Atrial arrhythmias following CAR-chimeric antigen receptor T-cell therapy: Incidence, risk factors and biomarker profile.

Recent reports have raised concerns about the association of chimeric antigen receptor T cell (CAR-T) with non-negligible cardiotoxicity, particularly atrial arrhythmias. First, we conducted a pharmacovigilance study to assess the reporting of atrial arrhythmias following CD19-directed CAR-T. Subsequently, to determine the incidence, risk factors and outcomes of atrial arrhythmias post-CAR-T, we compiled a retrospective single-centre cohort of non-Hodgkin lymphoma patients. Only commercial CAR-T products were considered. Atrial arrhythmias were nearly fourfold more likely to be reported after CAR-T therapy compared to all other cancer patients in the FAERS (adjusted ROR = 3.76 [95% CI 2.67-5.29]). Of the 236 patients in our institutional cohort, 23 (10%) developed atrial arrhythmias post-CAR-T, including 12 de novo arrhythmias, with most (83%) requiring medical intervention. Atrial arrhythmias frequently co-occurred with cytokine release syndrome and were associated with higher post-CAR-T infusion peak levels of IL-10, TNF-alpha and LDH, and lower trough levels of fibrinogen. In a multivariable analysis, risk factors for atrial arrhythmia were history of atrial arrhythmia (OR = 6.80 [2.39-19.6]) and using CAR-T product with a CD28-costimulatory domain (OR = 5.17 [1.72-18.6]). Atrial arrhythmias following CD19-CAR-T therapy are prevalent and associated with elevated inflammatory biomarkers, a history of atrial arrhythmia and the use of a CAR-T product with a CD28 costimulatory domain.

Moving towards establishing centres of excellence in cardiac amyloidosis: an International Cardio-Oncology Society statement.

The prevalence of amyloidosis has been increasing, driven by a combination of improved awareness, evolution of diagnostic pathways, and effective treatment options for both transthyretin and light chain amyloidosis. Due to the complexity of amyloidosis, centralised expert providers with experience in delineating the nuances of confirmatory diagnosis and management may be beneficial. There are many potential benefits of a centre of excellence designation for the treatment of amyloidosis including recognition of institutions that have been leading the way for the optimal treatment of this condition, establishing the expectations for any centre who is engaging in the treatment of amyloidosis and developing cooperative groups to allow more effective research in this disease space. Standardising the expectations and criteria for these centres is essential for ensuring the highest quality of clinical care and community education. In order to define what components are necessary for an effective centre of excellence for the treatment of amyloidosis, we prepared a survey in cooperation with a multidisciplinary panel of amyloidosis experts representing an international consortium. The purpose of this position statement is to identify the essential elements necessary for highly effective clinical care and to develop a general standard with which practices or institutions could be recognised as a centre of excellence.

Artificial Intelligence Enabled Interpretation of ECG Images to Predict Hematopoietic Cell Transplantation Toxicity.

Artificial intelligence enabled interpretation of electrocardiogram waveform images (AI-ECG) can identify patterns predictive of future adverse cardiac events. We hypothesized such an approach, which is well described in general medical and surgical patients, would provide prognostic information with respect to the risk of cardiac complications and overall mortality in patients undergoing hematopoietic cell transplantation (HCT) for blood malignancy. We retrospectively subjected ECGs obtained pre-HCT to an externally trained, deep learning model designed to predict risk of atrial fibrillation (AF). Included were 1,377 patients (849 autologous HCT and 528 allogeneic HCT recipients). Median follow-up was 2.9 years. The three-year cumulative incidence of AF was 9% (95% CI: 7-12%) in autologous HCT patients and 13% (10-16%) in allogeneic HCT patients. In the entire cohort, pre-HCT AI-ECG estimate of AF risk correlated highly with development of clinical AF (Hazard Ratio (HR) 7.37, 3.53-15.4, p <0.001), inferior overall survival (HR: 2.4; 1.3-4.5, p = 0.004), and greater risk of non-relapse mortality (HR 3.36, 1.39-8.13, p = 0.007), without increased risk of relapse. Significant associations with mortality were only noted in allo HCT recipients, where the risk of non-relapse mortality was greater. Compared to calcineurin inhibitor-based graft versus host disease prophylaxis, the use of post-transplantation cyclophosphamide resulted in greater 90-day incidence of AF (13% versus 5%, p = 0.01), corresponding to temporal changes in AI-ECG AF prediction post HCT. In summary, AI-ECG can inform risk of post-transplant cardiac outcomes and survival in HCT patients and represents a novel strategy for personalized risk assessment after HCT.