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Record W4396613915 · doi:10.51731/cjht.2024.884

Anticytokine Therapy and Corticosteroids for Cytokine Release Syndrome and for Neurotoxicity Following T-Cell Engager or CAR T-Cell Therapy

2024· article· en· W4396613915 on OpenAlexaboutno aff
CADTH

Bibliographic record

VenueCanadian Journal of Health Technologies · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsCytokine release syndromeMedicineAnakinraInternal medicineOncologyChimeric antigen receptorT cellImmunologyImmune system

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.345
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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