Search

Immune thrombotic thrombocytopenic purpura (iTTP) is a chronically relapsing disorder caused by autoantibody mediated deficiency of ADAMTS13. Rituximab is frequently administered to prevent relapses, but whether the durability of rituximab is maintained with subsequent treatment courses has not been studied. Using the United States Thrombotic Microangiopathy Consortium (USTMA) retrospective iTTP registry, we evaluated clinical relapse free survival (RFS) with subsequent courses of rituximab treatment in multiply relapsing patients. Separately, we evaluated overall RFS (composite of time to clinical relapse, ADAMTS13 relapse, or preemptive rituximab) in a prospective iTTP cohort from the Johns Hopkins University and the University of Minnesota. In the USTMA registry, median clinical RFS was shorter after the 2nd or subsequent rituximab-treated episode compared to the first (2.1 vs 6.0 years, P = 0.04). White patients' clinical relapse risk after the second and subsequent rituximab courses was not significantly different compared to the first [HR=1.86 (95% CI 0.22-15.80), P=0.57], while for Black patients, clinical relapse risk was significantly higher after the second or subsequent courses [HR=2.82 (95% CI 1.52-5.24), P=0.001]. In the prospective cohort, overall RFS progressively shortened after each episode of rituximab treatment with the first episode having the longest RFS (2.8 years IQR 2.0-6.0) and this loss of response durability was most pronounced in Black patients. The durability of rituximab's effect declines with subsequent treatments, which is more pronounced in Black patients who may benefit from closer monitoring and alternative immunomodulatory approaches such as maintenance rituximab and consideration of other agents., (Copyright © 2024 American Society of Hematology.)

Background: Mortality due to immune-mediated thrombotic thrombocytopenic purpura (iTTP) remains significant. Predicting mortality risk may potentially help individualize treatment. The French Thrombotic Microangiopathy (TMA) Reference Score has not been externally validated in the United States. Recent advances in machine learning technology can help analyze large numbers of variables with complex interactions for the development of prediction models., Objectives: To validate the French TMA Reference Score in the United States Thrombotic Microangiopathy (USTMA) iTTP database and subsequently develop a novel mortality prediction tool, the USTMA TTP Mortality Index., Methods: We analyzed variables available at the time of initial presentation, including demographics, symptoms, and laboratory findings. We developed our model using gradient boosting machine, a machine learning ensemble method based on classification trees, implemented in the R package gbm., Results: In our cohort ( n = 419), the French score predicted mortality with an area under the receiver operating characteristic curve of 0.63 (95% CI: 0.50-0.77), sensitivity of 0.35, and specificity of 0.84. Our gradient boosting machine model selected 8 variables to predict acute mortality with a cross-validated area under the receiver operating characteristic curve of 0.77 (95% CI: 0.71-0.82). The 2 cutoffs corresponded to sensitivities of 0.64 and 0.50 and specificities of 0.76 and 0.87, respectively., Conclusion: The USTMA Mortality Index was acceptable for predicting mortality due to acute iTTP in the USTMA registry, but not sensitive enough to rule out death. Identifying patients at high risk of iTTP-related mortality may help individualize care and ultimately improve iTTP survival outcomes. Further studies are needed to provide external validation. Our model is one of many recent examples where machine learning models may show promise in clinical prediction tools in healthcare., (© 2024 The Author(s).)