Anticytokine Therapy and Corticosteroids for Cytokine Release Syndrome and for Neurotoxicity Following T-Cell Engager or CAR T-Cell Therapy
Bibliographic record
Abstract
What Is the Issue? Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) are the most common toxicities secondary to T-cell engager or chimeric antigen receptor (CAR) T-cell therapy. The US FDA and Health Canada approved tocilizumab, an anti-interleukin-6 receptor antagonist, for the management of severe or life-threatening cases of CRS. Corticosteroids also play an important role in CRS management and are the mainstay of ICANS management. Decision-makers are interested in understanding the use of anticytokine drugs (i.e., tocilizumab, anakinra, siltuximab) and/or corticosteroids in the management of CRS and ICANS following T-cell engager or CAR T-cell therapy. What Did We Do? We identified and summarized the literature comparing the clinical effectiveness and safety of anticytokine therapy and/or corticosteroids with alternative care or treatment as usual for treating and preventing of CRS and ICANS. We also searched for evidence-based recommendations for the use of anticytokine therapy and/or corticosteroids to treat and prevent CRS and ICANS. A research information specialist conducted a literature search of peer-reviewed and grey literature sources published between January 1, 2019 and February 26, 2024 for CRS; and between January 1, 2019 and March 4, 2024 for ICANS. One reviewer screened citations for inclusion based on predefined criteria, critically appraised the included studies, and narratively summarized the findings. What Did We Find? This report presents evidence-based findings on 3 retrospective chart review studies, 2 prospective cohort studies, and 4 consensus guidelines. Limited and low-quality clinical evidence from studies with a high risk of bias suggested that early use of tocilizumab or corticosteroids, or prophylactic use of tocilizumab or anakinra may reduce the risk of a high-grade CRS without a negative impact on neurotoxicity or immunotherapy treatment outcomes. The included guidelines recommend the use of tocilizumab for treatment of higher-grade CRS, or for treatment of grade 1 CRS if symptoms persist for 3 days or more. Corticosteroids could be added in conjunction if there is no improvement or persistent symptoms after tocilizumab therapy. For the management of ICANS in the absence of concurrent CRS, supportive care is the preferred treatment option for grade 1 ICANS, while corticosteroids are recommended for the management of grade 2 to 4 ICANS. In the presence of concurrent CRS, guidelines recommend tocilizumab therapy as per management of CRS, and corticosteroids should be continued until improvement to grade 1. We did not identify any clinical evidence regarding the clinical efficacy and safety of anticytokine therapy and/or corticosteroids for treatment of CRS and ICANS compared with alternative treatment or treatment as usual. We also did not identify any guidelines for the use of prophylactic anticytokine therapy, corticosteroids, or both for the prevention of CRS and ICANS. What Does This Mean? Despite limited and low-quality evidence, the findings suggest some potential benefits of prophylactic or early use of anticytokine therapy and corticosteroids for the management of immunotherapy-related toxicities. Guidelines offer guidance on the management of CRS, ICANS and other less common toxicities related to immunotherapy based on the available low-quality evidence. When using the clinical evidence and recommendations summarized in this report to inform decisions, decision-makers should consider that the evidence is limited and of low quality. To improve the certainty of findings, there is a need for more robust prospective clinical trials with larger sample sizes, and lower risk of bias.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.026 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".