Management of patients undergoing CAR-T cell therapy in Germany

Introduction: Chimeric antigen receptor positive T cell (CAR-T cell) treatment became standard therapy for relapsed or refractory hematologic malignancies, such as non-Hodgkin’s lymphoma and multiple myeloma. Owing to the rapidly progressing field of CAR-T cell therapy and the lack of generally accepted treatment guidelines, we hypothesized significant differences between centers in the prevention, diagnosis, and management of short- and long-term complications. Methods: To capture the current CAR-T cell management among German centers to determine the medical need and specific areas for future clinical research, the DAG-HSZT (Deutsche Arbeitsgemeinschaft für Hämatopoetische Stammzelltransplantation und Zelluläre Therapie; German Working Group for Hematopoietic Stem Cell Transplantation and Cellular Therapy) performed a survey among 26 German CAR-T cell centers. Results: We received answers from 17 centers (65%). The survey documents the relevance of evidence in the CAR-T cell field with a homogeneity of practice in areas with existing clinical evidence. In contrast, in areas with no – or low quality – clinical evidence, we identified significant variety in management in between the centers: management of cytokine release syndrome, immune effector cell-related neurotoxicity syndrome, IgG substitution, autologous stem cell backups, anti-infective prophylaxis, and vaccinations. Conclusion: The results indicate the urgent need for better harmonization of supportive care in CAR-T cell therapies including clinical research to improve clinical outcome

Allogeneic hematopoietic stem cell transplantation and pre-transplant strategies in patients with NPM1-mutated acute myeloid leukemia: a single center experience

Abstract Patients with acute myeloid leukemia (AML) and nucleophosmin 1 gene mutations (NPM1mut) show a favorable prognosis with chemotherapy (CT) in the absence of negative prognostic genetic abnormalities. Between 2008 and 2021 64 patients with NPM1mutAML received alloHSCT because of additional adverse prognostic factors (1st line), inadequate response to or relapse during or after CT (2nd line). To expand the evidence in alloTX in NPM1mut AML, clinical and molecular data were retrospectively analyzed with respect to pre-transplant strategies and outcome. Patients with minimal residual disease negative (MRD−) CR at transplant had better 2-y-PFS and 2-y-OS (77% and 88%) than patients with minimal residual disease positive (MRD+) CR (41% and 71%) or patients with active disease (AD) at transplant (20% and 52%). The 2nd line patients with relapse after completing CT responded well to high dose cytarabine based salvage chemotherapy (salvage CT) in contrast to patients relapsing while still on CT (90% vs 20%, P = 0.0170). 2-y-PFS and 2-y-OS was 86% in patients who achieved a 2nd MRD− CR pre alloHSCT. Outcome in NPM1mutAML depends on disease burden at alloHSCT. Time and type of relapse in relation to CT are predictive for response to salvage CT

Wearable based monitoring and self-supervised contrastive learning detect clinical complications during treatment of Hematologic malignancies

Abstract Serious clinical complications (SCC; CTCAE grade ≥ 3) occur frequently in patients treated for hematological malignancies. Early diagnosis and treatment of SCC are essential to improve outcomes. Here we report a deep learning model-derived SCC-Score to detect and predict SCC from time-series data recorded continuously by a medical wearable. In this single-arm, single-center, observational cohort study, vital signs and physical activity were recorded with a wearable for 31,234 h in 79 patients (54 Inpatient Cohort (IC)/25 Outpatient Cohort (OC)). Hours with normal physical functioning without evidence of SCC (regular hours) were presented to a deep neural network that was trained by a self-supervised contrastive learning objective to extract features from the time series that are typical in regular periods. The model was used to calculate a SCC-Score that measures the dissimilarity to regular features. Detection and prediction performance of the SCC-Score was compared to clinical documentation of SCC (AUROC ± SD). In total 124 clinically documented SCC occurred in the IC, 16 in the OC. Detection of SCC was achieved in the IC with a sensitivity of 79.7% and specificity of 87.9%, with AUROC of 0.91 ± 0.01 (OC sensitivity 77.4%, specificity 81.8%, AUROC 0.87 ± 0.02). Prediction of infectious SCC was possible up to 2 days before clinical diagnosis (AUROC 0.90 at −24 h and 0.88 at −48 h). We provide proof of principle for the detection and prediction of SCC in patients treated for hematological malignancies using wearable data and a deep learning model. As a consequence, remote patient monitoring may enable pre-emptive complication management

Feasibility of Wearable-Based Remote Monitoring in Patients During Intensive Treatment for Aggressive Hematologic Malignancies

PURPOSE Intensive treatment protocols for aggressive hematologic malignancies harbor a high risk of serious clinical complications, such as infections. Current techniques of monitoring vital signs to detect such complications are cumbersome and often fail to diagnose them early. Continuousmonitoring of vital signs and physical activity bymeans of an upper arm medical wearable allowing 24/7 streaming of such parameters may be a promising alternative. METHODS This single-arm, single-center observational trial evaluated symptom-related patient-reported outcomes and feasibility of a wearable-based remote patient monitoring. All wearable data were reviewed retrospectively and were not available to the patient or clinical staff. A total of 79 patients (54 inpatients and 25 outpatients) participated and received standard-of-care treatment for a hematologic malignancy. In addition, the wearable was continuously worn and self-managed by the patient to record multiple parameters such as heart rate, oxygen saturation, and physical activity. RESULTS Fifty-one patients (94.4%) in the inpatient cohort and 16 (64.0%) in the outpatient cohort reported gastrointestinal symptoms (diarrhea, nausea, and emesis), pain, dyspnea, or shivering in at least one visit. With the wearable, vital signs and physical activity were recorded for a total of 1,304.8 days. Recordings accounted for 78.0% (63.0-88.5; median [interquartile range]) of the potential recording time for the inpatient cohort and 84.6% (76.3-90.2) for the outpatient cohort. Adherence to the wearable was comparable in both cohorts, but decreased moderately over time during the trial. CONCLUSION A high adherence to the wearable was observed in patients on intensive treatment protocols for a hematologic malignancy who experience high symptom burden. Remote patient monitoring of vital signs and physical activity was demonstrated to be feasible and of primarily sufficient quality. (C) 2022 by American Society of Clinical Oncolog