ABSTRACT
BACKGROUND: Chimeric antigen receptor (CAR) T-cell therapy and bispecific T-cell engagers, which redirect T-cells to tumor antigens, have immensely benefitted patients with relapsed/refractory B-cell cancers. How these therapies differ in cardiotoxicity is underexplored. We used the World Health Organization pharmacovigilance database, VigiBase, to compare cardiotoxicity profiles between CD19-targeted CAR-T therapy and blinatumomab (a CD19/CD3-targeted bispecific T-cell engager). METHODS: Safety reports in VigiBase were filtered for diffuse large B-cell lymphoma (DLBCL, n = 17,479) and acute lymphocytic leukemia (ALL, n = 28,803) for all adverse reactions. Data were further filtered for patients taking CAR-T therapy or blinatumomab. Reporting odds ratios (ROR) and fatality rates were compared between CAR-T cell products (e.g. tisagenlecleucel and axicabtagene ciloleucel), and between CAR-T therapy and blinatumomab. RESULTS: Tisagenlecleucel is associated with cardiac failure (IC025 = 0.366) with fatality rates of 85.7% and 80.0% in DLBCL and pediatric ALL patients respectively. For DLBCL patients, axicabtagene ciloleucel has greater reporting for hypotension than tisagenlecleucel (ROR: 2.54; 95% CI: 1.28-5.03; p = 0.012), but tisagenlecleucel has higher fatality rates for hypotension than axicabtagene ciloleucel [50.0% (tisagenlecleucel) vs 5.6% (axicabtagene ciloleucel); p < 0.001]. Blinatumomab and tisagenlecleucel have similar fatality rates for hypotension in pediatric ALL patients [34.7% (tisagenlecleucel) vs 20.0% (blinatumomab); p = 0.66]. CONCLUSIONS: Tisagenlecleucel is associated with severe and fatal adverse cardiac events, with higher fatality rates for hypotension compared to axicabtagene ciloleucel in DLBCL patients, but similar hypotension fatality rates compared to blinatumomab in pediatric ALL patients. Effective management necessitates experienced physicians, including cardio-oncologists, skilled in interdisciplinary approaches to manage these toxicities.
Chimeric antigen receptor (CAR) T-cell therapy and blinatumomab are two new types of cancer therapies used to treat blood cancers that fail to respond to conventional chemotherapy. Our goal is to study if there are major differences in how these treatments affect the heart. We analyzed a large, global database of patients who had these treatments. We find that in a blood cancer called diffuse large B-cell lymphoma, two CAR-T cell therapies are linked to heart failure and low blood pressure. In another type of cancer, acute lymphocytic leukemia, CAR-T cell therapy is associated with heart failure and cardiac arrest. The study suggests that given the frequency and severity of these side effects, clinical care should involve an interdisciplinary team experienced in managing these serious side effects.
ABSTRACT
Purpose: Ischemic myocardial scarring (IMS) is a common outcome of coronary artery disease that potentially leads to lethal arrythmias and heart failure. Late-gadolinium-enhanced cardiac magnetic resonance (CMR) imaging scans have served as the diagnostic bedrock for IMS, with recent advancements in machine learning enabling enhanced scar classification. However, the trade-off for these improvements is intensive computational and time demands. As a solution, we propose a combination of lightweight preprocessing (LWP) and template matching (TM) to streamline IMS classification. Approach: CMR images from 279 patients (151 IMS, 128 control) were classified for IMS presence using two convolutional neural networks (CNNs) and TM, both with and without LWP. Evaluation metrics included accuracy, sensitivity, specificity, F1-score, area under the receiver operating characteristic curve (AUROC), and processing time. External testing dataset analysis encompassed patient-level classifications (PLCs) and a CNN versus TM classification comparison (CVTCC). Results: LWP enhanced the speed of both CNNs (4.9x) and TM (21.9x). Furthermore, in the absence of LWP, TM outpaced CNNs by over 10x, while with LWP, TM was more than 100x faster. Additionally, TM performed similarly to the CNNs in accuracy, sensitivity, specificity, F1-score, and AUROC, with PLCs demonstrating improvements across all five metrics. Moreover, the CVTCC revealed a substantial 90.9% agreement. Conclusions: Our results highlight the effectiveness of LWP and TM in streamlining IMS classification. Anticipated enhancements to LWP's region of interest (ROI) isolation and TM's ROI targeting are expected to boost accuracy, positioning them as a potential alternative to CNNs for IMS classification, supporting the need for further research.