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A model for predicting day-100 stem cell transplant-related mortality in AL amyloidosis.
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A model for predicting day-100 stem cell transplant-related mortality in AL amyloidosis. Bone marrow transplantation Muchtar, E., Dispenzieri, A., Sanchorawala, V., Hassan, H., Mwangi, R., Maurer, M., Buadi, F., Lee, H. C., Qazilbash, M., Kin, A., Zonder, J., Arai, S., Chin, M. M., Chakraborty, R., Lentzsch, S., Magen, H., Shkury, E., Sarubbi, C., Landau, H., Schönland, S., Hegenbart, U., Gertz, M. 2025Abstract
Autologous stem cell Transplant (ASCT)-related mortality (TRM) in AL amyloidosis remains elevated. AL amyloidosis patients (n?=?1718) from 9 centers, transplanted 2003-2020 were included. Pre-ASCT variables of interest were assessed for association with day-100 all-cause mortality. A random forest (RF) classifier with 10-fold cross-validation assisted in variable selection. The final model was fitted using logistic regression. The median age at ASCT was 58 years. Day-100 TRM occurred in 75 patients (4.4%) with the predominant causes being shock, high-grade arrhythmia, and organ failure. Ten factors were associated with day-100 TRM on univariate analysis. RF classifier using these variables generated a model with an area under the curve (AUC) of 0.72?±?0.12. To refine the model selection using importance hierarchy function, a 4-variable model [NT-proBNP/BNP, serum albumin, ECOG performance status (PS), and systolic blood pressure] was built with an AUC of 0.70?±?0.12. Based on logistic regression coefficients, ECOG PS 2/3 was assigned two points while other adverse predictors 1-point each. The model score range was 0-5, with a day-100 TRM of 0.46%, 3.2%, 5.8%, and 14.5% for 0, 1, 2, and =3 points, respectively. This model to predict day-100 TRM in AL amyloidosis allows better-informed decision-making in this heterogeneous disease.
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