Cardiotoxicity Associated With Chimeric Antigen Receptor (CAR)-T Cell Therapy for Hematologic Malignancies: A Systematic Review
Bibliographic record
Abstract
Chimeric Antigen Receptor (CAR)-T cell therapy has been one of the most important breakthroughs for treating hematologic malignancies. On the other hand, the therapy had many toxicities. One of the toxicities of the CAR-T therapy is cardiotoxicity. The goal of the systematic review is to elaborate on the cardiotoxicities related to CAR-T therapy for hematologic malignancies. The systematic review is following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) 2020 guidelines. The systematic search was done using PubMed, PubMed Central (PMC), Google Scholar, Cochrane Library, ScienceDirect, and clinicaltrial.gov. The search and selection of studies were done on April 28, 2022, and May 6, 2022, respectively. The studies were selected based upon participants, intervention, and outcomes (PIO) elements and the articles that were included were, full-text articles published within the last ten years, clinical trials, meta-analyses, randomized controlled trial, review, and systematic review. The exclusion criteria were non-hematologic malignancy, non-English-language articles. The initial search had 2,159 publications. The publications were assessed with assessment tools of Scale of the Assessment of Narrative Review Articles (SANRA), Newcastle-Ottawa Scale (NCOS), and Cochrane Collaboration Risk of Bias Tool (CCRBT), which led to selection of eight publications. The systematic review concludes that cardiotoxicity happened in adults and pediatric patients receiving the CAR-T cell therapy and that those cardiac adverse events had many risk factors. Therefore, monitoring these cardiotoxicities is highly essential.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".