Thrombotic and hemorrhagic complications in children and young adult recipients of Hematopoietic Stem Cell Transplant (HSCT)

Machine learning algorithm as a prognostic tool for venous thromboembolism in allogeneic transplant patients

As a serious complication after allogenic hematopoietic stem cell transplantation (allo-HSCT), venous thromboembolism (VTE) is significantly related to increased nonrelapse mortality. Therefore distinguishing patients at high risk of death who should receive specific therapeutic management is key to improving survival. This study aimed to establish a machine learning-based prognostic model for the identification of post-transplantation VTE patients who have a high risk of death. We retrospectively evaluated 256 consecutive VTE patients who underwent allo-HSCT at our center between 2008 and 2019. These patients were further randomly divided into (1) a derivation (80%) cohort of 205 patients and (2) a test (20%) cohort of 51 patients. The least absolute shrinkage and selection operator (LASSO) approach was used to choose the potential predictors from the primary dataset. Eight machine learning classifiers were used to produce 8 candidate models. A 10-fold cross-validation procedure was used to internally evaluate the models and to select the best-performing model for external assessment using the test cohort. In total, 256 of 7238 patients were diagnosed with VTE after transplantation. Among them, 118 patients (46.1%) had catheter-related venous thrombosis, 107 (41.8%) had isolated deep-vein thrombosis (DVT), 20 (7.8%) had isolated pulmonary embolism (PE), and 11 (4.3%) had concomitant DVT and PE. The 2-year overall survival (OS) rate of patients with VTE was 68.8%. Using LASSO regression, 8 potential features were selected from the 54 candidate variables. The best-performing algorithm based on the 10-fold cross-validation runs was a logistic regression classifier. Therefore a prognostic model named BRIDGE was then established to predict the 2-year OS rate. The areas under the curves of the BRIDGE model were 0.883, 0.871, and 0.858 for the training, validation, and test cohorts, respectively. The Hosmer-Lemeshow goodness-of-fit test showed a high agreement between the predicted and observed outcomes. Decision curve analysis indicated that VTE patients could benefit from the clinical application of the prognostic model. A BRIDGE risk score calculator for predicting the study result is available online (47.94.162.105:8080/bridge/). We established the BRIDGE model to precisely predict the risk for all-cause death in VTE patients after allo-HSCT. Identifying VTE patients who have a high risk of death can help physicians treat these patients in advance, which will improve patient survival.

Aspirin use and bleeding events during thrombocytopenia after autologous stem-cell transplantation for multiple myeloma

Background

In patients with cardiovascular (CV) comorbidities that necessitate antiplatelet therapy (APT), its optimal management during chemotherapy-induced thrombocytopenia remains elusive, as the risk of bleeding has to be balanced against the risk of CV events. The purpose of this study was to assess the risk for bleeding with APT during thrombocytopenia in patients with multiple myeloma undergoing high-dose chemotherapy and subsequent autologous stem-cell transplantation (ASCT) with and without acetylsalicylic acid (ASA) as comedication.

Methods

We assessed patients who underwent ASCT at the Heidelberg University Hospital between 2011 and 2020 for bleeding events, management strategies for ASA intake during thrombocytopenia, transfusion requirements, and the occurrence of CV events.

Results

There were 57/1,113 patients who continued ASA until at least 1 day after ASCT; thus, a continuous platelet inhibition during thrombocytopenia was assumed. Most of the patients (41/57) continued ASA until they had a platelet count of 20-50/nl. This range reflects the kinetics of thrombocytopenia and nondaily measurements of platelets during ASCT. A tendency toward a higher risk for bleeding events in the ASA group was demonstrated (1.9% (control group) vs. 5.3% (ASA), p = 0.082). The risk factors for bleeding in multivariate analysis were the duration of thrombocytopenia < 50/nl, a history of gastrointestinal bleeding, and diarrhea. The factors predicting the duration of thrombocytopenia were age >60 years, a hematopoietic stem-cell transplantation comorbidity index ≥3, and an impaired bone marrow reserve at admission. CV events occurred in three patients; none of them took ASA or had an indication for APT.

Conclusions

The intake of ASA until thrombocytopenia with a platelet count of 20-50/nl appears safe, although an elevated risk cannot be excluded. If ASA is indicated for the secondary prevention of CV events, the evaluation of risk factors for bleeding and a prolonged time of thrombocytopenia before conditioning is crucial to adapt the strategy for ASA intake during thrombocytopenia.

Incidence and risk factors associated with bleeding and thrombosis following chimeric antigen receptor T-cell therapy

Clinically significant bleeding occurred in 9% of patients after CAR T therapy and was associated with features of systemic coagulopathy.

Low baseline platelets and possibly high-grade ICANS are risk factors for bleeding and require close monitoring for bleeding up to 1 month.

Bleeding and thrombotic events are an emerging toxicity associated with chimeric antigen receptor (CAR) therapies. To determine their incidence, we retrospectively analyzed consecutive adult patients (N = 127) with large B-cell lymphoma (LBCL) or B-cell acute lymphoblastic leukemia (B-ALL) treated from 2017 through 2020 with axicabtagene ciloleucel (axi-cel; n = 89) or a bispecific CD19/CD22 CAR (n = 38). Twelve (9.4%) and 8 (6.3%) patients developed bleeding and thrombosis within the first 3 months, respectively. In the axi-cel subgroup, these occurred in 11.2% and 6.7%, respectively. Bleeding occurred between days 8 and 30 (median, 17.5) and thrombosis between days 2 and 91 (median, 29). Bleeding sites included genitourinary, soft tissue, intracranial, gastrointestinal, and pulmonary and were associated with features of consumptive coagulopathy. On univariate analysis, patients with bleeding were older, had lower baseline platelets (86 × 10³/μL vs 178 × 10³/μL; P < .01), lower platelet and fibrinogen nadirs , and elevated lactate dehydrogenase. Immune effector cell (IEC)–associated neurotoxicity syndrome (ICANS) grade ≥3 was associated with increased bleeding (50% vs 15%; P = .01), thrombosis (50% vs 16%; P = .04), prothrombin time prolongation, hypofibrinogenemia, and elevated D-dimer. Low pretreatment platelet counts were associated with bleeding in a multivariate logistic regression model. Patients with thrombocytopenia or severe ICANS are at increased risk of bleeding and should be closely monitored, particularly within the first month after CAR therapy. Future studies in larger cohorts should assess risk factors for systemic coagulopathies in CAR T therapy, including their association with neurotoxicity.