokine Release Syndrome in Patients with Multiple Myeloma.Targeted oncology · 2025Trial
- Predictive Models for Toxicities after CAR T-cell Therapy: Challenges and Opportunities.Blood cancer discovery · 2026Review
- Review
- Admission Criteria to Paediatric Intensive Care for Oncology Haematology Patients: Updates and Evidence-Based Clinical Recommendations.Pediatric reports · 2026Review
- Beyond the infusion: nursing at the vanguard of cytokine release syndrome rescue in CAR-T cell therapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Low reticulocyte count at infusion is a risk factor for high-grade cytokine release syndrome in chimeric antigen receptor T cell therapy.International journal of hematology · 2026Article
- Anti-CD19 CAR T-cell therapy for autoimmune diseases: from exploratory clinical trials to quantitative pharmacodynamic modeling development.Frontiers in immunology · 2026Review
- Cytokine release syndrome in solid tumours: mechanism-based therapeutic strategies for prevention and management.Therapeutic advances in medical oncology · 2026Review
- The future directions of CAR-T Cell therapy: unlocking the potential of immunotherapy in cancer treatment.Frontiers in molecular medicine · 2026Review
- Repurposing mitochondrial-targeting drugs for management of ICANS in CAR T-cell therapy: a novel steroid-sparing approach.Frontiers in pharmacology · 2026Article
- Predictive markers for the efficacy of CAR T-cell therapy: the interplay between CAR T-cell fitness and systemic immunity.Blood advances · 2025Review
- Digital Biomarkers of Cytokine Release Syndrome: Scoping Review and Ontology Development of the Role and Relevance of Digital Measures Using a Mixed Methods Approach.Journal of medical Internet research · 2025Article
- A Novel Early Memory-Enriched Allogeneic NKG2D CAR-T Cell Therapy Based on CRISPR/Cas9 Technology for Solid Tumors.Cancers · 2025Article
- Immunomodulatory Effects of Curcumin on CAR T-Cell Therapy.Antioxidants (Basel, Switzerland) · 2025Article
- Immune effector cell-associated neurotoxicity syndrome: integrative mechanisms, predictive biomarkers, and translational pathways for prevention in CAR T-cell therapy.Frontiers in neurologyReview
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CAR-T cell therapy is a revolutionary new treatment for hematological malignancies, but it can also result in significant adverse effects, with cytokine release syndrome (CRS) being the most common and potentially life-threatening. The identification of biomarkers to predict the severity of CRS is crucial to ensure the safety and efficacy of CAR-T therapy. To achieve this goal, we characterized the expression profiles of seven cytokines, four conventional biochemical markers, and five hematological markers prior to and following CAR-T cell infusion. Our results revealed that IL-2, IFN-γ, IL-6, and IL-10 are the key cytokines for predicting severe CRS (sCRS). Notably, IL-2 levels rise at an earlier stage of sCRS and have the potential to serve as the most effective cytokine for promptly detecting the condition's onset. Furthermore, combining these cytokine biomarkers with hematological factors such as lymphocyte counts can further enhance their predictive performance. Finally, a predictive tree model including lymphocyte counts, IL-2, and IL-6 achieved an accuracy of 85.11% (95% CI = 0.763-0.916) for early prediction of sCRS. The model was validated in an independent cohort and achieved an accuracy of 74.47% (95% CI = 0.597-0.861). This new prediction model has the potential to become an effective tool for assessing the risk of CRS in clinical practice.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.