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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. [ABSTRACT FROM AUTHOR]

Simple Summary: Allogeneic stem cell transplantation (aHSCT) is the only potentially curative treatment option for patients with high-risk myeloid malignancies. Depending on the underlying genetic risk profile, up to 50% of patients die of relapse even after aHSCT in first remission. Therefore, further improvement of conditioning regimens is an urgent medical need. Current sequential conditioning regimens combine intensive AML-like induction therapy with total body irradiation or alkylators like treosulfan or melphalan. The first and currently widely accepted prototype of this treatment strategy is the fludarabine/amsacrine/ara-C (FLAMSA) protocol, which has been modified multiple times by changing parts or adding additional cytotoxic drugs to improve clinical results. Knowing that venetoclax, an inhibitor of B-cell lymphoma-2 protein (BCL2), has synergistic effects to chemotherapy without increasing the level of non-hematologic toxicity, several German transplant centers have added venetoclax to the FLAMSA protocol as an individualized treatment approach to improve long term outcome in patients with high-risk myeloid malignancies. Up to 50% of patients with high-risk myeloid malignancies die of relapse after allogeneic stem cell transplantation. Current sequential conditioning regimens like the FLAMSA protocol combine intensive induction therapy with TBI or alkylators. Venetoclax has synergistic effects to chemotherapy. In a retrospective survey among German transplant centers, we identified 61 patients with myeloid malignancies that had received FLAMSA-based sequential conditioning with venetoclax between 2018 and 2022 as an individualized treatment approach. Sixty patients (98%) had active disease at transplant and 74% had genetic high-risk features. Patients received allografts from matched unrelated, matched related, or mismatched donors. Tumor lysis syndrome occurred in two patients but no significant non-hematologic toxicity related to venetoclax was observed. On day +30, 55 patients (90%) were in complete remission. Acute GvHD II°–IV° occurred in 17 (28%) and moderate/severe chronic GvHD in 7 patients (12%). Event-free survival and overall survival were 64% and 80% at 1 year as well as 57% and 75% at 2 years, respectively. The off-label combination of sequential FLAMSA-RIC with venetoclax appears to be safe and highly effective. To further validate these insights and enhance the idea of smart conditioning, a controlled prospective clinical trial was initiated in July 2023. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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., (© 2023. The Author(s).)